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SICStus Prolog

This manual documents SICStus Prolog 3.9, February 2002.

Prolog is a simple but powerful programming language developed at the University of Marseilles, as a practical tool for programming in logic. From a user's point of view the major attraction of the language is ease of programming. Clear, readable, concise programs can be written quickly with few errors.


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Introduction

Prolog is a simple but powerful programming language developed at the University of Marseilles [Roussel 75], as a practical tool for programming in logic [Kowalski 74]. From a user's point of view the major attraction of the language is ease of programming. Clear, readable, concise programs can be written quickly with few errors.

For an introduction to programming in Prolog, readers are recommended to consult [Sterling & Shapiro 86]. However, for the benefit of those who do not have access to a copy of this book, and for those who have some prior knowledge of logic programming, a summary of the language is included. For a more general introduction to the field of Logic Programming see [Kowalski 79]. See Prolog Intro.

This manual describes a Prolog system developed at the Swedish Institute of Computer Science. Parts of the system were developed by the project "Industrialization of SICStus Prolog" in collaboration with Ericsson Telecom AB, NobelTech Systems AB, Infologics AB and Televerket. The system consists of a WAM emulator written in C, a library and runtime system written in C and Prolog and an interpreter and a compiler written in Prolog. The Prolog engine is a Warren Abstract Machine (WAM) emulator [Warren 83]. Two modes of compilation are available: in-core i.e. incremental, and file-to-file. When compiled, a predicate will run about 8 times faster and use memory more economically. Implementation details can be found in [Carlsson 90] and in several technical reports available from SICS.

SICStus Prolog follows the mainstream Prolog tradition in terms of syntax and built-in predicates. As of release 3.8, SICStus Prolog provides two execution modes: the iso mode, which is fully compliant with the International Standard ISO/IEC 13211-1 (PROLOG: Part 1--General Core); and the sicstus mode, which is largely compatible with e.g. C-Prolog and Quintus Prolog, supports code written in earlier versions of SICStus Prolog.


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Acknowledgments

The following people have contributed to the development of SICStus Prolog:

Jonas Almgren, Johan Andersson, Stefan Andersson, Nicolas Beldiceanu,
Tamás Benko'', Kent Boortz, Dave Bowen, Per Brand, Göran Båge,
Mats Carlsson, Per Danielsson, Jesper Eskilson, Lena Flood, György
Gyaraki, Dávid Hanák, Seif Haridi, Ralph Haygood, Christian
Holzbaur, Tom Howland, Key Hyckenberg, Per Mildner, Richard O'Keefe,
Greger Ottosson, László Péter, Dan Sahlin, Peter Schachte, Rob
Scott, Thomas Sjöland, Péter Szeredi, Tamás Szeredi, Peter Van
Roy, Johan Widén, David Warren, and Emil Åström.

The Industrialization of SICStus Prolog (1988-1991) was funded by

Ericsson Telecom AB, NobelTech Systems AB, Infologics AB and
Televerket under the National Swedish Information Technology
Program IT4.

The development of release 3 (1991-1995) was funded in part by

Ellemtel Utvecklings AB

This manual is based on DECsystem-10 Prolog User's Manual by

D.L. Bowen, L. Byrd, F.C.N. Pereira,
L.M. Pereira, D.H.D. Warren

See CLPQR, for acknowledgments relevant to the clp(Q,R) constraint solver.

See CLPFD, for acknowledgments relevant to the clp(FD) constraint solver.

UNIX is a trademark of Bell Laboratories. MSDOS and Windows is a trademark of Microsoft Corp. OS/2 is a trademark of IBM Corp.


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Notational Conventions


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Keyboard Characters

When referring to keyboard characters, printing characters are written thus: a, while control characters are written like this: ^A. Thus ^C is the character you get by holding down the <CTL> key while you type c. Finally, the special control characters carriage-return, line-feed and space are often abbreviated to <RET>, <LFD> and <SPC> respectively.

Throughout, we will assume that ^D is the EOF character (it's usually ^Z under Windows) and that ^C is the interrupt character. In most contexts, the term end_of_file terminated by a full stop (.) can be typed instead of the EOF character.


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Mode Spec

When introducing a built-in predicate, we shall present its usage with a mode spec which has the form name(arg, ..., arg) where each arg denotes how that argument should be instantiated in goals, and has one of the following forms:

:ArgName
This argument should be instantiated to a term denoting a goal or a clause or a predicate name, or which otherwise needs special handling of module prefixes. The argument is subject to module name expansion (see Meta Exp).
+ArgName
This argument should be instantiated to a non-variable term.
-ArgName
This argument should be uninstantiated.
?ArgName
This argument may or may not be instantiated.

Mode specs are not only used in the manual, but are part of the syntax of the language as well. When used in the source code, however, the ArgName part must be omitted. That is, arg must be either :, +, -, or ?.


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Development and Runtime Systems

The full Prolog system with top-level, compiler, debugger etc. is known as the development system.

It is possible to link user-written C code with a subset of SICStus Prolog to create runtime systems. When introducing a built-in predicate, any limitations on its use in runtime systems will be mentioned.


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Function Prototypes

Whenever this manual documents a C function as part of SICStus Prolog's foreign language interface, the function prototype will be displayed in ANSI C syntax.


Node:ISO Compliance, Previous:Function Prototypes, Up:Notation

ISO Compliance

SICStus Prolog provides two execution modes: the iso mode, which is fully compliant with the International Standard ISO/IEC 13211-1 (PROLOG: Part 1--General Core), and the sicstus mode, which supports code written in earlier versions of SICStus Prolog. The execution mode can be changed using the Prolog flag language; see State Info. Note, however, that SICStus Prolog does not offer a strictly conforming mode which rejects uses of implementation specific features.

To aid programmers who wish to write standard compliant programs, built-in predicates that are part of the ISO Prolog Standard are annotated with [ISO] in this manual. If such a predicate behaves differently in sicstus mode, an appropriate clarification is given. For the few predicates that have a completely different meaning in the two modes, two separate descriptions are given. The one for the iso mode is annotated with [ISO only], while the sicstus mode version is annotated with [SICStus only].


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Glossary

abolish
To abolish a predicate is to retract all the predicate's clauses and to remove all information about it from the Prolog system, to make it as if that predicate had never existed.
advice-point
A special case of breakpoint, the advice breakpoint. It is distinguished from spypoints in that it is intended for non-interactive debugging, such as checking of program invariants, collecting information, profiling, etc.
aligned pointer
An aligned pointer is NULL or an address having the four most significant bits consistent with the smallest non-NULL value returned by the function SP_malloc(). In particular, under Linux, these bits must be zero. Furthermore, the address must be aligned on a four bytes boundary. Aligned pointers are represented by integers in Prolog. In particular, NULL is represented by 0. Aligned pointers are relevant in the foreign language interface, in stream_code/2, and in the memory manager's bottom layer.
alphanumeric
An alphanumeric character is any of the lowercase characters from a to z, the uppercase characters from A to Z, the numerals from 0 to 9, or underscore (_).
ancestors
An ancestor of a goal is any goal which the system is trying to solve when it calls that goal. The most distant ancestor is the goal which was typed at the top-level prompt.
anonymous
An anonymous variable is one which has no unique name, and whose value is therefore inaccessible. An anonymous variable is denoted by an underscore (_).
argument
See predicate, structure, and arity.
arity
The arity of a structure is its number of arguments. For example, the structure customer(jones,85) has an arity of 2.
atom
A character sequence used to uniquely denote some entity in the problem domain. A number is not an atom. Unless character escapes have been switched off, examples of legal atoms are:
hello   *   :=   '#$%'   'New York'   'don\'t'

See Atoms. Atoms are recognized by the built-in predicate atom/1. Each Prolog atom is represented internally by a unique integer, represented in C as an SP_atom.

atomic term
Synonym for constant.
backtrace
A collection of information on the control flow of the program, gathered by the debugger. Also the display of this information produced by the debugger. The backtrace includes data on goals that were called but not exited and also on goals that exited nondeterministically.
backtracking
The process of reviewing the goals that have been satisfied and attempting to resatisfy these goals by finding alternative solutions.
binding
The process of assigning a value to a variable; used in unification.
blocked goal
A goal which is suspended because it is not instantiated enough.
body
The body of a clause consists of the part of a Prolog clause following the :- symbol.
breakpoint
A description of certain invocations in the program where the user wants the debugger to stop, or to perform some other actions. A breakpoint is specific if it applies to the calls of a specific predicate, possibly under some conditions; otherwise, it is generic. Depending on the intended usage, breakpoints can be classified as debugger breakpoints, also known as spypoints, or advice breakpoints, also called advice-points; see Advanced Debugging.
breakpoint spec
A term describing a breakpoint. Composed of a test part, specifying the conditions under which the breakpoint should be applied, and an action part, specifying the effects of the breakpoint on the execution.
buffer
A temporary workspace in Emacs that contains a file being edited.
built-in predicate
A predicate that comes with the system and which does not have to be explicitly loaded before it is used.
callable term
A callable term is either a compound term or an atom. Callable terms are recognized by the built-in predicate callable/1.
character code
An integer which is the numeric representation of a character. SICStus Prolog supports character codes in the range 0..2147483647 (i.e. 2^31-1). However, to be able to input or output character codes larger than 255, one needs to use the appropriate wide character external encoding.
character code set
A subset of the set {0, ..., 2^31-1} that can be handled by the external encoding. SICStus Prolog assumes that the character code set is an extension of the ASCII code set, i.e. it includes codes 0..127, and these codes are interpreted as ASCII characters
character-conversion mapping
SICStus Prolog maintains a character-conversion mapping which is used while reading terms and programs. Initially, the mapping prescribes no character conversions. It can be modified by the built-in predicate char_conversion(In, Out), following which In will be converted to Out. Character coversion can be switched off by the char_conversion Prolog flag.
character-type mapping
A function mapping each element of the character code set to one of the character categories (layout, letter, symbol-char, etc.), required for parsing tokens.
choicepoints
A memory block representing outstanding choices for some goals or disjunctions.
clause
A fact or a rule. A rule comprises a head and a body. A fact consists of a head only, and is equivalent to a rule with the body true.
conjunction
A series of goals connected by the connective "and" (that is, a series of goals whose principal operator is ,).
compactcode
Virtual code representation of compiled code. A reasonable compromise between performance and space requirement. A valid value for the compiling Prolog flag.
compile
To load a program (or a portion thereof) into Prolog through the compiler. Compiled code runs more quickly than interpreted code, but you cannot debug compiled code in as much detail as interpreted code.
compound term
A compound term is a name which is an atom together with one or more arguments. For example, in the term father(X), father is the name, and X is the first and only argument. The argument to a compound term can be another compound term, as in father(father(X)). Compound terms are recognized by the built-in predicate compound/1.
console-based executable
An executable which inherits the standard streams from the process that invoked it, e.g. a UNIX shell or a DOS-prompt.
constant
An integer (for example: 1, 20, -10), a floating-point number (for example: 12.35), or an atom. Constants are recognized by the built-in predicate atomic/1.
consult
To load a program (or a portion thereof) into Prolog through the interpreter. Interpreted code runs more slowly than compiled code, but you can debug interpreted code in more detail than compiled code.
creep
What the debugger does in trace mode, also known as single-stepping. It goes to the next port of a procedure box and prints the goal, then prompts you for input. See Basic Debug.
cursor
The point on the screen at which typed characters appear. This is usually highlighted by a line or rectangle the size of one space, which may or may not blink.
cut
Written as !. A built-in predicate that succeeds when encountered; if backtracking should later return to the cut, the goal that matched the head of the clause containing the cut fails immediately.
database
The Prolog database comprises all of the clauses which have been loaded or asserted into the Prolog system or which have been asserted, except those clauses which have been retracted or abolished.
database reference
A compound term denoting a unique reference to a dynamic clause.
debug
A mode of program execution in which the debugger stops to print the current goal only at procedures which have spypoints set on them (see leap).
debugcode
Interpreted representation of compiled code. A valid value for the compiling Prolog flag.
declaration
A declaration looks like a directive, but is not executed but conveys information about procedures about to be loaded.
deinit function
A function in a foreign resource which is called prior to unloading the resource.
determinate
A procedure is determinate if it can supply only one answer.
development system
A stand-alone executable with the full programming environment, including top-level, compiler, debugger etc. The default sicstus executable is a development system; new development systems containing pre-linked foreign resources can also be created.
directive
A directive is a goal preceded by the prefix operator :-, whose intuitive meaning is "execute this as a query, but do not print out any variable bindings."
disjunction
A series of goals connected by the connective "or" (that is, a series of goals whose principal operator is ;).
dynamic predicate
A predicate that can be modified while a program is running. A predicate must explicitly be declared to be dynamic or it must be added to the database via one of the assertion predicates.
encoded string
A sequence of bytes representing a sequence of possibly wide character codes, using the UTF-8 encoding.
escape sequence
A sequence of characters beginning with \ inside certain syntactic tokens (see Escape Sequences).
export
A module exports a procedure so that other modules can import it.
external encoding (of wide characters)
A way of encoding sequences of wide characters as sequences of (8-bit) bytes, used in stream input and output.
fact
A clause with no conditions--that is, with an empty body. A fact is a statement that a relationship exists between its arguments. Some examples, with possible interpretations, are:
king(louis, france).   % Louis was king of France.
have_beaks(birds).     % Birds have beaks.
employee(nancy, data_processing, 55000).
                     % Nancy is an employee in the
                     % data processing department.

fastcode
Native code representation of compiled code. The fastest, but also the most space consuming representation. Only available for Sparc platforms. A valid value for the compiling Prolog flag.
filename
An atom or a compound term denoting the name of a file. The rules for mapping such terms to absolute filenames are described in Input Output.
floundered query
A query where all unsolved goals are blocked.
foreign predicate
A predicate that is defined in a language other than Prolog, and explicitly bound to Prolog predicates by the Foreign Language Interface.
foreign resource
A named set of foreign predicates.
functor
The functor of a compound term is its name and arity. For example, the compound term foo(a,b) is said to have "the functor foo of arity two", which is generally written foo/2.

The functor of a constant is the term itself paired with zero. For example, the constant nl is said to have "the functor nl of arity zero", which is generally written nl/0.

garbage collection
The freeing up of space for computation by making the space occupied by terms which are no longer available for use by the Prolog system.
generalized predicate spec
A generalized predicate spec is a term of one of the following forms. It is always interpreted wrt. a given module context:
Name
all predicates called Name no matter what arity, where Name is an atom for a specific name or a variable for all names, or
Name/Arity
the predicate of that name and arity, or
Name/(Low-High)
Name/[Low-High]
the predicates of that name with arity in the range Low-High, or
Name/[Arity,...,Arity]
the predicates of that name with one of the given arities, or
Module:Spec
specifying a particular module Module instead of the default module, where Module is an atom for a specific module or a variable for all modules, or
[Spec,...,Spec]
the set of all predicates covered by the Specs.

glue code
Interface code between the Prolog engine and foreign predicates. Automatically generated by the foreign language interface as part of building a linked foreign resource.
goal
A simple goal is a predicate call. When called, it will either succeed or fail.

A compound goal is a formula consisting of simple goals connected by connectives such as "and" (,) or "or" (;).

A goal typed at the top-level is called a query.

ground
A term is ground when it is free of (unbound) variables. Ground terms are recognized by the built-in predicate ground/1.
head
The head of a clause is the single goal which will be satisfied if the conditions in the body (if any) are true; the part of a rule before the :- symbol. The head of a list is the first element of the list.
hook predicate
A hook predicate is a procedure that somehow alters or customizes the behavior of a hookable predicate.
hookable predicate
A hookable predicate is a built-in predicate whose behavior is somehow altered or customized by a hook predicate.
import
Exported procedures in a module can be imported by other modules. Once a procedure has been imported by a module, it can be called, or exported, as if it were defined in that module.

There are two kinds of importation: procedure-importation, in which only specified procedures are imported from a module; and module-importation, in which all the predicates made exported by a module are imported.

indexing
The process of filtering a set of potentially matching clauses of a procedure given a goal. For interpreted and compiled code, indexing is done on the principal functor of the first argument. Indexing is coarse w.r.t. big integers and floats.
init function
A function in a foreign resource which is called upon loading the resource.
initialization
An initialization is a goal that is executed when the file in which the initialization is declared is loaded, or upon reinitialization. A initialization is declared as a directive :- initialization Goal.
instantiation
A variable is instantiated if it is bound to a non-variable term; that is, to an atomic term or a compound term.
internal encoding (of wide characters)
A way of encoding wide character sequences internally within the Prolog system. SICStus Prolog uses a technique known as the UTF-8 encoding for this purpose.
interpret
Load a program or set of clauses into Prolog through the interpreter (also known as consulting). Interpreted code runs more slowly than compiled code, but more extensive facilities are available for debugging interpreted code.
invocation box
Same as procedure box.
leap
What the debugger does in debug mode. The debugger shows only the ports of procedures that have spypoints on them. It then normally prompts you for input, at which time you may leap again to the next spypoint (see trace).
leashing
Determines how frequently the debugger will stop and prompt you for input when you are tracing. A port at which the debugger stops is called a "leashed port".
linked foreign resource
A foreign resource that is ready to be installed in an atomic operation, normally represented as a shared object or DLL.
list
A list is written as a set of zero or more terms between square brackets. If there are no terms in a list, it is said to be empty, and is written as []. In this first set of examples, all members of each list are explicitly stated:
[aa, bb,cc]  [X, Y]  [Name]  [[x, y], z]

In the second set of examples, only the first several members of each list are explicitly stated, while the rest of the list is represented by a variable on the right-hand side of the "rest of" operator, |:

[X | Y]  [a, b, c | Y]  [[x, y] | Rest]

| is also known as the "list constructor." The first element of the list to the left of | is called the head of the list. The rest of the list, including the variable following | (which represents a list of any length), is called the tail of the list.

load
To load a Prolog clause or set of clauses, in source or binary form, from a file or set of files.
meta-call
The process of interpreting a callable term as a goal. This is done e.g. by the built-in predicate call/1.
meta-predicate
A meta-predicate is one which calls one or more of its arguments; more generally, any predicate which needs to assume some module in order to operate is called a meta-predicate. Some arguments of a meta-predicate are subject to module name expansion.
mode spec
A term name(arg, ..., arg) where each arg denotes how that argument should be instantiated in goals. See Mode Spec.
module
A module is a set of procedures in a module-file. The name of a module is an atom. Some procedures in a module are exported. The default module is user.
module name expansion
The process by which certain arguments of meta-predicates get prefixed by the source module. See Meta Exp.
module-file
A module-file is a file that is headed with a module declaration of the form:
:- module(ModuleName, ExportedPredList).

which must appear as the first term in the file.

multifile predicate
A predicate whose definition is to be spread over more than one file. Such a predicate must be preceded by an explicit multifile declaration in all files containing clauses for it.
mutable term
A special form of compound term which is subject to destructive assignment. See Modify Term. Mutable terms are recognized by the built-in predicate is_mutable/1.
name clash
A name clash occurs when a module attempts to define or import a procedure that it has already defined or imported.
occurs-check
A test to ensure that binding a variable does not bind it to a term where that variable occurs.
one-char atom
An atom which consists of a single character.
operator
A notational convenience that allows you to express any compound term in a different format. For example, if likes in
| ?- likes(sue, cider).

is declared an infix operator, the query above could be written:

| ?- sue likes cider.

An operator does not have to be associated with a predicate. However, certain built-in predicates are declared as operators. For example,

| ?- =..(X, Y).

can be written as

| ?- X =.. Y.

because =.. has been declared an infix operator.

Those predicates which correspond to built-in operators are written using infix notation in the list of built-in predicates at the beginning of the part that contains the reference pages.

Some built-in operators do not correspond to built-in predicates; for example, arithmetic operators. See Standard Operators for a list of built-in operators.

pair
A compound term K-V. Pairs are used by the built-in predicate keysort/2 and by many library modules.
parent
The parent of the current goal is a goal which, in its attempt to obtain a successful solution to itself, is calling the current goal.
port
One of the five key points of interest in the execution of a Prolog procedure. See Procedure Box for a definition.
pre-linked foreign resource
A linked foreign resource that is linked into a stand-alone executable as part of building the executable.
precedence
A number associated with each Prolog operator, which is used to disambiguate the structure of the term represented by an expression containing a number of operators. Operators of lower precedence are applied before those of higher precedence; the operator with the highest precedence is considered the principal functor of the expression. To disambiguate operators of the same precedence, the associativity type is also necessary. See Operators.
predicate
A functor that specifies some relationship existing in the problem domain. For example, < /2 is a built-in predicate specifying the relationship of one number being less than another. In contrast, the functor + /2 is not (normally used as) a predicate.

A predicate is either built-in or is implemented by a procedure.

predicate spec
A compound term name/arity or module:name/arity denoting a predicate.
procedure
A set of clauses in which the head of each clause has the same predicate. For instance, a group of clauses of the following form:
connects(san_francisco, oakland, bart_train).
connects(san_francisco, fremont, bart_train).
connects(concord, daly_city, bart_train).

is identified as belonging to the procedure connects/3.

procedure box
A way of visualizing the execution of a Prolog procedure, A procedure box is entered and exited via ports.
profiledcode
Virtual code representation of compiled code, instrumented for profiling. A valid value for the compiling Prolog flag.
profiling
The process of gathering execution statistics of parts of the program, essentially counting the times selected program points have been reached.
program
A set of procedures designed to perform a given task.
PO file
A PO (Prolog object) file contains a binary representation of a set of modules, predicates, clauses and directives. They are portable between different platforms, except between 32-bit and 64-bit platforms. They are created by save_files/2, save_modules/2, and save_predicates/2.
QL file
A QL (quick load) file contains an intermediate representation of a compiled source code file. They are portable between different platforms, but less efficient than PO files, and are therefore obsolescent. They are created by fcompile/1.
query
A query is a question put by the user to the Prolog system. A query is written as a goal followed by a full-stop in response to the Prolog system prompt. For example,
| ?- father(edward, ralph).

refers to the predicate father/2. If a query has no variables in it, the system will respond either yes or no. If a query contains variables, the system will try to find values of those variables for which the query is true. For example,

| ?- father(edward, X).
X = ralph

After the system has found one answer, the user can direct the system to look for additional answers to the query by typing ;.

recursion
The process in which a running procedure calls itself, presumably with different arguments and for the purpose of solving some subset of the original problem.
region
The text between the cursor and a previously set mark in an Emacs buffer.
rule
A clause with one or more conditions. For a rule to be true, all of its conditions must also be true. For example,
has_stiff_neck(ralph) :-
   hacker(ralph).

This rule states that if the individual ralph is a hacker, then he must also have a stiff neck. The constant ralph is replaced in

has_stiff_neck(X) :-
   hacker(X).

by the variable X. X unifies with anything, so this rule can be used to prove that any hacker has a stiff neck.

runtime kernel
A shared object or DLL containing the SICStus virtual machine and other runtime support for stand-alone executables.
runtime system
A stand-alone executable with a restricted set of built-in predicates and no top-level. Stand-alone applications containing debugged Prolog code and destined for end-users are typically packaged as runtime systems.
saved-state
A snapshot of the state of Prolog saved in a file by save_program/[1,2].
semantics
The relation between the set of Prolog symbols and their combinations (as Prolog terms and clauses), and their meanings. Compare syntax.
sentence
A clause or directive.
side-effect
A predicate which produces a side-effect is one which has any effect on the "outside world" (the user's terminal, a file, etc.), or which changes the Prolog database.
simple term
A simple term is a constant or a variable. Simple terms are recognized by the built-in predicate simple/1.
small integer
An integer in the range [-2^25,2^25-1] on 32-bit platforms, or [-2^56,2^56-1] on 64-bit platforms.
source code
The human-readable, as opposed to the machine-executable, representation of a program.
source module
The module which is the context of a file being loaded. For module-files, the source module is named in the file's module declaration. For other files, the source module is inherited from the context.
SP_term_ref
A "handle" object providing an interface from C to Prolog terms.
spypoint
A special case of breakpoint, the debugger breakpoint, intended for interactive debugging. Its simplest form, the plain spypoint instructs the debugger to stop at all ports of all invocations of a specified predicate. Conditional spypoints apply to a single predicate, but are more selective: the user can supply applicability tests and prescribe the actions to be carried out by the debugger. A generic spypoint is like a conditional spypoint, but not restricted to a single predicate. See Advanced Debugging.
stand-alone executable
A binary program which can be invoked from the operating system, containing the SICStus runtime kernel. A stand-alone executable is a development system (e.g. the default sicstus executable), or a runtime system. Both kinds are created by the application builder. A stand-alone executable does not itself contain any Prolog code; all Prolog code must be loaded upon startup.
static predicate
A predicate that can be modified only by being reloaded or by being abolished. See dynamic predicate.
stream
An input/output channel. See Input Output.
stream alias
A name assigned to a stream at the time of opening, which can be referred to in I/O predicates. Must be an atom. There are also three predefined aliases for the standard streams: user_input, user_output and user_error.
stream position
A term representing the current position of a stream. This position is determined by the current byte, character and line counts and line position. Standard term comparison on stream position terms works as expected. When SP1 and SP2 refer to positions in the same stream, SP1@<SP2 if and only if SP1 is before SP2 in the stream. You should not otherwise rely on their internal representation.
string
A special syntactic notation which is, by default, equivalent to a list of character codes e.g.
"SICStus"

By setting the Prolog flag double_quotes, the meaning of strings can be changed. With an appropriate setting, a string can be made equivalent to a list of one-char atoms, or to an atom. Strings are not a separate data type.

subterm selector
A list of argument positions selecting a subterm within a term (i.e. the subterm can be reached from the term by successively selecting the argument positions listed in the selector). Example: within the term q, (r, s; t) the subterm s is selected by the selector [2, 1, 2].
syntax
The part of Prolog grammar dealing with the way in which symbols are put together to form legal Prolog terms. Compare semantics.
system encoding (of wide characters)
A way of encoding wide character strings, used or required by the operating system environment.
term
A basic data object in Prolog. A term can be a constant, a variable, or a compound term.
trace
A mode of program execution in which the debugger creeps to the next port and prints the goal.
type-in module
The module which is the context of queries.
unblocked goal
A goal which is not blocked.
unbound
A variable is unbound if it has not yet been instantiated.
unification
The process of matching a goal with the head of a clause during the evaluation of a query, or of matching arbitrary terms with one another during program execution.

The rules governing the unification of terms are:


unit clause
See fact.
UTF-8 encoding
See internal encoding
variable
A logical variable is a name that stands for objects that may or may not be determined at a specific point in a Prolog program. When the object for which the variable stands is determined in the Prolog program, the variable becomes instantiated. A logical variable may be unified with a constant, a compound term, or another variable. Variables become uninstantiated when the procedure they occur in backtracks past the point at which they were instantiated.

Variables may be written as any sequence of alphanumeric characters starting with either a capital letter or _; e.g.

X   Y   Z   Name   Position   _c   _305  One_stop

See Variables.

volatile
Predicate property. The clauses of a volatile predicate are not saved in saved-states.
windowed executable
An executable which pops up its own window when run, and which directs the standard streams to that window.
zip
Same as leap mode, except no debugging information is collected while zipping.


Node:Run Intro, Next:, Previous:Glossary, Up:Top

How to Run Prolog

SICStus Prolog offers the user an interactive programming environment with tools for incrementally building programs, debugging programs by following their executions, and modifying parts of programs without having to start again from scratch.

The text of a Prolog program is normally created in a file or a number of files using one of the standard text editors. The Prolog interpreter can then be instructed to read in programs from these files; this is called consulting the file. Alternatively, the Prolog compiler can be used for compiling the file.


Node:Start, Next:, Previous:Run Intro, Up:Run Intro

Getting Started

Under UNIX, SICStus Prolog is normally started from one of the shells. On other platforms, it is normally started by clicking on an icon. However, it is often convenient to run SICStus Prolog under GNU Emacs instead. A GNU Emacs interface for SICStus Prolog is described later (see Emacs Interface). From a shell, SICStus Prolog is started by typing:

% sicstus [options] [-a argument...]

where flags have the following meaning:


-f
Fast start. Don't read any initialization file (~/.sicstusrc or ~/.sicstus.ini) on startup. If the flag is omitted and this file exists, SICStus Prolog will consult it on startup after running any initializations and printing the version banners.
-i
Forced interactive. Prompt for user input, even if the standard input stream does not appear to be a terminal.
--iso
--sicstus
Start up in ISO Prolog mode or SICStus Prolog mode respectively. The language mode is set before any prolog-file or initialization file is loaded and any saved-state is restored.
-m
Use malloc()/free() in the memory manager's bottom layer.
-l prolog-file
Ensure that the file prolog-file is loaded on startup. This is done before any initialization file is loaded. Only one -l argument is allowed.
-r saved-state
Restore the saved state saved-state on startup. This is done before any prolog-file or initialization file is loaded. Only one -r argument is allowed.
--goal Goal
Read a term from the text Goal and pass the resulting term to call/1 after all files have been loaded. As usual Goal should be terminated by a full stop (.). Only one --goal argument is allowed.
-a argument...
where the arguments can be retrieved from Prolog by prolog_flag(argv, Args), which will unify Args with argument... represented as a list of atoms.
-B[abspath]
Creates a saved state for a development system. This option is not needed for normal use. If abspath is given, it specifies the absolute pathname for the saved state. NOTE: There must not be a space before the path, or it will be interpreted as a separate option.
-R[abspath]
Equivalent to the -B option, except that it builds a saved state for a runtime system instead.

Under UNIX, a saved state file can be executed directly by typing:

% file argument...

This is equivalent to:

% sicstus -r file [-a argument...]

NOTE: As of release 3.7, saved-states do not store the complete path of the binary sp.exe. Instead, they call the main executable sicstus, which is assumed to be found in the shell's path. If there are several versions of SICStus installed, it is up to the user to make sure that the correct start-script is found.

Notice that the flags are not available when executing saved states--all the command-line arguments are treated as Prolog arguments.

The development system checks that a valid SICStus license exists and responds with a message of identification and the prompt | ?- as soon as it is ready to accept input, thus:

SICStus 3.9.0 ...
Licensed to SICS
| ?-

At this point the top-level is expecting input of a query. You cannot type in clauses or directives immediately (see Inserting Clauses). While typing in a query, the prompt (on following lines) becomes . That is, the | ?- appears only for the first line of the query, and subsequent lines are indented.


Node:Environment Variables, Previous:Start, Up:Start

Environment Variables

The following environment variables can be set before starting SICStus Prolog. Some of these override the default sizes of certain areas. The sizes are given in bytes, but may be followed by K or M meaning kilobytes or megabytes respectively.

SP_CSETLEN
Selects the sub-code-set lengths when the EUC character set is used. For the details, see WCX Environment Variables.
SP_CTYPE
Selects the appropriate character set standard: The supported values are euc (for EUC), utf8 (for Unicode) and iso_8859_1 (for ISO 8859/1). The latter is the default. For the details, see WCX Environment Variables.
SP_PATH
This environment variable can be used to specify the location of the Runtime Library (corresponding to the third argument to SP_initialize()). In most cases there is no need to use it. See Setting SP_PATH under UNIX, for more information.
TMPDIR
If set, indicates the pathname where temporary files should be created. Defaults to /usr/tmp.
GLOBALSTKSIZE
Governs the initial size of the global stack.
LOCALSTKSIZE
Governs the initial size of the local stack.
CHOICESTKSIZE
Governs the initial size of the choicepoint stack.
TRAILSTKSIZE
Governs the initial size of the trail stack.
PROLOGINITSIZE
Governs the size of Prolog's initial memory allocation.
PROLOGMAXSIZE
Defines a limit on the amount of data space which Prolog will use.
PROLOGINCSIZE
Governs the amount of space Prolog asks the operating system for in any given memory expansion.
PROLOGKEEPSIZE
Governs the size of space Prolog retains after performing some computation. By default, Prolog gets memory from the operating system as the user program executes and returns all free memory back to the operating system when the user program does not need any more. If the programmer knows that her program, once it has grown to a certain size, is likely to need as much memory for future computations, then she can advise Prolog not to return all the free memory back to the operating system by setting this variable. Only memory that is allocated above and beyond PROLOGKEEPSIZE is returned to the OS; the rest will be kept.

In addition the following environment variables are set automatically on startup.

SP_APP_DIR
The absolute path to the directory that contains the executable. Also available as the application file search alias.
SP_RT_DIR
The full path to the directory that contains the SICStus run-time. If the application has linked statically to the SICStus run-time then SP_RT_DIR is the same as SP_APP_DIR. Also available as the runtime file search alias.

Send bug reports to sicstus-support@sics.se or use the form at http://www.sics.se/sicstus/bugreport/bugreport.html. Bugs tend actually to be fixed if they can be isolated, so it is in your interest to report them in such a way that they can be easily reproduced.

The mailing list sicstus-users@sics.se is a moderated mailing list for communication among users and implementors. To [un]subscribe, write to sicstus-users-request@sics.se.


Node:Reading In, Next:, Previous:Start, Up:Run Intro

Reading in Programs

A program is made up of a sequence of clauses and directives. The clauses of a predicate do not have to be immediately consecutive, but remember that their relative order may be important (see Procedural).

To input a program from a file file, just type the filename inside list brackets (followed by . and <RET>), thus:

| ?- [file].

This instructs the interpreter to read in (consult) the program. Note that it may be necessary to enclose the filename file in single quotes to make it a legal Prolog atom; e.g.

| ?- ['myfile.pl'].

| ?- ['/usr/prolog/somefile'].

The specified file is then read in. Clauses in the file are stored so that they can later be interpreted, while any directives are obeyed as they are encountered. When the end of the file is found, the system displays on the standard error stream the time spent. This indicates the completion of the query.

Predicates that expect the name of a Prolog source file as an argument use absolute_file_name/3 (see Stream Pred) to look up the file. If no explicit extension is given, this predicate will look for a file with the default extension .pl added as well as for a file without extension. There is also support for libraries.

In general, this query can be any list of filenames, such as:

| ?- [myprog,extras,tests].

In this case all three files would be consulted.

The clauses for all the predicates in the consulted files will replace any existing clauses for those predicates, i.e. any such previously existing clauses in the database will be deleted.

Note that consult/1 in SICStus Prolog behaves like reconsult/1 in DEC-10 Prolog.


Node:Inserting Clauses, Next:, Previous:Reading In, Up:Run Intro

Inserting Clauses at the Terminal

Clauses may also be typed in directly at the terminal, although this is only recommended if the clauses will not be needed permanently, and are few in number. To enter clauses at the terminal, you must give the special query:

| ?- [user].
|

and the new prompt | shows that the system is now in a state where it expects input of clauses or directives. To return to top level, type ^D. The system responds thus:

% consulted user in module user, 20 msec 200 bytes


Node:Queries and Directives, Next:, Previous:Inserting Clauses, Up:Run Intro

Queries and Directives

Queries and directives are ways of directing the system to execute some goal or goals.

In the following, suppose that list membership has been defined by loading the following clauses from a file:

member(X, [X|_]).
member(X, [_|L]) :- member(X, L).

(Notice the use of anonymous variables written _.)


Node:Queries, Next:, Previous:Queries and Directives, Up:Queries and Directives

Queries

The full syntax of a query is ?- followed by a sequence of goals. The top-level expects queries. This is signaled by the initial prompt | ?- . Thus a query at top-level looks like:

| ?- member(b, [a,b,c]).

Remember that Prolog terms must terminate with a full stop (., possibly followed by layout text), and that therefore Prolog will not execute anything until you have typed the full stop (and then <RET>) at the end of the query.

If the goal(s) specified in a query can be satisfied, and if there are no variables as in this example, then the system answers

yes

and execution of the query terminates.

If variables are included in the query, then the final value of each variable is displayed (except for variables whose names begin with _). Thus the query

| ?- member(X, [a,b,c]).

would be answered by

X = a

At this point the system is waiting for input of either just a <RET> or else a ; followed by <RET>. Simply typing <RET> terminates the query; the system responds with yes. However, typing ; causes the system to backtrack (see Procedural) looking for alternative solutions. If no further solutions can be found it outputs no.

While the variable bindings are displayed, all variables occurring in the values are replaced by terms of the form '$VAR'(N) to yield friendlier variable names. Such names come out as a sequence of letters and digits preceded by _. The outcome of some queries is shown below.

| ?- member(X, [tom,dick,harry]).

X = tom ;
X = dick ;
X = harry ;

no
| ?- member(X, [a,b,f(Y,c)]), member(X, [f(b,Z),d]).

X = f(b,c),
Y = b,
Z = c

yes
| ?- member(X, [f(_),g]).

X = f(_A)

yes
| ?-

Directives are like queries except that:

  1. Variable bindings are not displayed if and when the directive succeeds.
  2. You are not given the chance to backtrack through other solutions.


Node:Directives, Previous:Queries, Up:Queries and Directives

Directives

Directives start with the symbol :-. Any required output must be programmed explicitly; e.g. the directive:

:- member(3, [1,2,3]), write(ok).

asks the system to check whether 3 belongs to the list [1,2,3]. Execution of a directive terminates when all the goals in the directive have been successfully executed. Other alternative solutions are not sought. If no solution can be found, the system prints:

* Goal - goal failed

as a warning.

The principal use for directives (as opposed to queries) is to allow files to contain directives which call various predicates, but for which you do not want to have the answers printed out. In such cases you only want to call the predicates for their effect, i.e. you don't want terminal interaction in the middle of consulting the file. A useful example would be the use of a directive in a file which consults a whole list of other files, e.g.

:- [ bits, bobs, main, tests, data, junk ].

If a directive like this were contained in the file myprog then typing the following at top-level would be a quick way of reading in your entire program:

| ?- [myprog].

When simply interacting with the top-level, this distinction between queries and directives is not normally very important. At top-level you should just type queries normally. In a file, queries are in fact treated as directives, i.e. if you wish to execute some goals then the directive in the file must be preceded by :- or ?-; otherwise, it would be treated as a clause.


Node:Syntax Errors, Next:, Previous:Queries and Directives, Up:Run Intro

Syntax Errors

Syntax errors are detected during reading. Each clause, directive or in general any term read in by the built-in predicate read/1 that fails to comply with syntax requirements is displayed on the standard error stream as soon as it is read, along with its position in the input stream and a mark indicating the point in the string of symbols where the parser has failed to continue analysis, e.g.:

| member(X, X$L).
! Syntax error
! , or ) expected in arguments
! in line 5
! member ( X , X
! <<here>>
! $ L ) .

if $ has not been declared as an infix operator.

Note that any comments in the faulty line are not displayed with the error message. If you are in doubt about which clause was wrong you can use the listing/1 predicate to list all the clauses which were successfully read in, e.g.

| ?- listing(member/2).

NOTE: The built in predicates read/[1,2] normaly raise an exception on syntax errors (see Exception). The behavior is controlled by the flag syntax_errors (see prolog_flag/3).


Node:Undefined Predicates, Next:, Previous:Syntax Errors, Up:Run Intro

Undefined Predicates

There is a difference between predicates that have no definition and predicates that have no clauses. The latter case is meaningful e.g. for dynamic predicates (see Declarations) that clauses are being added to or removed from. There are good reasons for treating calls to undefined predicates as errors, as such calls easily arise from typing errors.

The system can optionally catch calls to predicates that have no definition. First the user defined predicate user:unknown_predicate_handler/3 (see Exception) is called. If undefined or if the call fails the action is governed by the state of the unknown/2 flag which can be:

trace
which causes calls to undefined predicates to be reported and the debugger to be entered at the earliest opportunity.
error
which causes calls to such predicates to raise an exception (the default state). See Exception.
warning
which causes calls to such predicates to display a warning message and then fail.
fail
which causes calls to such predicates to fail.

Calls to predicates that have no clauses are not caught.

The built-in predicate unknown(?OldState, ?NewState) unifies OldState with the current state and sets the state to NewState. The built-in predicate debugging/0 prints the value of this state along with its other information. This state is also controlled by the flag unknown (see prolog_flag/3).


Node:Execution, Next:, Previous:Undefined Predicates, Up:Run Intro

Program Execution And Interruption

Execution of a program is started by giving the system a query which contains a call to one of the program's predicates.

Only when execution of one query is complete does the system become ready for another query. However, one may interrupt the normal execution of a query by typing ^C. This ^C interruption has the effect of suspending the execution, and the following message is displayed:

Prolog interruption (h or ? for help) ?

At this point, the development system accepts one-letter commands corresponding to certain actions. To execute an action simply type the corresponding character (lower or upper case) followed by <RET>. The available commands in development systems are:

a
aborts the current computation.
c
continues the execution.
e
exits from SICStus Prolog, closing all files.
h
?
lists available commands.
b
invokes a recursive top-level.
d
z
t
switch on the debugger. See Debug Intro.

If the standard input stream is not connected to the terminal, e.g. by redirecting standard input to a file or a pipe, the above ^C interrupt options are not available. Instead, typing ^C causes SICStus Prolog to exit, and no terminal prompts are printed.


Node:Exiting, Next:, Previous:Execution, Up:Run Intro

Exiting From The Top-Level

To exit from the top-level and return to the shell, either type ^D at the top-level, or call the built-in predicate halt/0, or use the e (exit) command following a ^C interruption.


Node:Nested, Next:, Previous:Exiting, Up:Run Intro

Nested Executions--Break

The Prolog system provides a way to suspend the execution of your program and to enter a new incarnation of the top-level where you can issue queries to solve goals etc. This is achieved by issuing the query (see Execution):

| ?- break.

This invokes a recursive top-level, indicated by the message:

% Break level 1

You can now type queries just as if you were at top-level.

If another call of break/0 is encountered, it moves up to level 2, and so on. To close the break and resume the execution which was suspended, type ^D. The debugger state and current input and output streams will be restored, and execution will be resumed at the predicate call where it had been suspended after printing the message:

% End break


Node:Saving, Next:, Previous:Nested, Up:Run Intro

Saving and Restoring Program States

Once a program has been read, the system will have available all the information necessary for its execution. This information is called a program state.

The state of a program may be saved on disk for future execution. The state consists of all predicates and modules except built-in predicates and clauses of volatile predicates, the current operator declarations, the current character-conversion mapping, the values of all writable Prolog flags except debugging, source_info, and the user_* stream aliases (see State Info), any blackboard data (see Blackboard Primitives), internal database data (see Database), and profiling data (see Profiling), but no information for source-linked debugging.

To save a program into a file File, type the following query. On UNIX platforms, the file becomes executable:

| ?- save_program(File).

You can also specify a goal to be run when a saved program is restored. This is done by:

| ?- save_program(File, start).

where start/0 is the predicate to be called.

Once a program has been saved into a file File, the following query will restore the system to the saved state:

| ?- restore(File).

If a saved state has been moved or copied to another machine, the path names of foreign resources and other files needed upon restore are typically different at restore time from their save time values. To solve this problem, certain atoms will be relocated during restore as follows:

The purpose of this procedure is to be able to build and deploy an application consisting of a saved state and other files as a directory tree with the saved state at the root: as long as the other files maintain their relative position in the deployed copy, they can still be found upon restore.

NOTE: Foreign resources, see Calling C, are unloaded by save_program/[1,2]. The names and paths of the resources, typically $SP_PATH/library relative, are however included in the saved state. After the save, and after restoring a saved state, this information is used to reload the foreign resources again. The state of the foreign resource in terms of global C variables and allocated memory is thus not preserved. Foreign resources may define init and deinit functions to take special action upon loading and unloading; see Init and Deinit Functions.

As of SICStus Prolog 3.8, partial saved states corresponding to a set of source files, modules, and predicates can be created by the built-in predicates save_files/2, save_modules/2, and save_predicates/2 respectively. These predicates create files in a binary format, by default with the prefix .po (for Prolog object file), which can be loaded by load_files/[1,2]. For example, to compile a program split into several source files into a single object file, type:

| ?- compile(Files), save_files(Files, Object).

For each filename given, the first goal will try to locate a source file with the default suffix .pl and compile it into memory. The second goal will save the program just compiled into an object file whose default suffix is .po. Thus the object file will contain a partial memory image.

NOTE: Prolog object files can be created with any suffix, but cannot be loaded unless the suffix is .po!


Node:Emacs Interface, Previous:Saving, Up:Run Intro

Emacs Interface

This section explains how to use the GNU Emacs interface for SICStus Prolog, and how to customize your GNU Emacs environment for it.

Emacs is a powerful programmable editor especially suitable for program development. It is available for free for many platforms, including various UNIX dialects, Windows and MacOS. For information on obtaining Emacs, see http://www.emacs.org. For information specific to GNU Emacs or XEmacs, see http://www.gnu.org and http://www.xemacs.org respectively.

The advantages of using SICStus in the Emacs environment are source-linked debugging, auto indentation, syntax highlighting, help on predefined predicates (requires the SICStus info files to be installed), loading code from inside Emacs, auto-fill mode, and more.

The Emacs interface is not part of SICStus Prolog proper, but is included in the distribution for convenience. It was written by Emil Åström and Milan Zamazal, based on an earlier version of the mode written by Masanobu Umeda. Contributions has also been made by Johan Andersson, Peter Olin, Mats Carlsson, Johan Bevemyr, Stefan Andersson, and Per Danielsson, Henrik Båkman, and Tamás Rozmán. Some ideas and also a few lines of code have been borrowed (with permission) from Oz.el by Ralf Scheidhauer and Michael Mehl, the Emacs major mode for the Oz programming language. More ideas and code have been taken from the SICStus debugger mode by Per Mildner.


Node:Installation, Next:, Previous:Emacs Interface, Up:Emacs Interface

Installation

See The Emacs Interface, for more information about installing the Emacs interface.

There are some differences between GNU Emacs and XEmacs. This will be indicated with Emacs-Lisp comments in the examples.

Customizing Emacs

Version 20 of GNU Emacs and XEmacs introduced a new method for editing and storing user settings. This feature is available from the menu bar as Customize and particular Emacs variables can be customized with M-x customize-variable. Using Customize is the preferred way to modify the settings for emacs and the appropriate customize commands will be indicated below, sometimes together with the old method of directly setting Emacs variables.

Enabling Emacs Support for SICStus

Assuming the Emacs interface for SICStus Prolog has been installed in the default location, inserting the following lines in your ~/.emacs will make Emacs use this mode automatically when editing files with a .pl extension:

(setq load-path
   (cons (expand-file-name "/usr/local/lib/sicstus-3.9.0/emacs")
         load-path))
(autoload 'run-prolog "prolog" "Start a Prolog sub-process." t)
(autoload 'prolog-mode "prolog" "Major mode for editing Prolog programs." t)
(setq prolog-use-sicstus-sd t)
(setq auto-mode-alist (cons '("\\.pl$" . prolog-mode) auto-mode-alist))

where the path in the first line is the file system path to prolog.el (the generic Prolog mode) and sicstus-support.el (SICStus specific code). For example, ~/emacs means that the file is in the user's home directory, in directory emacs. Windows paths can be written like C:/Program Files/SICStus Prolog 3.9.0/emacs.

The last line above makes sure that files ending with .pl are assumed to be Prolog files and not Perl, which is the default Emacs setting. If this is undesirable, remove that line. It is then necessary for the user to manually switch to prolog mode by typing M-x prolog-mode after opening a prolog file, for an alternative approach, see Mode Line.

If the shell command sicstus is not available in the default path, then it is necessary to set the value of the environment variable EPROLOG to a shell command to invoke SICStus Prolog. This is an example for C Shell:

setenv EPROLOG /usr/local/bin/sicstus

Enabling Emacs Support for SICStus Documentation

It is possible to look up the documentation for any built in or library predicate from within Emacs (using C-c ? or the menu). For this to work Emacs must be told about the location of the info-files that make up the documentation.

The default location for the info-files are <prefix>/lib/sicstus-3.9.0/doc/info/ on UNIX platforms and C:/Program Files/SICStus Prolog 3.9.0/doc/info/ on Windows.

Add the following to your ~/.emacs file, assuming INFO is the path to the info files, e.g. C:/Program Files/SICStus Prolog 3.9.0/doc/info/

(setq Info-default-directory-list
   (append Info-default-directory-list '("INFO")))
for GNU Emacs, or
(setq Info-directory-list
   (append Info-directory-list '("INFO")))

for XEmacs. You can also use M-x customize-group <RET> info <RET> if your Emacs is new enough. You may have to quit and restart Emacs for these changes to take effect.


Node:Basic Configuration, Next:, Previous:Installation, Up:Emacs Interface

Basic Configuration

If the following lines are not present in ~/.emacs, we suggest they are added, so that the font-lock mode (syntax coloring support) is enabled for all major modes in Emacs that support it.

(global-font-lock-mode t)       ; GNU Emacs
(setq font-lock-auto-fontify t) ; XEmacs
(setq font-lock-maximum-decoration t)

These settings and more are also available through M-x customize-group <RET> font-lock.

If one wants to add font-locking only to the prolog mode, the two lines above could be replaced by:

(add-hook 'prolog-mode-hook 'turn-on-font-lock)

Similarly, to turn it off only for prolog mode use:

(add-hook 'prolog-mode-hook 'turn-off-font-lock)


Node:Usage, Next:, Previous:Basic Configuration, Up:Emacs Interface

Usage

A prolog process can be started by choosing Run Prolog from the Prolog menu, by typing C-c <RET>, or by typing M-x run-prolog. It is however not strictly necessary to start a prolog process manually since it is automatically done when consulting or compiling, if needed. The process can be restarted (i.e. the old one is killed and a new one is created) by typing C-u C-c <RET>.

Programs are run and debugged in the normal way, with terminal I/O via the *prolog* buffer. The most common debugging predicates are available from the menu or via key-bindings.

A particularly useful feature under the Emacs interface is source-linked debugging. This is enabled or disabled using the Prolog/Source level debugging menu entry. It can also be enabled by setting the Emacs variable prolog-use-sicstus-sd to t in ~/.emacs. Both these methods set the Prolog flag source_info to emacs. Its value should be emacs while loading the code to be debugged and while debugging. If so, the debugger will display the source code location of the current goal when it prompts for a debugger command, by overlaying the beginning of the current line of code with an arrow. If source_info was off when the code was loaded, or if it was asserted or loaded from user, the current goal will still be shown but out of context.

Note that if the code has been modified since it was last loaded, Prolog's line number information may be invalid. If this happens, just reload the relevant buffer.

Consultation and compilation is either done via the menu or with the following key-bindings:

C-c C-f
Consult file.
C-c C-b
Consult buffer.
C-c C-r
Consult region.
C-c C-p
Consult predicate.
C-c C-c f
Compile file.
C-c C-c b
Compile buffer.
C-c C-c r
Compile region.
C-c C-c p
Compile predicate.

The boundaries used when consulting and compiling predicates are the first and last clauses of the predicate the cursor is currently in.

Other useful key-bindings are:

M-n
Go to the next clause.
M-p
Go to the previous clause.
M-a
Go to beginning of clause.
M-e
Go to end of clause.
M-C-c
Mark clause.
M-C-a
Go to beginning of predicate.
M-C-e
Go to end of predicate.
M-C-h
Mark predicate.
M-{
Go to the previous paragraph (i.e. empty line).
M-}
Go to the next paragraph (i.e. empty line).
M-h
Mark paragraph.
M-C-n
Go to matching right parenthesis.
M-C-p
Go to matching left parenthesis.
M-;
Creates a comment at comment-column. This comment will always stay at this position when the line is indented, regardless of changes in the text earlier on the line, provided that prolog-align-comments-flag is set to t.
C-c C-t
C-u C-c C-t
Enable and disable tracing, respectively.
C-c C-d
C-u C-c C-d
Enable and disable debugging, respectively.
C-c C-z
C-u C-c C-z
Enable and disable zipping, respectively.
C-x SPC
C-u C-x SPC
Set and remove a line breakpoint. This uses the advanced debugger features introduced in SICStus 3.8, Advanced Debugging.
C-c C-s
Insert the PredSpec of the current predicate into the code.
C-c C-n
Insert the name of the current predicate into the code. This can be useful when writing recursive predicates or predicates with several clauses. See also the prolog-electric-dot-flag variable below.
C-c C-v a
Convert all variables in a region to anonymous variables. This can also be done using the Prolog/Transform/All variables to '_' menu entry. See also the prolog-electric-underscore-flag Emacs variable.
C-c ?
Help on predicate. This requires the SICStus info files to be installed. If the SICStus info files are installed in a nonstandard way, you may have to change the Emacs variable prolog-info-predicate-index.


Node:Mode Line, Next:, Previous:Usage, Up:Emacs Interface

Mode Line

If working with an application split into several modules, it is often useful to let files begin with a "mode line":

%%% -*- Mode: Prolog; Module: ModuleName; -*-

The Emacs interface will look for the mode line and notify the SICStus Prolog module system that code fragments being incrementally reconsulted or recompiled should be imported into the module ModuleName. If the mode line is missing, the code fragment will be imported into the type-in module. An additional benefit of the mode line is that it tells Emacs that the file contains Prolog code, regardless of the setting of the Emacs variable auto-mode-alist. A mode line can be inserted by choosing Insert/Module modeline in the Prolog menu.


Node:Configuration, Next:, Previous:Mode Line, Up:Emacs Interface

Configuration

The behavior of the Emacs interface can be controlled by a set of user-configurable settings. Some of these can be changed on the fly, while some require Emacs to be restarted. To set a variable on the fly, type M-x set-variable <RET> VariableName <RET> Value <RET>. Note that variable names can be completed by typing a few characters and then pressing <TAB>.

To set a variable so that the setting is used every time Emacs is started, add lines of the following format to ~/.emacs:

(setq VariableName Value)

Note that the Emacs interface is presently not using the Customize functionality to edit the settings.

The available settings are:

prolog-system
The Prolog system to use. Defaults to 'sicstus, which will be assumed for the rest of this chapter. See the on-line documentation for the meaning of other settings. For other settings of prolog-system the variables below named sicstus-something will not be used, in some cases corresponding functionality is available through variables named prolog-something.
sicstus-version
The version of SICStus that is used. Defaults to '(3 . 8). Note that the spaces are significant!
prolog-use-sicstus-sd
Set to t (the default) to enable the source-linked debugging extensions by default. The debugging can be enabled via the Prolog menu even if this variable is nil. Note that the source-linked debugging only works if sicstus-version is set correctly.
pltrace-port-arrow-assoc [Obsolescent]
Only relevant for source-linked debugging, this controls how the various ports of invocation boxes (see Procedure Box) map to arrows that point into the current line of code in source code buffers. Initialized as:
'(("call" . ">>>") ("exit" . "+++") ("ndexit" . "?++")
  ("redo" . "<<<") ("fail" . "---") ("exception" . "==>"))

where ndexit is the nondeterminate variant of the Exit port. Do not rely on this variable. It will change in future releases.

prolog-indent-width
How many positions to indent the body of a clause. Defaults to tab-width, normally 8.
prolog-paren-indent
The number of positions to indent code inside grouping parentheses. Defaults to 4, which gives the following indentation.
p :-
        (   q1
        ;   q2,
            q3
        ).

Note that the spaces between the parentheses and the code are automatically inserted when <TAB> is pressed at those positions.

prolog-align-comments-flag
Set to nil to prevent single %-comments to be automatically aligned. Defaults to t.

Note that comments with one % are indented to comment-column, comments with two % to the code level, and that comments with three % are never changed when indenting.

prolog-indent-mline-comments-flag
Set to nil to prevent indentation of text inside /* ... */ comments. Defaults t.
prolog-object-end-to-0-flag
Set to nil to indent the closing } of an object definition to prolog-indent-width. Defaults to t.
sicstus-keywords
This is a list with keywords that are highlighted in a special color when used as directives (i.e. as :- keyword). Defaults to
'((sicstus
     ("block" "discontiguous" "dynamic" "initialization"
      "meta_predicate" "mode" "module" "multifile" "public" "volatile")))

prolog-electric-newline-flag
Set to nil to prevent Emacs from automatically indenting the next line when pressing <RET>. Defaults to t.
prolog-hungry-delete-key-flag
Set to t to enable deletion of all white space before the cursor when pressing the delete key (unless inside a comment, string, or quoted atom). Defaults to nil.
prolog-electric-dot-flag
Set to t to enable the electric dot function. If enabled, pressing . at the end of a non-empty line inserts a dot and a newline. When pressed at the beginning of a line, a new head of the last predicate is inserted. When pressed at the end of a line with only whitespace, a recursive call to the current predicate is inserted. The function respects the arity of the predicate and inserts parentheses and the correct number of commas for separation of the arguments. Defaults to nil.
prolog-electric-underscore-flag
Set to t to enable the electric underscore function. When enabled, pressing underscore (_) when the cursor is on a variable, replaces the variable with the anynomous variable. Defaults to nil.
prolog-old-sicstus-keys-flag
Set to t to enable the key-bindings of the old Emacs interface. These bindings are not used by default since they violate GNU Emacs recommendations. Defaults to nil.
prolog-use-prolog-tokenizer-flag
Set to nil to use built-in functions of Emacs for parsing the source code when indenting. This is faster than the default but does not handle some of the syntax peculiarities of Prolog. Defaults to t.
prolog-parse-mode
What position the parsing is done from when indenting code. Two possible settings: 'beg-of-line and 'beg-of-clause. The first is faster but may result in erroneous indentation in /* ... */ comments. The default is 'beg-of-line.
prolog-imenu-flag
Set to t to enable a new Predicate menu which contains all predicates of the current file. Choosing an entry in the menu moves the cursor to the start of that predicate. Defaults to nil.
prolog-info-predicate-index
The info node for the SICStus predicate index. This is important if the online help function is to be used (by pressing C-c ?, or choosing the Prolog/Help on predicate menu entry). The default setting is "(sicstus)Predicate Index".
prolog-underscore-wordchar-flag
Set to nil to not make underscore (_) a word-constituent character. Defaults to t.


Node:Tips, Previous:Configuration, Up:Emacs Interface

Tips

Some general tips and tricks for using the SICStus mode and Emacs in general are given here. Some of the methods may not work in all versions of Emacs.


Node:Font-locking, Next:, Previous:Tips, Up:Tips

Font-locking

When editing large files, it might happen that font-locking is not done because the file is too large. Typing M-x lazy-lock-mode results in only the visible parts of the buffer being highlighted, which is much faster, see its Emacs on-line documentation for details.

If the font-locking seems to be incorrect, choose Fontify Buffer from the Prolog menu.


Node:Auto-fill mode, Next:, Previous:Font-locking, Up:Tips

Auto-fill mode

Auto-fill mode is enabled by typing M-x auto-fill-mode. This enables automatic line breaking with some features. For example, the following multiline comment was created by typing M-; followed by the text. The second line was indented and a % was added automatically.

dynamics([]).       % A list of pit furnace
                    % dynamic instances


Node:Speed, Next:, Previous:Auto-fill mode, Up:Tips

Speed

There are several things to do if the speed of the Emacs environment is a problem:


Node:Changing colors, Previous:Speed, Up:Tips

Changing Colors

The prolog mode uses the default Emacs colors for font-locking as far as possible. The only custom settings are in the prolog process buffer. The default settings of the colors may not agree with your preferences, so here is how to change them.

If your emacs support it, use Customize, M-x customize-group <RET> font-lock <RET> will show the Customize settings for font locking and also contains pointers to the Customize group for the font lock (type)faces. The rest of this section outlines the more involved methods needed in older versions of Emacs.

First of all, list all available faces (a face is a combined setting of foreground and background colors, font, boldness, etc.) by typing M-x list-faces-display.

There are several functions that change the appearance of a face, the ones you will most likely need are:

set-face-foreground
set-face-background
set-face-underline-p
make-face-bold
make-face-bold-italic
make-face-italic
make-face-unbold
make-face-unitalic

These can be tested interactively by typing M-x function-name. You will then be asked for the name of the face to change and a value. If the buffers are not updated according to the new settings, then refontify the buffer using the Fontify Buffer menu entry in the Prolog menu.

Colors are specified by a name or by RGB values. Available color names can be listed with M-x list-colors-display.

To store the settings of the faces, a few lines must be added to ~/.emacs. For example:

;; Customize font-lock faces
(add-hook 'font-lock-mode-hook
          '(lambda ()
             (set-face-foreground font-lock-variable-name-face "#00a000")
             (make-face-bold font-lock-keyword-face)
             (set-face-foreground font-lock-reference-face "Blue")
             ))


Node:Prolog Intro, Next:, Previous:Run Intro, Up:Top

The Prolog Language

This chapter provides a brief introduction to the syntax and semantics of a certain subset of logic (definite clauses, also known as Horn clauses), and indicates how this subset forms the basis of Prolog.


Node:Syntax, Next:, Previous:Prolog Intro, Up:Prolog Intro

Syntax, Terminology and Informal Semantics


Node:Terms, Next:, Previous:Syntax, Up:Syntax

Terms

The data objects of the language are called terms. A term is either a constant, a variable or a compound term.


Node:Integers, Next:, Previous:Terms, Up:Terms

Integers

The constants include integers such as

0   1   999   -512

Besides the usual decimal, or base 10, notation, integers may also be written in other base notations. In sicstus mode, any base from 2 to 36 can be specified, while in iso mode bases 2 (binary), 8 (octal), and 16 (hex) can be used. Letters A through Z (upper or lower case) are used for bases greater than 10. E.g.

15   2'1111   8'17  16'f  % sicstus mode
15   0b1111   0o17  0xf   % iso mode

all represent the integer fifteen. Except for the first, decimal, notation, the forms in the first line are only acceptable in sicstus mode, while those in the second line are only valid in iso mode.

There is also a special notation for character constants. E.g.

0'A   0'\x41   0'\101

are all equivalent to 65 (the character code for A). 0' followed by any character except \ (backslash) is thus read as an integer. Unless character escapes have been switched off, if 0' is followed by \, the \ denotes the start of an escape sequence with special meaning (see Escape Sequences).


Node:Floats, Next:, Previous:Integers, Up:Terms

Floats

Constants also include floats such as

1.0   -3.141   4.5E7   -0.12e+8   12.0e-9

Note that there must be a decimal point in floats written with an exponent, and that there must be at least one digit before and after the decimal point.


Node:Atoms, Next:, Previous:Floats, Up:Terms

Atoms

Constants also include atoms such as

a   void   =   :=   'Algol-68'   []

Atoms are definite elementary objects, and correspond to proper nouns in natural language. For reference purposes, here is a list of the possible forms which an atom may take:

  1. Any sequence of alphanumeric characters (including _), starting with a lower case letter.
  2. Any sequence from the following set of characters:
    +-*/\^<>=~:.?@#$&
    This set can in fact be larger; see Token String for a precise definition.
  3. Any sequence of characters delimited by single quotes. Unless character escapes have been switched off, backslashes in the sequence denote escape sequences (see Escape Sequences), and if the single quote character is included in the sequence it must be escaped, e.g. 'can\'t'.
  4. Any of: ! ; [] {}
    Note that the bracket pairs are special: [] and {} are atoms but [, ], {, and } are not. However, when they are used as functors (see below) the form {X} is allowed as an alternative to {}(X). The form [X] is the normal notation for lists, as an alternative to .(X,[]).


Node:Variables, Next:, Previous:Atoms, Up:Terms

Variables

Variables may be written as any sequence of alphanumeric characters (including _) starting with either a capital letter or _; e.g.

X   Value   A   A1   _3   _RESULT

If a variable is only referred to once in a clause, it does not need to be named and may be written as an anonymous variable, indicated by the underline character _. A clause may contain several anonymous variables; they are all read and treated as distinct variables.

A variable should be thought of as standing for some definite but unidentified object. This is analogous to the use of a pronoun in natural language. Note that a variable is not simply a writable storage location as in most programming languages; rather it is a local name for some data object, cf. the variable of pure LISP and identity declarations in Algol68.


Node:Compound Terms, Previous:Variables, Up:Terms

Compound Terms

The structured data objects of the language are the compound terms. A compound term comprises a functor (called the principal functor of the term) and a sequence of one or more terms called arguments. A functor is characterized by its name, which is an atom, and its arity or number of arguments. For example the compound term whose functor is named point of arity 3, with arguments X, Y and Z, is written

point(X, Y, Z)

Note that an atom is considered to be a functor of arity 0.

Functors are generally analogous to common nouns in natural language. One may think of a functor as a record type and the arguments of a compound term as the fields of a record. Compound terms are usefully pictured as trees. For example, the term

s(np(john),vp(v(likes),np(mary)))

would be pictured as the compound term

       s
     /   \
  np       vp
  |       /  \
john     v     np
         |     |
       likes  mary

Sometimes it is convenient to write certain functors as operators--2-ary functors may be declared as infix operators and 1-ary functors as prefix or postfix operators. Thus it is possible to write, e.g.

X+Y     (P;Q)     X<Y      +X     P;

as optional alternatives to

+(X,Y)   ;(P,Q)   <(X,Y)   +(X)   ;(P)

The use of operators is described fully below (see Operators).

Lists form an important class of data structures in Prolog. They are essentially the same as the lists of LISP: a list either is the atom [] representing the empty list, or is a compound term with functor . and two arguments which are respectively the head and tail of the list. Thus a list of the first three natural numbers is the compound term

  .
 / \
1    .
    / \
   2    .
       / \
      3   []

which could be written, using the standard syntax, as

.(1,.(2,.(3,[])))

but which is normally written, in a special list notation, as

[1,2,3]

The special list notation in the case when the tail of a list is a variable is exemplified by

[X|L]     [a,b|L]

representing

   .               .
  / \             / \
X     L         a     .
                     / \
                   b     L

respectively.

Note that this notation does not add any new power to the language; it simply makes it more readable. e.g. the above examples could equally be written

.(X,L)    .(a,.(b,L))

For convenience, a further notational variant is allowed for lists of integers which correspond to character codes or one-char atoms. Lists written in this notation are called strings. E.g.

"SICStus"

which, by default, represents exactly the same list as

[83,73,67,83,116,117,115]

The Prolog flag double_quotes can be used to change the way strings are interpreted. The default value of the flag is codes, which implies the above interpretation. If the flag is set to chars, a string is transformed to a list of one-char atoms. E.g. with this setting the above string represents the list:

['S','I','C','S',t,u,s]

Finally if double_quotes has the value atom, then the string is made equivalent to the atom formed from its characters: the above sample string is then the same as the atom 'SICStus'.

Unless character escapes have been switched off, backslashes in the sequence denote escape sequences (see Escape Sequences). As for quoted atoms, if a double quote character is included in the sequence it must be escaped, e.g. "can\"t".


Node:Programs, Previous:Terms, Up:Syntax

Programs

A fundamental unit of a logic program is the goal or procedure call. E.g.

gives(tom, apple, teacher)   reverse([1,2,3], L)   X<Y

A goal is merely a special kind of term, distinguished only by the context in which it appears in the program. The (principal) functor of a goal identifies what predicate the goal is for. It corresponds roughly to a verb in natural language, or to a procedure name in a conventional programming language.

A logic program consists simply of a sequence of statements called sentences, which are analogous to sentences of natural language. A sentence comprises a head and a body. The head either consists of a single goal or is empty. The body consists of a sequence of zero or more goals (i.e. it too may be empty). If the head is not empty, the sentence is called a clause.

If the body of a clause is empty, the clause is called a unit clause, and is written in the form

P.

where P is the head goal. We interpret this declaratively as

Goals matching P are true.

and procedurally as

Goals matching P are satisfied.

If the body of a clause is non-empty, the clause is called a rule, and is written in the form

P :- Q, R, S.

where P is the head goal and Q, R and S are the goals which make up the body. We can read such a clause either declaratively as

P is true if Q and R and S are true.

or procedurally as

To satisfy goal P, satisfy goals Q, R and S.

A sentence with an empty head is called a directive (see Directives), and is written in the form

:- P, Q.

where P and Q are the goals of the body. Such a query is read declaratively as

Are P and Q true?

and procedurally as

Satisfy goals P and Q.

Sentences generally contain variables. Note that variables in different sentences are completely independent, even if they have the same name--i.e. the lexical scope of a variable is limited to a single sentence. Each distinct variable in a sentence should be interpreted as standing for an arbitrary entity, or value. To illustrate this, here are some examples of sentences containing variables, with possible declarative and procedural readings:

  1. employed(X) :- employs(Y,X).

    "Any X is employed if any Y employs X."

    "To find whether a person X is employed, find whether any Y employs X."

  2. derivative(X,X,1).

    "For any X, the derivative of X with respect to X is 1."

    "The goal of finding a derivative for the expression X with respect to X itself is satisfied by the result 1."

  3. ?- ungulate(X), aquatic(X).

    "Is it true, for any X, that X is an ungulate and X is aquatic?"

    "Find an X which is both an ungulate and aquatic."

In any program, the predicate for a particular (principal) functor is the sequence of clauses in the program whose head goals have that principal functor. For example, the predicate for a 3-ary functor concatenate/3 might well consist of the two clauses

concatenate([], L, L).
concatenate([X|L1], L2, [X|L3]) :- concatenate(L1, L2, L3).

where concatenate(L1,L2,L3) means "the list L1 concatenated with the list L2 is the list L3". Note that for predicates with clauses corresponding to a base case and a recursive case, the preferred style is to write the base case clause first.

In Prolog, several predicates may have the same name but different arities. Therefore, when it is important to specify a predicate unambiguously, the form name/arity is used; e.g. concatenate/3.

Certain predicates are predefined by built-in predicates supplied by the Prolog system. Such predicates are called built-in predicates.

As we have seen, the goals in the body of a sentence are linked by the operator , which can be interpreted as conjunction ("and"). It is sometimes convenient to use an additional operator ;, standing for disjunction ("or"). (The precedence of ; is such that it dominates , but is dominated by :-.) An example is the clause

grandfather(X, Z) :-
        (mother(X, Y); father(X, Y)),
        father(Y, Z).

which can be read as

For any X, Y and Z, X has Z as a grandfather if either the mother of X is Y or the father of X is Y, and the father of Y is Z.

Such uses of disjunction can always be eliminated by defining an extra predicate--for instance the previous example is equivalent to

grandfather(X,Z) :- parent(X,Y), father(Y,Z).

parent(X,Y) :- mother(X,Y).
parent(X,Y) :- father(X,Y).

--and so disjunction will not be mentioned further in the following, more formal, description of the semantics of clauses.

The token |, when used outside a list, is an alias for ;. The aliasing is performed when terms are read in, so that

a :- b | c.

is read as if it were

a :- b ; c.

Note the double use of the . character. On the one hand it is used as a sentence terminator, while on the other it may be used in a string of symbols which make up an atom (e.g. the list functor ./2). The rule used to disambiguate terms is that a . followed by layout-text is regarded as a sentence terminator (see Token String).


Node:Declarative, Next:, Previous:Syntax, Up:Prolog Intro

Declarative Semantics

The semantics of definite clauses should be fairly clear from the informal interpretations already given. However it is useful to have a precise definition. The declarative semantics of definite clauses tells us which goals can be considered true according to a given program, and is defined recursively as follows.

A goal is true if it is the head of some clause instance and each of the goals (if any) in the body of that clause instance is true, where an instance of a clause (or term) is obtained by substituting, for each of zero or more of its variables, a new term for all occurrences of the variable.

For example, if a program contains the preceding procedure for concatenate/3, then the declarative semantics tells us that

?- concatenate([a], [b], [a,b]).

is true, because this goal is the head of a certain instance of the first clause for concatenate/3, namely,

concatenate([a], [b], [a,b]) :- concatenate([], [b], [b]).

and we know that the only goal in the body of this clause instance is true, since it is an instance of the unit clause which is the second clause for concatenate/3.


Node:Procedural, Next:, Previous:Declarative, Up:Prolog Intro

Procedural Semantics

Note that the declarative semantics makes no reference to the sequencing of goals within the body of a clause, nor to the sequencing of clauses within a program. This sequencing information is, however, very relevant for the procedural semantics which Prolog gives to definite clauses. The procedural semantics defines exactly how the Prolog system will execute a goal, and the sequencing information is the means by which the Prolog programmer directs the system to execute the program in a sensible way. The effect of executing a goal is to enumerate, one by one, its true instances. Here then is an informal definition of the procedural semantics. We first illustrate the semantics by the simple query

?- concatenate(X, Y, [a,b]).

We find that it matches the head of the first clause for concatenate/3, with X instantiated to [a|X1]. The new variable X1 is constrained by the new query produced, which contains a single recursive procedure call:

?- concatenate(X1, Y, [b]).

Again this goal matches the first clause, instantiating X1 to [b|X2], and yielding the new query:

?- concatenate(X2, Y, [])

Now the single goal will only match the second clause, instantiating both X2 and Y to []. Since there are no further goals to be executed, we have a solution

X = [a,b]
Y = []

i.e. a true instance of the original goal is

concatenate([a,b], [], [a,b])

If this solution is rejected, backtracking will generate the further solutions

X = [a]
Y = [b]

X = []
Y = [a,b]

in that order, by re-matching, against the second clause for concatenate, goals already solved once using the first clause.

Thus, in the procedural semantics, the set of clauses

H :- B1, ..., Bm.
H' :- B1', ..., Bm'.
...

are regarded as a procedure definition for some predicate H, and in a query

?- G1, ..., Gn.

each Gi is regarded as a procedure call. To execute a query, the system selects by its computation rule a goal, Gj say, and searches by its search rule a clause whose head matches Gj. Matching is done by the unification algorithm (see [Robinson 65] which computes the most general unifier, mgu, of Gj and H). The mgu is unique if it exists. If a match is found, the current query is reduced to a new query

?- (G1, ..., Gj-1, B1, ..., Bm, Gj+1, ..., Gn)mgu.

and a new cycle is started. The execution terminates when the empty query has been produced.

If there is no matching head for a goal, the execution backtracks to the most recent successful match in an attempt to find an alternative match. If such a match is found, an alternative new query is produced, and a new cycle is started.

In SICStus Prolog, as in other Prolog systems, the search rule is simple: "search forward from the beginning of the program".

The computation rule in traditional Prolog systems is also simple: "pick the leftmost goal of the current query". However, SICStus Prolog and other modern implementations have a somewhat more complex computation rule "pick the leftmost unblocked goal of the current query".

A goal can be blocked on one ore more uninstantiated variables, and a variable may block several goals. Thus binding a variable can cause blocked goals to become unblocked, and backtracking can cause currently unblocked goals to become blocked again. Moreover, if the current query is

?- G1, ..., Gj-1, Gj, Gj+1, ..., Gn.

where Gj is the first unblocked goal, and matching Gj against a clause head causes several blocked goals in G1, ..., Gj-1 to become unblocked, then these goals may become reordered. The internal order of any two goals that were blocked on the same variable is retained, however.

Another consequence is that a query may be derived consisting entirely of blocked goals. Such a query is said to have floundered. The top-level checks for this condition. If detected, the outstanding blocked subgoals are printed on the standard error stream along with the answer substitution, to notify the user that the answer (s)he has got is really a speculative one, since it is only valid if the blocked goals can be satisfied.

A goal is blocked if certain arguments are uninstantiated and its predicate definition is annotated with a matching block declaration (see Block Declarations). Goals of certain built-in may also be blocked if their arguments are not sufficiently instantiated.

When this mechanism is used, the control structure resembles that of coroutines, suspending and resuming different threads of control. When a computation has left blocked goals behind, the situation is analogous to spawning a new suspended thread. When a blocked goal becomes unblocked, the situation is analogous to temporarily suspending the current thread and resuming the thread to which the blocked goal belongs.


Node:Occur, Next:, Previous:Procedural, Up:Prolog Intro

Occurs-Check

It is possible, and sometimes useful, to write programs which unify a variable to a term in which that variable occurs, thus creating a cyclic term. The usual mathematical theory behind Logic Programming forbids the creation of cyclic terms, dictating that an occurs-check should be done each time a variable is unified with a term. Unfortunately, an occurs-check would be so expensive as to render Prolog impractical as a programming language. Thus cyclic terms may be created and may cause loops trying to print them.

SICStus Prolog mitigates the problem by its ability to unify, compare (see Term Compare), assert, and copy cyclic terms without looping. The write_term/[2,3] built-in predicate can optionally handle cyclic terms; see Term I/O. Unification with occurs-check is available as a built-in predicate; see Misc Pred. Predicates testing (a)cyclicity are available in a library package; see Term Utilities. Other predicates usually do not handle cyclic terms well.


Node:Cut, Next:, Previous:Occur, Up:Prolog Intro

The Cut Symbol

Besides the sequencing of goals and clauses, Prolog provides one other very important facility for specifying control information. This is the cut symbol, written !. It is inserted in the program just like a goal, but is not to be regarded as part of the logic of the program and should be ignored as far as the declarative semantics is concerned.

The effect of the cut symbol is as follows. When first encountered as a goal, cut succeeds immediately. If backtracking should later return to the cut, the effect is to fail the parent goal, i.e. that goal which matched the head of the clause containing the cut, and caused the clause to be activated. In other words, the cut operation commits the system to all choices made since the parent goal was invoked, and causes other alternatives to be discarded. The goals thus rendered determinate are the parent goal itself, any goals occurring before the cut in the clause containing the cut, and any subgoals which were executed during the execution of those preceding goals.

For example:

member(X, [X|_]).
member(X, [_|L]) :- member(X, L).

This predicate can be used to test whether a given term is in a list. E.g.

| ?- member(b, [a,b,c]).

returns the answer yes. The predicate can also be used to extract elements from a list, as in

| ?- member(X, [d,e,f]).

With backtracking this will successively return each element of the list. Now suppose that the first clause had been written instead:

member(X, [X|_]) :- !.

In this case, the above call would extract only the first element of the list (d). On backtracking, the cut would immediately fail the whole predicate.

x :- p, !, q.
x :- r.

This is equivalent to

x := if p then q else r;

in an Algol-like language.

It should be noticed that a cut discards all the alternatives since the parent goal, even when the cut appears within a disjunction. This means that the normal method for eliminating a disjunction by defining an extra predicate cannot be applied to a disjunction containing a cut.

A proper use of the cut is usually a major difficulty for new Prolog programmers. The usual mistakes are to over-use cut, and to let cuts destroy the logic. A cut that doesn't destroy the logic is called a green cut; a cut that does is called a red cut. We would like to advise all users to follow these general rules. Also see Writing Efficient Programs.


Node:Operators, Next:, Previous:Cut, Up:Prolog Intro

Operators

Operators in Prolog are simply a notational convenience. For example, the expression 2+1 could also be written +(2,1). This expression represents the compound term

   +
 /   \
2     1

and not the number 3. The addition would only be performed if the term were passed as an argument to an appropriate predicate such as is/2 (see Arithmetic).

The Prolog syntax caters for operators of three main kinds--infix, prefix and postfix. An infix operator appears between its two arguments, while a prefix operator precedes its single argument and a postfix operator is written after its single argument.

Each operator has a precedence, which is a number from 1 to 1200. The precedence is used to disambiguate expressions where the structure of the term denoted is not made explicit through the use of parentheses. The general rule is that it is the operator with the highest precedence that is the principal functor. Thus if + has a higher precedence than /, then

a+b/c     a+(b/c)

are equivalent and denote the term +(a,/(b,c)). Note that the infix form of the term /(+(a,b),c) must be written with explicit parentheses, i.e.

(a+b)/c

If there are two operators in the subexpression having the same highest precedence, the ambiguity must be resolved from the types of the operators. The possible types for an infix operator are

xfx     xfy     yfx

Operators of type xfx are not associative: it is a requirement that both of the two subexpressions which are the arguments of the operator must be of lower precedence than the operator itself, i.e. their principal functors must be of lower precedence, unless the subexpression is explicitly parenthesized (which gives it zero precedence).

Operators of type xfy are right-associative: only the first (left-hand) subexpression must be of lower precedence; the right-hand subexpression can be of the same precedence as the main operator. Left-associative operators (type yfx) are the other way around.

A functor named name is declared as an operator of type type and precedence precedence by the directive:

:- op(precedence, type, name).

The argument name can also be a list of names of operators of the same type and precedence.

It is possible to have more than one operator of the same name, so long as they are of different kinds, i.e. infix, prefix or postfix. Note that the ISO Prolog standard contains a limitation that there should be no infix and postfix operators with the same name, however, SICStus Prolog lifts this restriction.

An operator of any kind may be redefined by a new declaration of the same kind. This applies equally to operators which are provided as standard, except for the ',' operator. Declarations of all the standard operators can be found elsewhere (see Standard Operators).

For example, the standard operators + and - are declared by

:- op(500, yfx, [ +, - ]).

so that

a-b+c

is valid syntax, and means

(a-b)+c

i.e.

     +
   /   \
  -     c
 / \
a   b

The list functor ./2 is not a standard operator, but if we declare it thus:

:- op(900, xfy, .).

then a.b.c would represent the compound term

  .
 / \
a   .
   / \
  b   c

Contrasting this with the diagram above for a-b+c shows the difference between yfx operators where the tree grows to the left, and xfy operators where it grows to the right. The tree cannot grow at all for xfx operators; it is simply illegal to combine xfx operators having equal precedences in this way.

The possible types for a prefix operator are

fx      fy

and for a postfix operator they are

xf      yf

The meaning of the types should be clear by analogy with those for infix operators. As an example, if not were declared as a prefix operator of type fy, then

not not P

would be a permissible way to write not(not(P)). If the type were fx, the preceding expression would not be legal, although

not P

would still be a permissible form for not(P).

If these precedence and associativity rules seem rather complex, remember that you can always use parentheses when in any doubt.

Note that the arguments of a compound term written in standard syntax must be expressions of precedence below 1000. Thus it is necessary to parenthesize the expression P :- Q in

| ?- assert((P :- Q)).


Node:Restrictions, Next:, Previous:Operators, Up:Prolog Intro

Syntax Restrictions

Note carefully the following syntax restrictions, which serve to remove potential ambiguity associated with prefix operators.

  1. In a term written in standard syntax, the principal functor and its following ( must not be separated by any intervening layout-text. Thus
    point (X,Y,Z)
    

    is invalid syntax.

  2. If the argument of a prefix operator starts with a (, this ( must be separated from the operator by at least one layout-char. Thus
    :-(p;q),r.
    

    (where :- is the prefix operator) is invalid syntax. The system would try to interpret it as the compound term:

        ,
       / \
     :-    r
      |
      ;
     / \
    p   q
    

    That is, it would take :- to be a functor of arity 1. However, since the arguments of a compound term are required to be expressions of precedence below 1000, this interpretation would fail as soon as the ; (precedence 1100) was encountered.

    In contrast, the term:

    :- (p;q),r.
    

    is valid syntax and represents the following compound term:

       :-
        |
        ,
       / \
      ;   r
     / \
    p   q
    


Node:Comments, Previous:Restrictions, Up:Prolog Intro

Comments

Comments have no effect on the execution of a program, but they are very useful for making programs more readily comprehensible. Two forms of comment are allowed in Prolog:

  1. The character % followed by any sequence of characters up to end of line.
  2. The symbol /* followed by any sequence of characters (including new lines) up to */.


Node:Module Intro, Next:, Previous:Prolog Intro, Up:Top

The Module System

By making use of the module systems facilities, programs can be divided into different modules. Each module has its own independent predicate name space. This is an important feature for the development of larger programs. The module system of SICStus Prolog is procedure based. This means that only the predicates are local to a module, whereas terms are global. The module system is flat, not hierarchical, so all modules are visible to one another. It is non-strict, i.e. the normal visibility rules can be overridden by special syntax. No overhead is incurred on compiled calls to predicates in other modules. It is modeled after and compatible with the Quintus Prolog module system. Finally, using the module system is optional, and SICStus Prolog may be used without the user being aware of the module system at all.

Modules in SICStus Prolog can also be used for object-oriented programming. See Obj Intro, for details.


Node:Basic Concepts, Next:, Previous:Module Intro, Up:Module Intro

Basic Concepts

Each predicate in the Prolog system, whether built-in or user defined, belongs to a module. A predicate is generally only visible in the module where it is defined. However a predicate may be imported by another module. It is thereby made visible in that module too. Built-in predicates are visible in every module. Predicates declared as public in a module declaration (see below) are exported. Normally only public predicates may be imported by another module.

For any given goal, the source module is the module in which the corresponding predicate must be visible. Similarly, for any given clause, the source module of its head is the module into which the clause is loaded.

For goals occurring in a source file with a module declaration, the source module is the declared module. For goals occurring in a source file without a module declaration, the source module is the module that the file is being loaded into. For goals typed at the top-level, the source module is the type-in module. The type-in module is by default the user module but may be changed by the built-in predicate module/1.

The other predefined module is the prolog module where all the built-in predicates reside. The exported built-in predicates are automatically imported into each new module as it is created.


Node:Module Spec, Next:, Previous:Basic Concepts, Up:Module Intro

Module Prefixing

Notwithstanding the visibility rules, any predicate can be called from any other module by prefixing the goal with the module name and the colon operator, thus overriding the source module of the goal:

| ?- foo:bar(X).

This feature is intended mainly for debugging purposes, since it defies the purposes of the module system. If the prefixed goal is a meta-predicate, however, the prefixed module name may affect the module name expansion of the goal (see Meta Exp). If multiple module prefixes are used, the innermost one has priority.

It is also possible to override the source module of clauses and directives by module prefixing. For example,

:- dynamic mod:p/1.
p(X) :- mod:(q(X), r(X)).
mod:(q(X) :- r(X)).
mod:s(X) :- t(X).

declares mod:p/1 as dynamic, whatever the source module is; defines p/1 in the source module as calling mod:q/1 and mod:r/1; defines mod:q/1 as calling mod:r/1; and defines mod:s/1 as calling t/1 in the source module. The latter technique is particularly useful when the prefix is user and the predicate is a hook predicate such as user:portray/1 which must be defined in the user module, but the rest of the file consists of predicates belonging to some other module.


Node:Def Modules, Next:, Previous:Module Spec, Up:Module Intro

Defining Modules

A module is normally defined by putting a module declaration in a source file. A module declaration has the form:

:- module(ModuleName, ExportList[, Options]).

where ModuleName is an atom, and should precede all other clauses and directives of that file.

When the file is loaded, all predicates in the file go into ModuleName and the predicates of the ExportList are exported. When a module declaration is processed, all existing predicates in the module are erased before the new ones are loaded. A file which contains a module declaration is henceforth called a module-file.

Options is an optional argument, and should be a list. The only available option is hidden(Boolean), where Boolean is false (the default) or true. In the latter case, tracing of the predicates of the module is disabled (although spypoints can be set), and no source information is generated at compile time.

A module can also be defined dynamically by asserting or loading predicates to it:

| ?- assert(m:p(x)).

creates the module m, if it does not already exists, and asserts p(x) to it.

| ?- compile(m:f).

creates the module m and loads f into m.

Dynamically created modules have no public predicates.


Node:Importation, Next:, Previous:Def Modules, Up:Module Intro

Importation

When a module-file is loaded by load_files/[1,2] or one of its shorthands (see Read In), by default all the public predicates of the module-file are imported by the receiving module. An explicit list of predicates to import may also be specified.

Clashes with already existing predicates, local or imported from other modules, are handled in two different ways: If the receiving module is the user module, the user is asked for redefinition of the predicate. For other receiving modules, a warning is issued and the importation is canceled. In the first case redefinition silently takes place if the flag redefine_warnings has the value off (see prolog_flag/3). The binding of an imported predicate remains, even if the origin is reloaded or deleted. However, abolish/[1,2] break up the importation binding. When a module-file is reloaded, a check is made that the predicates imported by other modules are still in the public list. If that is not the case, a warning is issued. Note that an imported predicate may be re-exported.


Node:Meta Exp, Next:, Previous:Importation, Up:Module Intro

Module Name Expansion

Some predicates take goals as arguments (i.e. meta-predicates). These arguments must include a module specification stating which module the goal refers. Some other predicates also need module information i.e. compile/1. The property of needing module information is declared with a meta-predicate declaration (see Meta Decl). Goals for these predicates are module name expanded to ensure the module information. Goals appearing in queries and meta-calls are expanded prior to execution while goals in the bodies of clauses and directives are expanded at compile time. The expansion is made by preceding the relevant argument with Module:. If the goal is prefixed by Module:, Module is used for the expansion; otherwise, the source/type-in module is used. An argument is not expanded if:

Some examples:

| ?- [user].
| :- meta_predicate p(:), q(:).
| r(X) :- p(X).
| q(X) :- p(X).
| ^D
% consulted user in module user, 40 msec 1088 bytes

yes
| ?- listing.

r(A) :-
        p(user:A).

q(A) :-
        p(A).

yes

Here, p/1 and q/1 are declared as meta-predicates while r/1 is not. Thus the clause r(X) :- p(X) will be transformed to r(X) :- p(M:X), by item 2 above, where M is the type-in module, whereas q(X) :- p(X) will not.

| ?- m:assert(f(1)).

Here, assert/1 is called in the module m. However, this does not ensure that f(1) is asserted into m. The fact that assert/1 is a meta-predicate makes the system module name expand the goal, transforming it to m:assert(m:f(1)) before execution. This way, assert/1 is supplied the correct module information.


Node:Meta Decl, Previous:Meta Exp, Up:Module Intro

Meta-Predicate Declarations

The fact that a predicate needs module name expansion is declared in a meta-predicate declaration:

:- meta_predicate MetaPredSpec, ..., MetaPredSpec.

where each MetaPredSpec is a mode spec. E.g.

:- meta_predicate p(:, +).

which means that the first argument of p/2 shall be module name expanded. The arguments in the mode spec are interpreted as:

:
An integer
This argument, in any call to the declared predicate, shall be expanded. (Integers are allowed for compatibility reasons).
Anything else e.g. +, - or ?
This argument shall not be expanded

A number of built-in predicates have predefined meta-predicate declarations, as indicated by the mode specs in this manual, e.g. call(:Term).


Node:Load Intro, Next:, Previous:Module Intro, Up:Top

Loading Programs

Programs can be loaded in three different ways: consulted or compiled from source file, or loaded from object files. The latter is the fastest way of loading programs, but of course requires that the programs have been compiled to object files first. Object files may be handy when developing large applications consisting of many source files, but are not strictly necessary since it is possible to save and restore entire execution states (see Misc Pred).

Consulted, or interpreted, predicates are equivalent to, but slower than, compiled ones. Although they use different representations, the two types of predicates can call each other freely.

The SICStus Prolog compiler produces compact and efficient code, running about 8 times faster than consulted code, and requiring much less runtime storage. Compiled Prolog programs are comparable in efficiency with LISP programs for the same task. However, against this, compilation itself takes about twice as long as consulting, and tracing of goals that compile in-line are not available in compiled code.

The compiler operates in four different modes, controlled by the "Compilation mode" flag (see prolog_flag/3). The possible states of the flag are:

compactcode
Compilation produces byte-coded abstract instructions. This is the default unless SICStus Prolog has been installed with support for fastcode compilation.
fastcode
Compilation produces native machine instructions. Currently only available for Sparc platforms. Fastcode runs about 3 times faster than compactcode. This is the default if SICStus Prolog has been installed with support for fastcode compilation.
profiledcode
Compilation produces byte-coded abstract instructions instrumented to produce execution profiling data. See Profiling. Profiling is not available in runtime systems.
debugcode
Compilation produces interpreted code, i.e. compiling is replaced by consulting.

The compilation mode can be changed by issuing the query:

| ?- prolog_flag(compiling, OldValue, NewValue).

A Prolog program consists of a sequence of sentences (see Sentence). Directives encountered among the sentences are executed immediately as they are encountered, unless they can be interpreted as declarations (see Declarations), which affect the treatment of forthcoming clauses, or as initializations, which build up a set of goals to be executed after the program has been loaded. Clauses are loaded as they are encountered.

A Prolog program may also contain a list of sentences (including the empty list). This is treated as equivalent to those sentences occurring in place of the list. This feature makes it possible to have user:term_expansion/[2,4] (see Definite) "return" a list of sentences, instead of a single sentence.


Node:Load Predicates, Next:, Previous:Load Intro, Up:Load Intro

Predicates which Load Code

This section contains a summary of the relevant predicates. For a more precise description, see Read In.

To consult a program, issue the query:

| ?- consult(Files).

where Files is either a filename or a list of filenames, instructs the processor to read in the program which is in the files. For example:

| ?- consult([dbase,'extras.pl',user]).

When a directive is read it is immediately executed. Any predicate defined in the files erases any clauses for that predicate already present. If the old clauses were loaded from a different file than the present one, the user will be queried first whether (s)he really wants the new definition. However, if a multifile declaration (see Declarations) is read and the corresponding predicate exists and has previously been declared as multifile, new clauses will be added to the predicate, rather than replacing the old clauses. If clauses for some predicate appear in more than one file, the later set will effectively overwrite the earlier set. The division of the program into separate files does not imply any module structure--any predicate can call any other (see Module Intro).

consult/1, used in conjunction with save_program/[1,2] and restore/1, makes it possible to amend a program without having to restart from scratch and consult all the files which make up the program. The consulted file is normally a temporary "patch" file containing only the amended predicate(s). Note that it is possible to call consult(user) and then enter a patch directly on the terminal (ending with ^D). This is only recommended for small, tentative patches.

| ?- [File|Files].

This is a shorthand way of consulting a list of files. (The case where there is just one filename in the list was described earlier (see Reading In).

To compile a program in-core, use the built-in predicate:

| ?- compile(Files).

where Files is specified just as for consult/1.

The effect of compile/1 is very much like that of consult/1, except all new procedures will be stored in compiled rather than consulted form. However, predicates declared as dynamic (see below) will be stored in consulted form, even though compile/1 is used.

Programs can be compiled into an intermediate representation known as .ql (for Quick Load file). As of SICStus Prolog 3.8, this feature is obsolescent with the introduction of partial saved states (.po files; see Saving), which can be handled much more efficiently.

To compile a program into a .ql file, use the built-in predicate:

| ?- fcompile(Files).

where Files is specified just as for consult/1. For each filename in the list, the compiler will append the suffix .pl to it and try to locate a source file with that name and compile it to a .ql file. The filename is formed by appending the suffix .ql to the specified name. The internal state of SICStus Prolog is not changed as result of the compilation. See Considerations.

To load a program from a set of source or object files, use the built-in predicates load_files/[1,2] (the latter is controlled by an options list):

| ?- load_files(Files).

where Files is either a single filename or a list of filenames, optionally with .pl or .po or .ql extensions. This predicate takes the following action for each File in the list of filenames:

  1. If the File is user, compile(user) or [user] is performed;
  2. If File cannot be found, not even with an extension, an existence error is signaled;
  3. If an .po file is found, the file is loaded;
  4. If an .ql file is found, the file is loaded;
  5. If a source file is found, the file is compiled or consulted.
  6. If more than one file is found for File, item 3 or 4 or 5 applies depending on which file was modified most recently.
  7. If File cannot be found, not even with an extension, an existence error is signaled.
  8. Source files are compiled, unless load_files/1 was called from a directive of a file being consulted.

Finally, to ensure that some files have been loaded, use the built-in predicate:

| ?- ensure_loaded(Files).

Same as load_files(Files), except if the file to be loaded has already been loaded and has not been modified since that time, in which case the file is not loaded again. If a source file has been modified, ensure_loaded/1 does not cause any object file to become recompiled.


Node:Declarations, Next:, Previous:Load Predicates, Up:Load Intro

Declarations

When a program is to be loaded, it is sometimes necessary to tell the system to treat some of the predicates specially. This information is supplied by including declarations about such predicates in the source file, preceding any clauses for the predicates which they concern. A declaration is written just as a directive, beginning with :-. A declaration is effective from its occurrence through the end of file.

Although declarations that affect more than one predicate may be collapsed into a single declaration, the recommended style is to write the declarations for a predicate immediately before its first clause.

Operator declarations are not declarations proper, but rather directives that modify the global table of syntax operators. Operator declarations are executed as they are encountered while loading programs.

The rest of this section details the available forms of predicate declarations.


Node:Multifile Declarations, Next:, Previous:Declarations, Up:Declarations

Multifile Declarations

A declaration

:- multifile PredSpec, ..., PredSpec.  [ISO]

where each PredSpec is a predicate spec, causes the specified predicates to become multifile. This means that if more clauses are subsequently loaded from other files for the same predicate, then the new clauses will not replace the old ones, but will be added at the end instead. As of release 3, multifile declarations are required in all files from where clauses to a multifile predicate are loaded.

An example when multifile declarations are particularly useful is in defining hook predicates. A hook predicate is a user-defined predicate that somehow alters or customizes the behavior of SICStus Prolog. A number of such hook predicates are described in this manual. Often, an application needs to combine the functionality of several software modules, some of which define clauses for such hook predicates. By simply declaring every hook predicates as multifile, the functionality of the clauses for the hook predicates is automatically combined. If this is not done, the last software module to define clauses for a particular hook predicate will effectively supersede any clauses defined for the same hook predicate in a previous module. By default, hook predicates must be defined in the user module, and only their first solution is relevant.

If a file containing clauses for a multifile predicate is reloaded, the old clauses from the same file are removed. The new clauses are added at the end.

If a multifile predicate is loaded from a file with no multifile declaration for it, the predicate is redefined as if it were an ordinary predicate (i.e. the user is asked for confirmation).

Clauses of multifile predicates are (currently) always loaded in interpreted form, even if they were processed by the compiler. If performance is an issue, define the multifile predicates as unit clauses or as clauses with a single goal that just calls an auxiliary compiled predicate to perform any time-critical computation.

If a multifile predicate is declared dynamic in one file, it must also be done so in the other files from where it is loaded. Hook predicates should always be declared as multifile and dynamic, as this is the convention followed in the library modules.

Multifile declarations must precede any other declarations for the same predicate(s)!


Node:Dynamic Declarations, Next:, Previous:Multifile Declarations, Up:Declarations

Dynamic Declarations

A declaration

:- dynamic PredSpec, ..., PredSpec.  [ISO]

where each PredSpec is a predicate spec, causes the specified predicates to become dynamic, which means that other predicates may inspect and modify them, adding or deleting individual clauses. Dynamic predicates are always stored in consulted form even if a compilation is in progress. This declaration is meaningful even if the file contains no clauses for a specified predicate--the effect is then to define a dynamic predicate with no clauses.


Node:Volatile Declarations, Next:, Previous:Dynamic Declarations, Up:Declarations

Volatile Declarations

A declaration

:- volatile PredSpec, ..., PredSpec.

where each PredSpec is a predicate spec, causes the specified predicates to become volatile.

A predicate should be declared as volatile if it refers to data that cannot or should not be saved in a saved state. In most cases a volatile predicate will be dynamic, and it will be used to keep facts about streams or memory references. When a program state is saved at run-time, the clauses of all volatile predicates will be left unsaved. The predicate definitions will be saved though, which means that the predicates will keep all properties, that is volatile and maybe dynamic or multifile, when the saved state is restored.


Node:Discontiguous Declarations, Next:, Previous:Volatile Declarations, Up:Declarations

Discontiguous Declarations

A declaration

:- discontiguous PredSpec, ..., PredSpec.  [ISO]

where each PredSpec is a predicate spec, disables warnings about clauses not being together for the specified predicates. By default, such warnings are issued in development systems unless disabled selectively for specific predicates, or globally by setting the discontiguous_warnings flag to off.


Node:Block Declarations, Next:, Previous:Discontiguous Declarations, Up:Declarations

Block Declarations

The declaration

:- block BlockSpec, ..., BlockSpec.

where each BlockSpec is a mode spec, specifies conditions for blocking goals of the predicate referred to by the mode spec (f/3 say). When a goal for f/3 is to be executed, the mode specs are interpreted as conditions for blocking the goal, and if at least one condition evaluates to true, the goal is blocked.

A block condition evaluates to true iff all arguments specified as - are uninstantiated, in which case the goal is blocked until at least one of those variables is instantiated. If several conditions evaluate to true, the implementation picks one of them and blocks the goal accordingly.

The recommended style is to write the block declarations in front of the source code of the predicate they refer to. Indeed, they are part of the source code of the predicate, and must precede the first clause. For example, with the definition:

:- block merge(-,?,-), merge(?,-,-).

merge([], Y, Y).
merge(X, [], X).
merge([H|X], [E|Y], [H|Z]) :- H @< E,  merge(X, [E|Y], Z).
merge([H|X], [E|Y], [E|Z]) :- H @>= E, merge([H|X], Y, Z).

calls to merge/3 having uninstantiated arguments in the first and third position or in the second and third position will suspend.

The behavior of blocking goals for a given predicate on uninstantiated arguments cannot be switched off, except by abolishing or redefining the predicate.

Block declarations generalize the "wait declarations" of earlier versions of SICStus Prolog. A declaration :- wait f/3 in the old syntax corresponds to :- block f(-,?,?) in the current syntax. See Use Of Term Exp, for a simple way to extend the system to accept the old syntax.


Node:Meta-Predicate Declarations, Next:, Previous:Block Declarations, Up:Declarations

Meta-Predicate Declarations

A declaration

:- meta_predicate MetaPredSpec, ..., MetaPredSpec.

where each MetaPredSpec is a mode spec, informs the compiler that certain arguments of the declared predicates are used for passing goals. To ensure the correct semantics in the context of multiple modules, clauses or directives containing goals for the declared predicates may need to have those arguments module name expanded. See Meta Exp, for details.


Node:Module Declarations, Next:, Previous:Meta-Predicate Declarations, Up:Declarations

Module Declarations

A declaration

:- module(ModuleName, ExportList[, Options]).

where ExportList is a list of predicate specs, declares that the forthcoming predicates should go into the module named ModuleName and that the predicates listed should be exported. See Def Modules, for details.


Node:Public Declarations, Next:, Previous:Module Declarations, Up:Declarations

Public Declarations

The only effect of a declaration

:- public PredSpec, ..., PredSpec.

where each PredSpec is a predicate spec, is to give the SICStus cross-referencer (see The Cross-Referencer) a starting point for tracing reachable code. In some Prologs, this declaration is necessary for making compiled predicates visible. In SICStus Prolog, predicate visibility is handled by the module system. See Module Intro.


Node:Mode Declarations, Next:, Previous:Public Declarations, Up:Declarations

Mode Declarations

A declaration

:- mode ModeSpec, ..., ModeSpec.

where each ModeSpec is a mode spec, has no effect whatsoever, but is accepted for compatibility reasons. In some Prologs, this declaration helps reduce the size of the compiled code for a predicate, and may speed up its execution. Unfortunately, writing mode declarations can be error-prone, and since errors in mode declaration do not show up while running the predicates interpretively, new bugs may show up when predicates are compiled. However, mode declarations may be used as a commenting device, as they express the programmer's intention of data flow in predicates.


Node:Include Declarations, Previous:Mode Declarations, Up:Declarations

Include Declarations

A declaration

:- include(Files).  [ISO]

where Files is a file name or a list of file names, instructs the processor to literally embed the Prolog clauses and directives in Files into the file being loaded. This means that the effect of the include directive is such as if the include directive itself was replaced by the text in the Files. Including some files is thus different from loading them in several respects:

SICStus Prolog uses the included file name (as opposed to the embedding file name) only in source level debugging and error reporting. Note that source level debugging information is not kept for included files which are compiled to .ql format; in such cases the debugger will show the include directive itself as the source information.


Node:Initializations, Next:, Previous:Declarations, Up:Load Intro

Initializations

A directive

:- initialization :Goal.  [ISO]

in a file includes Goal to the set of goals which shall be executed after that file has been loaded.

initialization/1 is actually callable at any point during loading of a file. Initializations are saved by save_modules/2 and save_program/[1,2], and so are executed after loading or restoring such files too.

Goal is associated with the file loaded, and with a module, if applicable. When a file, or module, is going to be reloaded, all goals earlier installed by that file, or in that module, are removed first.


Node:Considerations, Previous:Initializations, Up:Load Intro

Considerations for File-To-File Compilation

When compiling a source file to a .ql file, remember that clauses are loaded and directives are executed at run time, not at compile time. Only predicate declarations are processed at compile time. For instance, it does not work to include operator declarations or clauses of user:term_expansion/[2,4] or user:goal_expansion/3 or any auxiliary predicates that they might need, and rely on the new transformations to be effective for subsequent clauses of the same file or subsequent files of the same compilation.

Any directives or clauses that affect the compile-time environment must be loaded prior to compiling source files to .ql files. This also holds for meta-predicates called by the source files but defined elsewhere, for module name expansion to work correctly. If this separation into files is unnatural or inconvenient, one can easily ensure that the compile-time environment is up to date by doing:

| ?- ensure_loaded(Files), fcompile(Files).

Since module name expansion takes place at compile time, the module into which the file is to be loaded must be known when compiling to .ql files. This is no problem for module-files because the module name is picked from the module declaration. When non-module-files are compiled, the file name may be prefixed with the module name that is to be used for expansion:

| ?- fcompile(Module:Files).

If an .ql file is loaded into a different module from which it was compiled for, a warning is issued.


Node:Debug Intro, Next:, Previous:Load Intro, Up:Top

Debugging

This chapter describes the debugging facilities that are available in development systems. The purpose of these facilities is to provide information concerning the control flow of your program.

The main features of the debugging package are as follows:

The Procedure Box model of execution is also called the Byrd Box model after its inventor, Lawrence Byrd.

Much of the information in this chapter is also in Chapter eight of [Clocksin & Mellish 81] which is recommended as an introduction.

Unless otherwise stated, the debugger prints goals using write_term/3 with the value of the Prolog flag debugger_print_options (see State Info).

The debugger is not available in runtime systems and the predicates defined in this chapter are undefined; see Runtime Systems.


Node:Procedure Box, Next:, Previous:Debug Intro, Up:Debug Intro

The Procedure Box Control Flow Model

During debugging, the debugger prints out a sequence of goals in various states of instantiation in order to show the state the program has reached in its execution. However, in order to understand what is occurring it is necessary to understand when and why the debugger prints out goals. As in other programming languages, key points of interest are predicate entry and return, but in Prolog there is the additional complexity of backtracking. One of the major confusions that novice Prolog programmers have to face is the question of what actually happens when a goal fails and the system suddenly starts backtracking. The Procedure Box model of Prolog execution views program control flow in terms of movement about the program text. This model provides a basis for the debugging mechanism in development systems, and enables the user to view the behavior of the program in a consistent way.

Let us look at an example Prolog predicate :

           *--------------------------------------*
   Call    |                                      |    Exit
---------> +  descendant(X,Y) :- offspring(X,Y).  + --------->
           |                                      |
           |  descendant(X,Z) :-                  |
<--------- +     offspring(X,Y), descendant(Y,Z). + <---------
   Fail    |                                      |    Redo
           *-------------------+------------------*
                               |
<------------------------------+
   Exception

The first clause states that Y is a descendant of X if Y is an offspring of X, and the second clause states that Z is a descendant of X if Y is an offspring of X and if Z is a descendant of Y. In the diagram a box has been drawn around the whole predicate and labeled arrows indicate the control flow in and out of this box. There are five such arrows which we shall look at in turn.

Call
This arrow represents initial invocation of the predicate. When a goal of the form descendant(X,Y) is required to be satisfied, control passes through the Call port of the descendant box with the intention of matching a component clause and then satisfying the subgoals in the body of that clause. Note that this is independent of whether such a match is possible; i.e. first the box is called, and then the attempt to match takes place. Textually we can imagine moving to the code for descendant when meeting a call to descendant in some other part of the code.
Exit
This arrow represents a successful return from the predicate. This occurs when the initial goal has been unified with one of the component clauses and the subgoals have been satisfied. Control now passes out of the Exit port of the descendant box. Textually we stop following the code for descendant and go back to the place we came from.
Redo
This arrow indicates that a subsequent goal has failed and that the system is backtracking in an attempt to find alternatives to previous solutions. Control passes through the Redo port of the descendant box. An attempt will now be made to resatisfy one of the component subgoals in the body of the clause that last succeeded; or, if that fails, to completely rematch the original goal with an alternative clause and then try to satisfy any subgoals in the body of this new clause. Textually we follow the code backwards up the way we came looking for new ways of succeeding, possibly dropping down on to another clause and following that if necessary.
Fail
This arrow represents a failure of the initial goal, which might occur if no clause is matched, or if subgoals are never satisfied, or if any solution produced is always rejected by later processing. Control now passes out of the Fail port of the descendant box and the system continues to backtrack. Textually we move back to the code which called this predicate and keep moving backwards up the code looking for choicepoints.
Exception
This arrow represents an exception which was raised in the initial goal, either by a call to throw/1 or raise_exception/1 or by an error in a built-in predicate. See Exception. Control now passes out of the Exception port of the descendant box and the system continues to pass the exception to outer levels. Textually we move back to the code which called this predicate and keep moving backwards up the code looking for a call to catch/3 or on_exception/3.

In terms of this model, the information we get about the procedure box is only the control flow through these five ports. This means that at this level we are not concerned with which clause matches, and how any subgoals are satisfied, but rather we only wish to know the initial goal and the final outcome. However, it can be seen that whenever we are trying to satisfy subgoals, what we are actually doing is passing through the ports of their respective boxes. If we were to follow this, then we would have complete information about the control flow inside the procedure box.

Note that the box we have drawn round the predicate should really be seen as an invocation box. That is, there will be a different box for each different invocation of the predicate. Obviously, with something like a recursive predicate, there will be many different Calls and Exits in the control flow, but these will be for different invocations. Since this might get confusing each invocation box is given a unique integer identifier.

In addition to the five basic ports discussed above, there are two more ports for invocations involving a blocked goal:

Block
This port is passed through when a goal is blocked.
Unblock
This port is passed through when a previously blocked goal is unblocked.


Node:Basic Debug, Next:, Previous:Procedure Box, Up:Debug Intro

Basic Debugging Predicates

Development systems provide a range of built-in predicates for control of the debugging facilities. The most basic predicates are as follows:

debug

Switches the debugger on, and ensures that the next time control reaches a spypoint, it will be activated. In basic usage this means that a message will be produced and you will be prompted for a command. In order for the full range of control flow information to be available it is necessary to have the debugger on from the start. When it is off the system does not remember invocations that are being executed. (This is because it is expensive and not required for normal running of programs.) You can switch Debug Mode on in the middle of execution, either from within your program or after a ^C (see trace/0 below), but information prior to this will be unavailable.

zip

Same as debug/0, except no debugging information is being collected, and so is almost as fast as running with the debugger switched off.

trace

Switches the debugger on, and ensures that the next time control enters an invocation box, a message will be produced and you will be prompted for a command. The effect of trace can also be achieved by typing t after a ^C interruption of a program.

At this point you have a number of options. See Debug Commands. In particular, you can just type <RET> to creep (or single-step) into your program. If you continue to creep through your program you will see every entry and exit to/from every invocation box, including compiled code, except for code belonging to hidden modules (see Def Modules). You will notice that the debugger stops at all ports. However, if this is not what you want, the following built-in predicate gives full control over the ports at which you are prompted:

leash(+Mode)

Leashing Mode is set to Mode. Leashing Mode determines the ports of invocation boxes at which you are to be prompted when you Creep through your program. At unleashed ports a tracing message is still output, but program execution does not stop to allow user interaction. Note that leash/1 does not apply to spypoints, the leashing mode of these can be set using the advanced debugger features; see Advanced Debugging. Block and Unblocked ports cannot be leashed. Mode can be a subset of the following, specified as a list of the following:

call
Prompt on Call.
exit
Prompt on Exit.
redo
Prompt on Redo.
fail
Prompt on Fail.
exception
Prompt on Exception.

The following shorthands are also allowed:

?- leash(full).
Same as ?- leash([call,exit,redo,fail,exception])..
?- leash(half).
Same as ?- leash([call,redo])..
?- leash(none).
Same as ?- leash([])..

The initial value of Leashing Mode is [call,exit,redo,fail,exception] (full leashing).

nodebug
notrace
nozip

Switches the debugger off. If there are any spypoints set then they will be kept but will never be activated.

debugging

Prints information about the current debugging state. This will show:

  1. Whether undefined predicates are being trapped.
  2. What breakpoints have been set (see below).
  3. What mode of leashing is in force (see above).


Node:Plain Spypoint, Next:, Previous:Basic Debug, Up:Debug Intro

Plain Spypoints

For programs of any size, it is clearly impractical to creep through the entire program. Spypoints make it possible to stop the program whenever it gets to a particular predicate which is of interest. Once there, one can set further spypoints in order to catch the control flow a bit further on, or one can start creeping.

In this section we discuss the simplest form of spypoints, the plain spypoints. The more advanced forms, the conditional and generic spypoints will be discussed later; see Advanced Debugging.

Setting a plain spypoint on a predicate indicates that you wish to see all control flow through the various ports of its invocation boxes, except during skips. When control passes through any port of an invocation box with a spypoint set on it, a message is output and the user is asked to interact. Note that the current mode of leashing does not affect plain spypoints: user interaction is requested on every port.

Spypoints are set and removed by the following built-in predicates. The first two are also standard operators:

spy :Spec

Sets plain spypoints on all the predicates given by the generalized predicate spec Spec.

Examples:

| ?- spy [user:p, m:q/[2,3]].
| ?- spy m:[p/1, q/1].

If you set some spypoints when the debugger is switched off then it will be automatically switched on, entering zip mode.

nospy :Spec

Similar to spy Spec except that all the predicates given by Spec will have all previously set spypoints removed from them (including conditional spypoints; see Creating Breakpoints).

nospyall

Removes all the spypoints that have been set, including the conditional and generic ones.

The commands available when you arrive at a spypoint are described later. See Debug Commands.


Node:Debug Format, Next:, Previous:Plain Spypoint, Up:Debug Intro

Format of Debugging Messages

We shall now look at the exact format of the message output by the system at a port. All trace messages are output to the standard error stream, using the print_message/2 predicate; see Messages and Queries. This allows you to trace programs while they are performing file I/O. The basic format is as follows:

N S    23     6 Call: T foo(hello,there,_123) ?

N is only used at Exit ports and indicates whether the invocation could backtrack and find alternative solutions. Unintended nondeterminacy is a source of inefficiency, and this annotation can help spot such efficiency bugs. It is printed as ?, indicating that foo/3 could backtrack and find alternative solutions, or otherwise.

S is a spypoint indicator. If there is a plain spypoint on foo/3, it is printed as +. In case of conditional and generic spypoints it takes the form * and #, respectively. Finally, it is printed as , if there is no spypoint on the predicate being traced.

The first number is the unique invocation identifier. It is increasing regardless of whether or not debugging messages are output for the invocations (provided that the debugger is switched on). This number can be used to cross correlate the trace messages for the various ports, since it is unique for every invocation. It will also give an indication of the number of procedure calls made since the start of the execution. The invocation counter starts again for every fresh execution of a command, and it is also reset when retries (see later) are performed.

The number following this is the current depth; i.e. the number of direct ancestors this goal has, for which a procedure box has been built by the debugger.

The next word specifies the particular port (Call, Exit, Redo, Fail, or Exception).

T is a subterm trace. This is used in conjunction with the ^ command (set subterm), described below. If a subterm has been selected, T is printed as the sequence of commands used to select the subterm. Normally, however, T is printed as , indicating that no subterm has been selected.

The goal is then printed so that you can inspect its current instantiation state.

The final ? is the prompt indicating that you should type in one of the commands allowed (see Debug Commands). If this particular port is unleashed then you will not get this prompt since you have specified that you do not wish to interact at this point.

At Exception ports, the trace message is preceded by a message about the pending exception, formatted as if it would arrive uncaught at the top level.

Note that calls that are compiled in-line and built-in predicates at depth 1 (e.g. those called directly from the top-level) are not traced.

Block and unblock ports are exceptions to the above debugger message format. A message

       S -  -  Block: p(_133)

indicates that the debugger has encountered a blocked goal, i.e. one which is temporarily suspended due to insufficiently instantiated arguments (see Procedural). By default, no interaction takes place at this point, and the debugger simply proceeds to the next goal in the execution stream. The suspended goal will be eligible for execution once the blocking condition ceases to exist, at which time a message

       S -  -  Unblock: p(_133)

is printed. Although Block and Unblock ports are unleashed by default in trace mode, you can make the debugger interact at these ports by using conditional spypoints.


Node:Debug Commands, Next:, Previous:Debug Format, Up:Debug Intro

Commands Available during Debugging

This section describes the particular commands that are available when the system prompts you after printing out a debugging message. All the commands are one or two letter mnemonics, some of which can be optionally followed by an argument. They are read from the standard input stream with any blanks being completely ignored up to the end of the line (<RET>).

The only command which you really have to remember is h (followed by <RET>). This provides help in the form of the following list of available commands.

   <cr>   creep            c      creep
    l     leap             z      zip
    s     skip             s <i>  skip i
    o     out              o <n>  out n
    q     q-skip           q <i>  q-skip i
    r     retry            r <i>  retry i
    f     fail             f <i>  fail i
    j<p>  jump to port     j<p><i>jump to port i
    d     display          w      write
    p     print            p <i>  print partial
    g     ancestors        g <n>  ancestors n
    t     backtrace        t <n>  backtrace n
    &     blocked goals    & <n>  nth blocked goal
    n     nodebug          =      debugging
    +     spy this         *      spy conditionally
    -     nospy this       \ <i>  remove brkpoint
    D <i> disable brkpoint E <i>  enable brkpoint
    a     abort            b      break
    @     command          u      unify
    e     raise exception  .      find this
    <     reset printdepth < <n>  set printdepth
    ^     reset subterm    ^ <n>  set subterm
    ?     help             h      help
c
<RET>
creep causes the debugger to single-step to the very next port and print a message. Then if the port is leashed (see Basic Debug), the user is prompted for further interaction. Otherwise, it continues creeping. If leashing is off, creep is the same as leap (see below) except that a complete trace is printed on the standard error stream.
l
leap causes the debugger to resume running your program, only stopping when a spypoint is reached (or when the program terminates). Leaping can thus be used to follow the execution at a higher level than exhaustive tracing. All you need to do is to set spypoints on an evenly spread set of pertinent predicates, and then follow the control flow through these by leaping from one to the other. Debugging information is collected while leaping, so when a spypoint is reached, it is possible to inspect the ancestor goals, or creep into them upon entry to Redo ports.
z
zip is like leap, except no debugging information is being collected while zipping, resulting in significant savings in memory and execution time.
s
skip is only valid for Call and Redo ports. It skips over the entire execution of the predicate. That is, you will not see anything until control comes back to this predicate (at either the Exit port or the Fail port). Skip is particularly useful while creeping since it guarantees that control will be returned after the (possibly complex) execution within the box. If you skip then no message at all will appear until control returns. This includes calls to predicates with spypoints set; they will be masked out during the skip. No debugging information is being collected while skipping.

If you supply an integer argument, then this should denote an invocation number of an ancestral goal. The system tries to get you to the Exit or Fail port of the invocation box you have specified.

o
out is a shorthand for skipping to the Exit or Fail port of the immediate ancestor goal. If you supply an integer argument n, it denotes skipping to the Exit or Fail port of the nth ancestor goal.
q
quasi-skip is like a combination of zip and skip: execution stops when either control comes back to this predicate, or a spypoint is reached. No debugging information is being collected while quasi-skipping.

An integer argument can be supplied as for skip.

r
retry can be used at any port (although at the Call port it has no effect). It transfers control back to the Call port of the box. This allows you to restart an invocation when, for example, you find yourself leaving with some weird result. The state of execution is exactly the same as when you originally called, (unless you use side effects in your program; i.e. asserts etc. will not be undone). When a retry is performed the invocation counter is reset so that counting will continue from the current invocation number regardless of what happened before the retry. This is in accord with the fact that you have, in executional terms, returned to the state before anything else was called.

If you supply an integer argument, then this should denote an invocation number of an ancestral goal. The system tries to get you to the Call port of the box you have specified. It does this by continuously failing until it reaches the right place. Unfortunately this process cannot be guaranteed: it may be the case that the invocation you are looking for has been cut out of the search space by cuts (!) in your program. In this case the system fails to the latest surviving Call port before the correct one.

f
fail can be used at any of the four ports (although at the Fail port it has no effect). It transfers control to the Fail port of the box, forcing the invocation to fail prematurely.

If you supply an integer after the command, then this is taken as specifying an invocation number and the system tries to get you to the Fail port of the invocation box you have specified. It does this by continuously failing until it reaches the right place. Unfortunately this process cannot be guaranteed: it may be the case that the invocation you are looking for has been cut out of the search space by cuts (!) in your program. In this case the system fails to the latest surviving Fail port before the correct one.

j<p>
jump to port transfers control back to the prescribed port <p>. Here, <p> is one of: c, e, r, f, standing for Call, Exit, Redo and Fail ports. Takes an optional integer argument, an invocation number.

Jumping to a Call port is the same as retrying it, i.e. jc is the same as the r debugger command; and similarly jf is the same as f.

The je jump to Exit port command transfers control back to the Exit port of the box. It can be used at a Redo or an Exit port (although at the latter it has no effect). This allows you to restart a computation following an Exit port, which you first leapt over, but because of its unexpected failure you arrived at the Redo port. When you supply an integer argument, then this should denote an exact invocation number of an exited invocation present in the backtrace, and then the system will get you to the specified Exit port. The debugger requires here an exact invocation number so that it does not jump too far back in the execution (if an Exit port is not present in the backtrace, it may be be a better choice to jump to the preceding Call port, rather than to continue looking for another Exit port).

The jr jump to Redo port command transfers control back to the Redo port of the box. It can be used at an Exit or a Redo port (although at the latter it has no effect). This allows you to force the goal in question to try to deliver another solution. When you supply an integer argument, then this should denote an exact invocation number of an exited invocation present in the backtrace, and then the system will get you to the specified Redo port.

d
display goal displays the current goal using display/1. See Write (below).
p
print goal displays the current goal using print/1. An argument will override the default printdepth, treating 0 as infinity.
w
write goal displays the current goal using writeq/1.
g
print ancestor goals provides you with a list of ancestors to the current goal, i.e. all goals that are hierarchically above the current goal in the calling sequence. You can always be sure of jumping to the Call or Fail port of any goal in the ancestor list (by using retry etc). If you supply an integer n, then only that number of ancestors will be printed. That is to say, the last n ancestors will be printed counting back from the current goal. Each entry is displayed just as they would be in a trace message.
t
print backtrace is the same as the above, but also shows any goals that have exited nondeterministically and their ancestors. This information shows where there are outstanding choices that the program could backtrack to. If you supply an integer n, then only that number of goals will be printed.

Ancestors to the current goal are annotated with the Call: port, as they have not yet exited, whereas goals that have exited are annotated with the Exit: port. You can always be sure of jumping to the Exit or Redo port of any goal shown to be exited in the backtrace listing.

The backtrace is a tree rather than a stack: to find the parent of a given goal with depth indicator d, look for the closest goal above it with depth indicator d-1.

&
print blocked goals prints a list of the goals which are currently blocked in the current debugging session together with the variable that each such goal is blocked on (see Procedural). The goals are enumerated from 1 and up. If you supply an integer n, then only that goal will be printed. Each entry is preceded by the goal number followed by the variable name.
n
nodebug switches the debugger off. Note that this is the correct way to switch debugging off at a trace point. You cannot use the @ or b commands because they always return to the debugger.
=
debugging outputs information concerning the status of the debugging package. See Debug Pred, the built-in debugging/0.
+
spy this sets a plain spypoint on the current goal.
*
spy this conditionally sets a conditional spypoint on the current goal. Prompts for the Conditions, and calls the
spy(Func, Conditions)
goal, where Func is the predicate spec of the current invocation. For spy/2, see Breakpoint Predicates.
-
nospy this removes all spypoints applicable to the current goal. Equivalent to nospy Func, where Func is the predicate spec of the current invocation.
\
remove this removes the spypoint which caused the debugger to interact at the current port. With an argument n, it removes the breakpoint with identifier n. Equivalent to remove_breakpoints(BID), where BID is the current breakpoint identifier, or the supplied argument (see Breakpoint Predicates).
D
disable this disables the spypoint which caused the debugger to interact at the current port. With an argument n, it disables the breakpoint with identifier n. Equivalent to disable_breakpoints(BID), where BID is the current breakpoint identifier, or the supplied argument (see Breakpoint Predicates).
E
enable this enables all specific spypoints for the predicate at the current port. With an argument n, it enables the breakpoint with identifier n. Equivalent to enable_breakpoints(BID), where BID is the breakpoint identifiers for the current predicate, or the supplied argument (see Breakpoint Predicates).
.
find this outputs information about where the predicate being called is defined.
a
abort causes an abort of the current execution. All the execution states built so far are destroyed and you are put right back at the top-level. (This is the same as the built-in predicate abort/0.)
b
break calls the built-in predicate break/0, thus putting you at a recursive top-level with the execution so far sitting underneath you. When you end the break (^D) you will be reprompted at the port at which you broke. The new execution is completely separate from the suspended one; the invocation numbers will start again from 1 during the break. The debugger is temporarily switched off as you call the break and will be re-switched on when you finish the break and go back to the old execution. However, any changes to the leashing or to spypoints will remain in effect.
@
command gives you the ability to call arbitrary Prolog goals. It is effectively a one-off break (see above). The initial message | :- will be output on the standard error stream, and a command is then read from the standard input stream and executed as if you were at top-level. If the term read is of form Pattern ^ Body, then Pattern is unified with the current goal and Body is executed.
u
unify is available at the Call port and gives you the option of providing a solution to the goal from the standard input stream rather than executing the goal. This is convenient e.g. for providing a "stub" for a predicate that has not yet been written. A prompt will be output on the standard error stream, and the solution is then read from the standard input stream and unified with the goal. If the term read in is of the form Head :- Body, then Head will be unified with the current goal, and Body will be executed in its place.
e
raise exception is available at all ports. A prompt will be output on the standard error stream, and an exception term is then read from the standard input stream and raised in the program being debugged.
<
This command, without arguments, resets the printdepth to 10. With an argument of n, the printdepth is set to n, treating 0 as infinity.
^
While at a particular port, a current subterm of the current goal is maintained. It is the current subterm which is displayed, printed, or written when prompting for a debugger command. Used in combination with the printdepth, this provides a means for navigating in the current goal for focusing on the part which is of interest. The current subterm is set to the current goal when arriving at a new port. This command, without arguments, resets the current subterm to the current goal. With an argument of n (> 0), the current subterm is replaced by its n:th subterm. With an argument of 0, the current subterm is replaced by its parent term. With a list of arguments, the arguments are applied from left to right.
?
h
help displays the table of commands given above.

The user can define new debugger commands or modify the behavior of the above ones using the debugger_command_hook hook predicate, see Breakpoint Predicates.


Node:Advanced Debugging, Next:, Previous:Debug Commands, Up:Debug Intro

Advanced Debugging -- an Introduction

This section gives an overview of the advanced debugger features. These center around the notion of breakpoint. Breakpoints can be classified as either spypoints (a generalization of the plain spypoint introduced earlier) or advice-points (e.g. for checking program invariants independently from tracing). The first five subsections will deal with spypoints only. Nevertheless we will use the term breakpoint, whenever a statement is made which applies to both spypoints and advice-points. Breakpoint Processing describes the breakpoint processing mechanism in full detail. Reference style details of built-in predicates dealing with breakpoints are given in Breakpoint Predicates and in Breakpoint Conditions.


Node:Creating Breakpoints, Next:, Previous:Advanced Debugging, Up:Advanced Debugging

Creating Breakpoints

Breakpoints can be created using the add_breakpoint/2 built-in predicate. Its first argument should contain the description of the breakpoint, the so called breakpoint spec. It will return the breakpoint identifier (BID) of the created breakpoint in its second argument. For example:

| ?- add_breakpoint(pred(foo/2), BID).
% Plain spypoint for user:foo/2 added, BID=1
BID = 1 ?

Here, we have a simple breakpoint spec, prescribing that the debugger should stop at all ports of all invocations of the predicate foo/2. Thus the above goal actually creates a plain spypoint, exactly as ?- spy foo/2. does.

A slightly more complicated example follows:

| ?- add_breakpoint([pred(foo/2),line(123)], _).
% Conditional spypoint for user:foo/2 added, BID=1
yes

This breakpoint will be activated only for those calls of foo/2, which occur in line 123 in one of the Prolog program files. Because of the additional condition, this is called conditional spypoint.

The breakpoint identifier (BID) returned by add_breakpoint/2 is an integer, assigned in increasing order, i.e. more recent breakpoints receive higher identifier values. When looking for applicable breakpoints, the debugger tries the breakpoints in descending order of BIDs, i.e. the most recent applicable breakpoint is used. Breakpoint identifiers can be used for referring to breakpoints to be deleted, disabled or enabled (see later).

Generally, the breakpoint spec is a pair Tests-Actions. Here, the Tests part describes the conditions under which the breakpoint should be activated, while the Actions part contains instructions on what should be done at activation. The test part is built from tests, while the action part from actions and tests. Test, actions and composite constructs built from these are generally referred to as breakpoint conditions, or simply conditions.

The default action part for spypoints is [show(print),command(ask)]. This instructs the debugger to print the goal in question and then ask the user what to do next, exactly as described in Debug Format. To illustrate other possibilities let us explain the effect of the [show(display),command(proceed)] action part: this will use display/1 for presenting the goal (just as the d debugger command, see Debug Commands), and will then proceed with execution without stopping (i.e. the spypoint is unleashed).


Node:Processing Breakpoints, Next:, Previous:Creating Breakpoints, Up:Advanced Debugging

Processing Breakpoints

We first give a somewhat simplified sketch of how the debugger treats the breakpoints. This description will be refined in the sequel.

The debugger allows us to prescribe some activities to be performed at certain points of execution, namely at the ports of procedure boxes. In principle, the debugger is entered at each port of each procedure invocation. It then considers the current breakpoints one by one, most recent first. The first breakpoint for which the evaluation of the test part succeeds is then activated, and the execution continues according to its action part. The activated breakpoint "hides" the remaining (older) ones, i.e. those are not tried here. If none of the current breakpoints is activated, the debugger behaves according to the actual debugging mode (trace, debug or zip).

Both the test and the action part can be simple or composite. Evaluating a simple test amounts to checking whether it holds in the current state of execution, e.g. pred(foo/2) holds if the debugger is at a port of predicate foo/2.

Composite conditions can be built from simple ones by forming lists, or using the ,, ;, ->, and \+ operators, with the usual meaning of conjunction, disjunction, if-then-else and negation. A list of conditions is equivalent to a conjunction of the same conditions. For example, the condition [pred(foo/2), \+port(fail)] will hold for all ports of foo/2, except for the Fail port.


Node:Breakpoint Tests, Next:, Previous:Processing Breakpoints, Up:Advanced Debugging

Breakpoint Tests

This section gives a tour of the most important simple breakpoint tests. In all examples here, the action part will be empty. Note that the examples are independent, so if you want to try out these, you should get rid of the old breakpoints (e.g. using ?- nospyall.) before you enter a new one.

The goal(...) test is a generalization of the pred(...) test, as it allows us to check the arguments of the invocation. For example:

| ?- add_breakpoint(goal(foo(1,_)), _).
% Conditional spypoint for user:foo/2 added, BID=1

The goal(G) breakpoint test specifies that the breakpoint should be applied only if it unifies with G. Thus in the above example the debugger will stop if foo/2 is called with 1 as its first argument, but not if the first argument is, say, 2.

Note that the above breakpoint can only be used safely if the first argument of foo/2 is input, i.e. it is never uninstantiated at the Call port. This is because the debugger actually unifies the term given within the goal test with the current goal. If foo/2 is called with a variable first argument, then the above breakpoint instantiates the variable to 1, which is probably not what you intended to do!

If you have a predicate foo/2 which sometimes is called with a variable first argument, and you want the debugger to stop when the first argument is a specific constant (say 1), here is what you should do:

| ?- add_breakpoint([goal(foo(X,_)),true(X==1)], _).
% Conditional spypoint for user:foo/2 added, BID=1

Here the first test, goal, specifies that we are only interested in invocations of foo/2, and names the first argument of the goal as X. The second, the true/1 test specifies a further condition stated as a Prolog goal: X is identical to 1. Thus this breakpoint will be applicable if and only if the first argument of foo/2 is identical to 1. Generally, an arbitrary Prolog goal can be placed inside the true test: the test will succeed iff the goal completes successfully.

Both the pred and the goal tests may include a module name. In fact, the first argument of add_breakpoint is module name expanded, and the (explicit or implicit) module name of this argument is then inherited by default by the pred, goal, and true tests. Notice the module names inserted in the breakpoint spec of the last example, as shown in the output of the debugging built-in predicate:

| ?- debugging.
(...)
Breakpoints:
      1 *  user:foo/2 if [goal(user:foo(A,B)),true(user:(A==1))]

For exported predicates, a pred or goal test will be found applicable for all invocations of the predicate, irrespective of the module they occur in. When you add the breakpoint you can use the defining or an importing module name, but this information is not remembered: the module name is "normalized", i.e. it is changed to the defining module. For example:

| ?- use_module(library(lists)).
(...)
% module lists imported into user
(...)
| ?- spy user:append.
% Plain spypoint for lists:append/3 added, BID=1
yes
| ?- debugging.
(...)
Breakpoints:
      1 +  lists:append/3

If you would like to restrict a breakpoint to calls from within a particular module, then you should use the module test, e.g.

| ?- add_breakpoint([pred(append/3),module(user)], _).
% Conditional spypoint for lists:append/3 added, BID=1
yes
% zip
| ?- append([1,2], [3,4], L).
 *      1      1 Call: append([1,2],[3,4],_458) ? z
 *      1      1 Exit: append([1,2],[3,4],[1,2,3,4]) ?
L = [1,2,3,4] ?
yes

With this spypoint, the debugger will only stop at the invocations of append/3 from the user module. In the above example the debugger does not stop at the recursive calls to append/3 (from within the lists module), as would be the case with a plain spypoint.

Note that calling module information is not kept by the compiler for the built-in predicates, therefore the module test will always unify its argument with prolog in case of compiled calls to built-ins.

There are two further interesting breakpoint tests related to invocations: inv(Inv) and depth(Depth). These unify they arguments with the invocation number and the depth, respectively (the two numbers shown at the beginning of each trace message). Such tests are most often used in more complex breakpoints, but there may be some simple cases when they are useful.

Assume you put a plain spypoint on foo/2, and start leaping through your program. After some time, you notice some inconsistency at an Exit port, but you cannot go back to the Call port for retrying this invocation, because of side effects. So you would like to restart the whole top-level goal and get back to the Call port of the suspicious goal as fast as possible. Here is what you can do:

| ?- spy foo/2.
% Plain spypoint for user:foo/2 added, BID=1
yes
| ?- debug, foo(23, X).
% The debugger will first leap -- showing spypoints (debug)
 +      1      1 Call: foo(23,_414) ? l
(...)
 +     81     17 Call: foo(7,_9151) ? l
 +     86     18 Call: foo(6,_9651) ? l
 +     86     18 Exit: foo(6,8) ? -
% Plain spypoint for user:foo/2, BID=1, removed (last)
       86     18 Exit: foo(6,8) ? *
Placing spypoint on user:foo/2 with conditions: inv(86).
% Conditional spypoint for user:foo/2 added, BID=1
 *     86     18 Exit: foo(6,8) ? a
% Execution aborted
% source_info
| ?- debug, foo(23, X).
% The debugger will first leap -- showing spypoints (debug)
 *     86     18 Call: foo(6,_2480) ?

When you reach the Exit port of the suspicious invocation (number 86), you remove the plain spypoint, and add a conditional one using the * debugger command. This automatically includes pred(foo/2) among the conditions and displays the prompt Placing spypoint ... with conditions:, requesting further ones. You enter here the inv test with the invocation number in question, resulting in a breakpoint with the [pred(foo/2),inv(86)] conditions. If you restart the original top-level goal in debug mode, the debugger immediately positions you at the invocation with the specified number.

Note that when the debugger executes a skip or a zip command, no procedure boxes are built. Consequently, the invocation and depth counters are not incremented. If skip and/or zip commands were used during the first execution, then the suspicious invocation gets an invocation number higher than 86 in the second run. Therefore it is better to supply the inv(I),true(I>=86) condition to the * debugger command, which will bring you to the first call of foo/2 at, or after invocation number 86 (which still might not be the suspicious invocation).

In the examples, the inv test was used both with a numeric and a variable argument (inv(86) and inv(I)). This is possible because the debugger unifies the given feature with the argument of the test. This holds for most tests, we will mention the exceptions.

Another similar example: if you suspect that a given predicate goes into an infinite recursion, and would like the execution to stop when entering this predicate somewhere inside the recursion, then you can do the following:

| ?- add_breakpoint([pred(foo/2),depth(_D),true(_D>=100)], _).
% Conditional spypoint for user:foo/2 added, BID=1
yes
% zip,source_info
 | ?- debug, foo(200, X).
% The debugger will first leap -- showing spypoints (debug)
 *    496    100 Call: foo(101,_12156) ?

The above breakpoint spec will cause the debugger to stop at the first invocation of foo/2 at depth 100 or greater. Note again that debug mode has to be entered for this to work (in zip mode no debugging information is kept, so the depth does not change).

We now continue with tests which restrict the breakpoint to an invocation at a specific place in the code.

Assume file /home/bob/myprog.pl contains the following Prolog program:

p(X, U) :-                               % line 1
        q(X, Y),                         % line 2
        q(Y, Z),                         % line 3
        (   \+ q(Z, _)                   % line 4
        ->  q(Z+1, U)                    % line 5
        ;   q(Z+2, U)                    % line 6
        ).                               % ...

q(X, Y) :-
        X < 10, !, Y is X+1.             % line 10
q(X, Y) :-
        Y is X+2.                        % line 12

If you are interested only in the last invocation of q/2 within p/2, you can use the following breakpoint:

| ?- add_breakpoint([pred(q/2),line('/home/bob/myprog.pl',6)], _).
% Conditional spypoint for user:q/2 added, BID=1

Generally, the test line(File,Line) holds, if the current invocation was in line number Line of a file whose absolute name is File. This test (as well as the line/1 and file/1 tests) require the presence of source information: the file in question had to be consulted or compiled with the source_info prolog flag switched on (i.e. set to on or emacs).

If e.g. q/2 is called only from a single file, then the file name need not be mentioned and a line/1 test suffices: line(6). On the other hand, if we are interested in all invocations of a predicate within a file, then we can omit the line number and use the file(File) test.

For Prolog programs which are interpreted (consulted or asserted), further positioning information can be obtained, even in the absence of source information. The test parent_pred(Pred) unifies Pred with a predicate spec (of form Module:PredName/Arity) identifying the predicate in which the current invocation resides, while the test parent_pred(Pred,N) will additionally unify N with the serial number of the clause containing the current goal.

For example, assuming the above myprog.pl file is consulted, the breakpoint below will stop when execution reaches the call of is/2 in the second clause of q/2:

| ?- add_breakpoint([pred(is/2),parent_pred(user:q/2,2)], _).
% Conditional spypoint for prolog:is/2 added, BID=1
* Predicate prolog:is/2 compiled inline, breakable only in interpreted code
yes
% zip,source_info
| ?- p(20, X).
in scope of a goal at line 12 in /home/bob/myprog.pl
 *      1      1 Call: _579 is 20+2 ?

Note that one has to include an explicit module name prefix in the first argument of parent_pred, for the unification of the predicate spec to succeed. Also notice the warning issued by add_breakpoint/2: there are some built-ins (e.g. arithmetic, functor/3, arg/3, etc.), for which the compiler generates specific inline translation, rather than the generic predicate invocation code. Therefore compiled calls to such predicates are not visible to the debugger.

More exact positioning information can be obtained for interpreted programs by using the parent_clause(Cl,Sel,I) test. This unifies Cl with the clause containing the current invocation, while Sel and I both identify the current invocation within the body of this clause. Sel is unified with a subterm selector, while I with the serial number of the call. This test has variants parent_clause/[1,2], in which only the Cl argument, or the Cl,Sel arguments are present.

As an example, two further alternatives of putting a breakpoint on the last call of q/2 within myprog.pl (line 6) are shown below, together with a listing showing the selectors and call serial numbers for the body of p/2:

| ?- add_breakpoint([pred(q/2),parent_clause((p(_,_):-_),[2,2,2])],_).

| ?- add_breakpoint([pred(q/2),parent_clause((p(_,_):-_),_,5)],_).

p(X, U) :-                 % line  % call no.  % subterm selector
        q(X, Y),           %  2        1       [1]
        q(Y, Z),           %  3        2       [2,1]
        (   \+ q(Z, _)     %  4        3       [2,2,1,1,1]
        ->  q(Z+1, U)      %  5        4       [2,2,1,2]
        ;   q(Z+2, U)      %  6        5       [2,2,2]
        ).                 %  7

Here, the first argument of the parent_clause test ensures that the current invocation is in (the only clause of) p/2. If p/2 had more clauses, we would have to use an additional test, say parent_pred(user:p/2,1), and then the first argument of parent_clause could be an anonymous variable.

In the examples so far the breakpoint tests referred only to the goal in question. Therefore, the breakpoint was found applicable at all ports of the procedure box of the predicate. We can distinguish between ports using the port breakpoint test:

| ?- add_breakpoint([pred(foo/2),port(call)], _).

With this breakpoint, the debugger will stop at the Call port of foo/2, but not at other ports. Note that the port(call) test can be simplified to call -- add_breakpoint/2 will recognize this as a port name, and treat it as if it were enclosed in a port/1 functor.

Here are two equivalent formulations for a breakpoint which will cause the debugger to stop only at the Call and Exit ports of foo/2:

| ?- add_breakpoint([pred(foo/2),(call;exit)], _).

| ?- add_breakpoint([pred(foo/2),port(P),true((P=call;P=exit(_)))], _).

In both cases we have to use disjunction. In the first example we have a disjunctive breakpoint condition of the two simple tests port(call) and port(exit) (with the port functor omitted). In the second case the disjunction is inside the Prolog test within the true test.

Notice that the two examples refer to the Exit port differently. When you use port(P), where P is a variable, then, at an exit port, P will be unified with either exit(nondet) or exit(det), depending on the determinacy of the exited procedure. However, for convenience, the test port(exit) will also succeed at Exit ports. So in the first example above, exit can be replaced by exit(_), but the exit(_) in the second can not be replaced by exit.

Finally, there is a subtle point to note with respect to activating the debugger at non Call ports. Let us look at the following breakpoint:

| ?- add_breakpoint([pred(foo/2),fail], _).

The intention here is to have the debugger stop at only the Fail port of foo/2. This is very useful if foo/2 is not supposed to fail, but we suspect that it does. The above breakpoint will behave as expected when the debugger is leaping, but not while zipping. This is because for the debugger to be able to stop at a non Call port, a procedure box has to be built at the Call port of the given invocation. However, no debugging information is collected in zip mode by default, i.e. procedure boxes are not built. Later we will show how to achieve the required effect, even in zip mode.


Node:Specific and Generic Breakpoints, Next:, Previous:Breakpoint Tests, Up:Advanced Debugging

Specific and Generic Breakpoints

In all the examples so far a breakpoint was put on a specific predicate, described by a goal or pred test. Such breakpoints are called specific, as opposed to generic ones.

Generic breakpoints are the ones which do not specify a concrete predicate. This can happen when the breakpoint spec does not contain goal or pred tests at all, or their argument is not sufficiently instantiated. Here are some examples of generic breakpoints:

| ?- add_breakpoint(line('/home/bob/myprog.pl',6), _).
% Generic spypoint added, BID=1
yes
| ?- add_breakpoint(pred(foo/_), _).
% Generic spypoint added, BID=2
yes
| ?- add_breakpoint([goal(G),true((arg(1,G,X),X==bar))], _).
% Generic spypoint added, BID=3
true ?

The first breakpoint will stop at all calls in line 6 of the given file, the second at all calls of a predicate foo, irrespective of the number of arguments, while the third one will stop at any predicate with bar as its first argument. However, there is an additional implicit condition: the module name expansion inserts the type-in module as the default module name in all three cases:

Breakpoints:
      3 #  generic if [goal(user:A),true(user:(arg(1,A,B),B==bar))]
      2 #  generic if [pred(user:foo/A)]
      1 #  generic if [goal(user:A),line('/home/bob/myprog.pl',6)]

Notice that even the breakpoint with BID 1, which originally contained a single line condition, has been expanded to include a goal test, with the type-in module name. To get rid of it, you have to provide an explicit anonymous variable module name in front of the breakpoint spec. In the other two examples you can include an anonymous module prefix in the argument of the goal or pred test:

| ?- add_breakpoint(_:line('/home/bob/myprog.pl',6), _).
% Generic spypoint added, BID=1
yes
| ?- add_breakpoint(pred(_:foo/_), _).
% Generic spypoint added, BID=2
yes
% zip,source_info
| ?- add_breakpoint([goal(_:G),true((arg(1,G,X),X==bar))], _).
% Generic spypoint added, BID=3
true ?
yes
| ?- debugging.
(...)
Breakpoints:
      3 #  generic if [goal(A:B),true(user:(arg(1,B,C),C==bar))]
      2 #  generic if [pred(A:foo/B)]
      1 #  generic if [line('/home/bob/myprog.pl',6)]

Generic breakpoints are very powerful, but there is a price to pay: the zip debugging mode is slowed down considerably.

As said earlier, in principle the debugger is entered at each port of each procedure invocation. As an optimization, the debugger can request the underlying Prolog engine to run at full speed and invoke the debugger only when one of the specified predicates is called. This optimization is used in zip mode, provided there are no generic breakpoints. In the presence of generic breakpoints, however, the debugger has to be entered at each call, to check their applicability. Consequently, with generic breakpoints, zip mode execution will not give much speed-up over debug mode, although its space requirements will still be much lower.

It is therefore advisable to give preference to specific breakpoints over generic ones, whenever possible. For example, if your program includes predicates foo/2 and foo/3, then it is much better to create two specific breakpoints, rather than a single generic one with conditions [pred(foo/_),...].

spy/2 is a built-in predicate which will create specific breakpoints only. Its first argument is a generalized predicate spec, much like in spy/1, and the second argument is a breakpoint spec. spy/2 will expand the first argument to one or more predicate specs, and for each of these will create a breakpoint, with a pred condition added to the test part of the supplied breakpoint spec. For example, in the presence of predicates foo/2 and foo/3

| ?- spy(foo/_, file(...))

is equivalent to:

| ?- add_breakpoint([pred(foo/2),file(...)], _),
     add_breakpoint([pred(foo/3),file(...)], _).

Note that with spy/[1,2] it is not possible to put a breakpoint on a (yet) undefined predicate. On the other hand, add_breakpoint/2 is perfectly capable of creating such breakpoints.


Node:Breakpoint Actions, Next:, Previous:Specific and Generic Breakpoints, Up:Advanced Debugging

Breakpoint Actions

The action part of a breakpoint spec supplies information to the debugger as to what should be done when the breakpoint is activated. This is achieved by setting the three so called debugger action variables, listed below, together with their most important values.

For example, the breakpoint below specifies that whenever the Exit port of foo/2 is reached, no trace message should be output, no interaction should take place and the debugger should be switched off.

| ?- add_breakpoint([pred(foo/2),port(exit)]-
                    [show(silent),command(proceed),mode(off)], _).

Here, the action part consists of three actions, setting the three action variables. This breakpoint spec can be simplified by omitting the wrappers around the variable values, as the sets of possible values of the variables are all disjoint. If we use spy/2 then the pred wrapper goes away, too, resulting in a much more concise, equivalent formulation of the above breakpoint:

| ?- spy(foo/2,exit-[silent,proceed,off])

Let us now revisit the process of breakpoint selection. When the debugger arrives at a port it first initializes the action variables according to the current debugging and leashing modes, as shown below:

debugging    leashing           |        Action variables
mode         mode               |  show        command     mode
--------------------------------|-------------------------------
trace        at leashed port    |  print       ask         trace
                                |
trace        at unleashed port  |  print       proceed     trace
                                |
debug        -                  |  silent      proceed     debug
                                |
zip          -                  |  silent      flit        zip

It then considers each breakpoint, most recent first, until it finds a breakpoint whose test part succeeds. If such a breakpoint is found, its action part is evaluated, normally changing the action variable settings. A failure of the action part is ignored, in the sense that the breakpoint is still treated as the selected one. However, as a side effect, a procedure box will always be built in such cases. More precisely, the failure of the action part causes the flit command value to be changed to proceed, all other command values being left unchanged. This is to facilitate the creation of breakpoints which stop at non-Call ports (see below for an example).

If no applicable breakpoint is found, then the action variables remain unchanged.

The debugger then executes the actions specified by the action variables. This process, referred to as the action execution, means the following:

Specifically, if command is ask, then the user is prompted for a debugger command, which in turn is converted to new assignments to the action variables. The debugger will then repeat the action execution process, described above. For example, the c (creep) interactive command is converted to [silent,proceed,trace], the d (display) command to [display,ask] (when command is ask, the mode is irrelevant), etc.

The default values of the action variables correspond to the standard debugger behavior described in Basic Debug. For example, when an unleashed port is reached in trace mode, then a trace message is printed and the execution proceeds in trace mode, without stopping. In zip mode, no trace message is shown, and execution continues in zip mode, without building procedure boxes at Call ports.

If a spypoint is found applicable, but it does not change the action variables, then the debugger will behave as if no breakpoint was found. For example:

| ?- spy(foo/2, parent_pred(P)-true(format('Called from:~w~n',[P]))).

This spypoint will produce some output at ports of foo/2 called from within an interpreted clause, but otherwise will not influence the debugger. We see here a parent_pred condition with a variable argument, placed in the test part and a true condition appearing in the action part. Goals with side effects should only be called from the action part, because the test part may be evaluated multiple times for a single port -- that is why this true condition appears in the action part. On the other hand parent_pred can fail (if the current goal is invoked from compiled code), so it should normally be put in the test part.

Note that an action part which is [] or omitted is actually treated as [print,ask]. Again, this is the standard behavior of spypoints, as described in Basic Debug.

Let us look at some simple examples of what other effects can be achieved by appropriate action variable settings:

| ?- spy(foo/2, -[print,proceed]).
% Conditional spypoint for user:foo/2 added, BID=1
yes
| ?- debugging.
(...)
Breakpoints:
      1 *  user:foo/2 if []-[print,proceed]

This is an example of an unleashed spypoint: it will print a trace message passing each port of foo/2, but will not stop there. Note that because of the proceed command a procedure box will be built, even in zip mode, and so the debugger will be activated at non-Call ports of foo/2. Also notice that a breakpoint spec with an empty test part can be written -Actions.

The next example is a variant of the above:

| ?- spy(foo/2, -[print,flit]).

This will print a trace message at the Call port of foo/2 and will then continue the execution in the current debugging mode, without building a procedure box for this call. This means that the debugger will not be able to notice any other ports of foo/2.

Now let us address the task of stopping at a specific non-Call port of a predicate. For this to work in zip mode, one has to ensure that a procedure box is built at the Call port. In the following example, the first spypoint causes a box to be built for each call of foo/2, while the second one makes the debugger stop when the Fail port of foo/2 is reached.

| ?- spy(foo/2, call-proceed), spy(foo/2, fail).
% Conditional spypoint for user:foo/2 added, BID=1
% Conditional spypoint for user:foo/2 added, BID=2

You can achieve the same effect with a single spypoint, by putting the port condition in the action part, rather than in the test part.

| ?- spy(foo/2, -[fail,print,ask]).

Here, when the execution reaches the Call port of foo/2, the test part (which contains the pred(foo/2) condition only) succeeds, so the breakpoint is found applicable. However, the action part fails at the Call port. This has a side effect in zip mode, as the default flit command value is changed to proceed. In other modes the action variables are unaffected. The net result is that a procedure box is always built for foo/2, which means that the debugger will actually reach the Fail port of this predicate. When this happens, the action part succeeds, and executing the actions print,ask will cause the debugger to stop.

Note that we have to explicitly mention the print,ask actions here, because the action part is otherwise nonempty (contains the fail condition). It is only the empty or missing action part, which is replaced by the default [print,ask]. If you want to include a condition in the action part, you have to explicitly mention all action variable settings you need.

To make this simpler, the debugger handles breakpoint condition macros, which expand to other conditions. For example leash is a macro which expands to [print,ask]. Consequently, the last example can be simplified to:

| ?- spy(foo/2, -[fail,leash]).

Similarly, the macro unleash expands to [print,proceed], while hide to [silent,proceed].

We now briefly describe further possible settings to the action variables.

The mode variable can be assigned the values skip(Inv) and qskip(Inv), meaning skipping and quasi-skipping until a port is reached whose invocation number is less or equal to Inv. When the debugger arrives at this port it sets the mode variable to trace.

It may be surprising that skip(...) is a mode, rather than a command. This is because commands are executed and immediately forgotten, but skipping has a lasting effect: the program is to be run with no debugging until a specific point, without creating new procedure boxes, and ignoring the existing ones in the meantime.

Here is an example using the skip mode:

| ?- spy(foo/2,call-[print,proceed,inv(Inv),skip(Inv)]).

This breakpoint will be found applicable at Call ports of foo/2. It will print a trace message there and will skip over to the Exit or Fail port without stopping. Notice that the number of the current invocation is obtained in the action part, using the inv condition with a variable argument. A variant of this example follows:

| ?- spy(foo/2,-[silent,proceed,
                       (   call -> inv(Inv), skip(Inv)
                       ;   true
                       )]).

This spypoint makes foo/2 completely invisible in the output of the debugger: at all ports we silently proceed (i.e. display nothing and do not stop). Furthermore, at the Call port we perform a skip, so neither foo/2 itself, nor any predicate called within it will ever be shown by the debugger.

Notice the use of the true/0 test in the above conditional! This is a breakpoint test which always succeeds. The debugger also recognizes false as a test which always fails. Note that in breakpoint conditions fail and false are completely different, as the first one is an abbreviation of port(fail)!

The show variable has four additional value patterns. Setting it to display, write, or write_term(Options) will result in the debugged goal G being shown using display(G), writeq(G), or write_term(G, Options), respectively. The fourth pattern, Method-Sel, can be used for replacing the goal in the trace message by one of its subterms, the one pointed to by the selector Sel.

For example, the following spypoint instructs the debugger to stop at each port of foo/2, and to only display the first argument of foo/2 in the trace message, instead of the complete goal.

| ?- spy(foo/2, -[print-[1],ask]).
% Conditional spypoint for user:foo/2 added, BID=1
yes
| ?- foo(5,X).
 *      1      1 Call: ^1 5 ?

The command variable has several further value patterns. At a Call port this variable can be set to proceed(OldGoal,NewGoal). This instructs the debugger to first build a procedure box for the current goal, then to unify it with OldGoal and finally execute NewGoal in its place (cf. the u (unify) interactive debugger command). A variant of this setting, flit(OldGoal,NewGoal), has the same effect, but does not build a procedure box for OldGoal.

We now just briefly list further command values (for the details, see Action Variables). Setting command to exception(E) will raise an exception E, abort will abort the execution. The values retry(Inv), reexit(Inv), redo(Inv), fail(Inv) will cause the debugger to go back to an earlier Call, Exit, Redo, or Fail port with invocation number Inv (cf. the j (jump) interactive debugger command).

Finally, let us mention that the conditions show, command, and mode can also occur in the test part. In such cases they will read, rather than set, the action variables. For example:

| ?- spy(foo/2, mode(trace)-show(print-[1])).

This spypoint will be found applicable only in trace mode (and will cause the first argument of foo/2 to appear in the trace message). (The mode and show wrappers can be omitted in the above example, they are used only to help interpreting the breakpoint spec.)


Node:Advice-points, Next:, Previous:Breakpoint Actions, Up:Advanced Debugging

Advice-points

As mentioned earlier, there are two kinds of breakpoints: spypoints and advice-points. The main purpose of spypoints is to support interactive debugging. In contrast with this, advice-points can help you to perform non-interactive debugging activities. For example, the following advice-point will check a program invariant: whether the condition Y-X<3 always holds at exit from foo(X,Y).

| ?- add_breakpoint([goal(foo(X,Y)),advice]
                    -[exit,\+true(Y-X<3),trace], _).
% Conditional advice point for user:foo/2 added, BID=1
true ?
yes
% advice
| ?- foo(4, X).
X = 3 ?
yes
% advice
| ?- foo(9, X).
        3      3 Exit: foo(7,13) ? n
        2      2 Exit: foo(8,21) ?

The test part of the above breakpoint contains a goal test, and the advice condition, making it an advice-point. (You can also include the debugger condition in spypoint specs, although this is the default interpretation.)

The action part starts with the exit port condition. Because of this the rest of the action part is evaluated only at Exit ports. By placing the port condition in the action part, we ensure the creation of a procedure box at the Call port, as explained earlier.

The second condition in the action part, \+true(Y-X<3), checks if the invariant is violated. If this happens, the third condition sets the mode action variable to trace, switching on the interactive debugger.

Following the add_breakpoint/2 call the above example shows two top-level calls to foo/2. The invariant holds within the first goal, but is violated within the second. Notice that the advice mechanism works with the interactive debugger switched off.

You can ask the question, why do we need advice-points? The same task could be implemented using a spypoint. For example:

| ?- add_breakpoint(goal(foo(X,Y))-[exit,\+true(Y-X<3),leash], _).
% The debugger will first zip -- showing spypoints (zip)
% Conditional spypoint for user:foo/2 added, BID=1
true ?
yes
% zip
| ?- foo(4, X).
X = 3 ?
yes
% zip
| ?- foo(9, X).
 *      3      3 Exit: foo(7,13) ? z
 *      2      2 Exit: foo(8,21) ?

The main reason to have a separate advice mechanism is to be able to perform checks independently of the interactive debugging. With the second solution, if you happen to start some interactive debugging, you cannot be sure that the invariant is always checked. For example, no spypoints will be activated during a skip. In contrast with this, the advice mechanism is watching the program execution all the time, independently of the debugging mode.

Advice-points are handled in very much the same way as spypoints are. When arriving at a port, advice-point selection takes place first, followed by spypoint selection. This can be viewed as the debugger making two passes over the current breakpoints, considering advice-points only in the first pass, and spypoints only in the second.

In both passes the debugger tries to find a breakpoint which can be activated, checking the test and action parts, as described earlier. However, there are some differences between the two passes:

Having performed advice processing, the debugger inspects the command variable. The command values different from proceed and flit are called divertive, as they alter the normal flow of control (e.g. proceed(...,...)), or involve user interaction (ask). If the command value is divertive, then the prescribed action is performed immediately, without executing the spypoint selection process. Otherwise, if command = proceed, it is noted that the advice part requests the building of a procedure box. Next, the second, spypoint processing pass is carried out, and possible user interaction takes place, as described earlier. A procedure box is built if either the advice-point or the spypoint search requests this.

Finally, let us show another example, a generic advice point for collecting branch coverage information:

| ?- add_breakpoint([advice,goal(_:_),call,line(F,L)]
                    -[true(assert(line_reached(F,L))),flit], _).
% Generic advice point added, BID=1
true ?
yes
% advice,source_info
| ?- foo(4,X).
X = 3 ? ;
no
% advice,source_info
| ?- setof(X, line_reached(F,X), S).
F = '/home/bob/myprog.pl',
S = [31,33,34,35,36] ?

The advice-point will only be applicable at Call ports for which source information is available. It will then assert a fact with the file name and the line number. Finally, it will set the command variable to flit. This reflects the fact that the advice-point does not request the building of a procedure box.

It is important to note that the recording of the line numbers reached is performed independently of the interactive debugging.

Further examples of advice-points are available in library(debugger_examples).


Node:Built-in Predicates for Breakpoint Handling, Next:, Previous:Advice-points, Up:Advanced Debugging

Built-in Predicates for Breakpoint Handling

For the last advice-point example to be practical, it should be improved to assert only line numbers not recorded so far. For this you will write a Prolog predicate for the conditional assertion of file/line information, assert_line_reached(File,Line). The breakpoint spec will then look as follows:

| ?- add_breakpoint([advice,goal(_:_),call,line(F,L)]
                      -[true(assert_line_reached(F,L)),flit], _).

The above breakpoint spec can be simplified by moving the line(F,L) query into the Prolog goal called within the true/1 condition. To achieve this, the built-in predicate execution_state/1 can be used. This predicate takes a simple or a composite breakpoint condition as its argument and evaluates it, as if in the test part of a breakpoint spec. The predicate will succeed iff the breakpoint condition evaluates successfully. Thus execution_state/1 allows you to access debugging information from within Prolog code. For example, you can write a Prolog predicate, assert_line_reached/0, which queries the debugger for the current line information and then processes the line number:

assert_line_reached :-
        (   execution_state(line(F,L)) -> assert_line_reached(F,L).
        ;   true
        ).

| ?- add_breakpoint([advice,goal(_:_),call]
                      -[true(assert_line_reached),flit], _).

Note that assert_line_reached/0 succeeds even if no source information is available. This is to avoid the creation of procedure boxes (if the action part fails, a procedure box is created).

Arbitrary tests can be used in execution_state/1, if it is called from within a true condition. It can also be called from outside the debugger, but then only a subset of conditions is available. Furthermore, the built-in predicate execution_state/2 allows accessing information from past debugger states (see Accessing Past Debugger States.

The built-in predicates remove_breakpoints(BIDs), disable_breakpoints(BIDs) and enable_breakpoints(BIDs) serve for removing, disabling and enabling the given breakpoints. Here BIDs can be a single breakpoint identifier, a list of these, or one of the atoms all, advice, debugger.

We now show an application of remove_breakpoints/1 for implementing one-off breakpoints, i.e. breakpoints which are removed when first activated.

For this we need to get hold of the currently selected breakpoint identifier. The bid(BID) condition serves for this purpose: it unifies its argument with the identifier of the breakpoint being processed. The following is an example of a one-off breakpoint.

| ?- spy(foo/2, -[bid(BID),true(remove_breakpoints(BID)),leash]).
% Conditional spypoint for user:foo/2 added, BID=1
true ?
yes
% zip
| ?- foo(2, X).
% Conditional spypoint for user:foo/2, BID=1, removed (last)
        1      1 Call: foo(2,_402) ? z
X = 1 ?

The action part of the above breakpoint calls the bid test to obtain the breakpoint identifier. It then uses this number as the argument to the built-in predicate remove_breakpoints, which removes the activated breakpoint.

The built-in predicate current_breakpoint(Spec, BID, Status, Kind) enumerates all breakpoints present in the debugger. Here Spec is the breakpoint spec of the breakpoint with identifier BID, Status is on for enabled breakpoints and off for disabled ones, while Kind is one of plain, conditional or generic. The Spec returned by current_breakpoint/4 is not necessarily the same as the one given in add_breakpoint/2, as the breakpoint spec is subject to some normalization, see Breakpoint Predicates.


Node:Accessing Past Debugger States, Next:, Previous:Built-in Predicates for Breakpoint Handling, Up:Advanced Debugging

Accessing Past Debugger States

The debugger collects control flow information about the goals being executed, more precisely about those goals, for which a procedure box is built. This collection of information, the backtrace, includes the invocations that were called but not exited yet, as well as those that exited nondeterministically. For each invocation, the main data items present in the backtrace are the following: the goal, the module, the invocation number, the depth and the source information, if any.

Furthermore, you can enter a new break level from within the debugger, so there can be multiple backtraces, one for each active break level.

+

You can access all the information collected by the debugger using the built-in predicate execution_state(Focus, Tests). Here Focus is a ground term specifying which break level and which invocation to access. It can be one of the following:

Note that the top-level counts as break level 0, while the invocations are numbered from 1 upwards.

The second argument of execution_state/2, Tests, is a simple or composite breakpoint condition. Most simple tests can appear inside Tests, with the exception of the port, bid, advice, debugger tests and the action variable queries. The tests appearing in the second argument will be interpreted in the context of the specified past debugger state. Specifically, if a true/1 condition is used, then any execution_state/1 queries appearing in it will be evaluated in the past context.

To illustrate the use of execution_state/2, we now define a predicate last_call_arg(ArgNo, Arg), which is to be called from within a break, and which will look at the last debugged goal of the previous break level, and return in Arg the ArgNoth argument of this goal.

last_call_arg(ArgNo, Arg) :-
        execution_state(break_level(BL1)),
        BL is BL1-1,
        execution_state(break_level(BL), goal(Goal)),
        arg(ArgNo, Goal, Arg).

We see two occurrences of the term break_level(...) in the above example. Although these look very similar, they have different roles. The first one, in execution_state/1, is a breakpoint test, which unifies the current break level with its argument. Here it is used to obtain the current break level and store it in BL1. The second use of break_level(...), in the first argument of execution_state/2, is a focus condition, whose argument has to be instantiated, and which prescribes the break level to focus on. Here we use it to obtain the goal of the current invocation of the previous break level.

Note that the goal retrieved from the backtrace is always in its latest instantiation state. For example, it not possible to get hold of the goal instantiation at the Call port, if the invocation in question is at the Exit port.

Here is an example run, showing how last_call_arg/2 can be used:

        5      2 Call: _937 is 8-2 ? b
% Break level 1
% 1
| ?- last_call_arg(2, A).
A = 8-2 ?

There are some further breakpoint tests which are primarily used in looking at past execution states.

The test max_inv(MaxInv) returns the maximal invocation number within the current (or selected) break level. The test last_port(LastPort) can be used for obtaining approximate port information for invocations in the backtrace: it unifies LastPort port with exit(nondet) if the invocation has exited, and with call otherwise. The latter piece of information is inaccurate: all we know is that the control is still within the invocation in question, but the last port passed through may have been e.g. the Redo port.

The following sample predicate lists those goals in the backtrace, together with their invocation numbers, which have exited nondeterministically. (Predicate between(N, M, I) enumerates all integers such that N =< I =< M.)

nondet_goals :-
     execution_state(max_inv(Max)),
     between(1, Max, Inv),
     execution_state(inv(Inv), [last_port(exit(nondet)),goal(G)]),
     format('~t~d~6| ~p\n', [Inv,G]),
     fail.
nondet_goals.

?*     27      2 Exit: foo(2,1) ? @
| :- nondet_goals.
     6 foo(3,2)
    11 foo(2,1)
    16 foo(1,1)
    19 foo(0,0)
    23 foo(1,1)
    32 foo(1,1)
    35 foo(0,0)
?*     27      2 Exit: foo(2,1) ?

Note that similar output can be obtained by entering a new break level and calling nondet_goals from within an execution_state/2:

% 1
| ?- execution_state(break_level(0), true(nondet_goals)).

The remaining two breakpoint tests allow you to find parent and ancestor invocations in the backtrace. The test parent_inv(Inv) unifies Inv with the invocation number of the youngest ancestor present in the backtrace, called debugger parent for short. Similarly, the test ancestor(AncGoal,Inv) looks for the youngest ancestor in the backtrace which is unifiable with AncGoal, and returns its invocation number in Inv.

Assume you would like to stop at all invocations of foo/2 which are within bar/1. The following two breakpoints achieve this effect:

| ?- spy(bar/1, advice), spy(foo/2, ancestor(bar(_),_)).
% Plain advice point for user:bar/1 added, BID=3
% Conditional spypoint for user:foo/2 added, BID=4

We added an advice-point for bar/1 to ensure that all calls to it will have procedure boxes built, and so become part of the backtrace. Advice-points are a better choice than spypoints for this purpose, as ?- spy(bar/1, -proceed) will unleash bar/1 when run in trace mode. Note that it is perfectly all right to create an advice-point using spy/2, although this is a bit of terminological inconsistency.

Further examples of accessing past debugger states can be found in library(debugger_examples).


Node:Storing User Information in the Backtrace, Next:, Previous:Accessing Past Debugger States, Up:Advanced Debugging

Storing User Information in the Backtrace

The debugger allows the user to store some private information in the backtrace, namely it allocates a Prolog variable in each break level and in each invocation. The breakpoint test private(Priv) unifies Priv with the private information associated with the break level, while the test goal_private(GPriv) unifies GPriv with the Prolog variable stored in the invocation.

Both variables are initially unbound, and behave as if they were passed around the program being debugged in additional arguments. This implies that any variable assignments done within these variables are undone on backtracking.

The private condition practically gives you access to a Prolog variable shared by all invocations of a break level. This makes it possible to remember a term and look at it later, in a possibly more instantiated form, as shown by the following example.

memory(Term) :-
        execution_state(private(P)),
        memberchk(myterm(Term), P).

| ?- trace, append([1,2,3,4], [5,6], L).
        1      1 Call: append([1,2,3,4],[5,6],_514) ? @
| :- append(_,_,L)^memory(L).
        1      1 Call: append([1,2,3,4],[5,6],_514) ? c
        2      2 Call: append([2,3,4],[5,6],_2064) ? c
        3      3 Call: append([3,4],[5,6],_2422) ? c
        4      4 Call: append([4],[5,6],_2780) ? @
| :- memory(L), write(L), nl.
[1,2,3|_2780]
        4      4 Call: append([4],[5,6],_2780) ?

The predicate memory/1 receives the term to be remembered in its argument. It gets hold of the private field associated with the break level in variable P, and calls memberchk/2 (see Lists), with the term to be remembered, wrapped in myterm, as the list element, and the private field, as the list. Thus the latter, initially unbound variable, is used as an open-ended list. For example, when memory/1 is called for the first time, the private field gets instantiated to [myterm(Term)|_]. If later you call memory/1 with an uninstantiated argument, it will retrieve the term remembered earlier and unify it with the argument.

The above trace excerpt shows how this utility predicate can be used to remember an interesting Prolog term. Within invocation number 1 we call memory/1 with the third, output argument of append/3, using the @ command (see Debug Commands). A few tracing steps later, we retrieve the term remembered and print it, showing its current instantiation. Being able to access the instantiation status of some terms of interest can be very useful in debugging. In library(debugger_examples) we describe new debugger commands for naming Prolog variables and providing name-based access to these variables, based on the above technique.

In the above example we could have avoided the use of memberchk/2 by simply storing the term to be remembered in the private field itself (memory(Term) :- execution_state(private(Term)).). But this would make the private field unusable for other purposes. For example, the finite domain constraint debugger (see FDBG) would stop working, as it relies on the private fields.

There is only a single private variable of both kinds within the given scope. Therefore the convention of using an open list for storing information in private fields, as shown in the above example, is very much recommended. The different users of the private field are distinguished by the wrapper they use (e.g. myterm/1 above, fdbg/1 for the constraint debugger, etc.). Future SICStus Prolog releases may enforce this convention by providing appropriate breakpoint tests.

We now present an example of using the goal private field. Earlier we have shown a spypoint definition which made a predicate invisible in the sense that its ports are silently passed through and it is automatically skipped over. However, with that earlier solution, execution always continues in trace mode after skipping. We now improve the spypoint definition: the mode in which the Call port was reached is remembered in the goal private field, and the mode action variable is set to this value at Exit ports.

mode_memory(Mode) :-
        execution_state(goal_private(GP)),
        memberchk(mymode(Mode), GP).

| ?- spy(foo/2, mode(M),
                -[silent,proceed,
                  true(mode_memory(MM)),
                       (   call -> true(MM=M), inv(Inv), skip(Inv)
                       ;   exit -> mode(MM)
                       ;   true
                       )]).

Above we first define an auxiliary predicate mode_memory/1, which uses the open list convention for storing information in the goal private field, applying the mymode/1 wrapper. This predicate is used in the action part of the spypoint, unifying the mode memory with the MM variable. We then branch in the action part: at Call ports the uninstantiated MM is unified with the current mode. At Exit ports MM holds the mode saved at the Call port, so by issuing the mode(MM) action, this mode is re-activated. At all other ports we just silently proceed without changing the debugger mode.


Node:Hooks Related to Breakpoints, Next:, Previous:Storing User Information in the Backtrace, Up:Advanced Debugging

Hooks Related to Breakpoints

There are two hooks related to breakpoints.

The hook breakpoint_expansion(Macro,Body) makes it possible for the user to extend the set of allowed conditions. If this hook is defined, it is called with each simple test or action in the Macro argument. If the hook succeeds, then the term returned in the Body argument is substituted for the original test or action. Note that Body can not span both the test and the action part, i.e. it cannot contain the - /2 operator. The whole Body will be interpreted either as a test or as an action, depending on the context of the original condition.

We now give a few examples for breakpoint macros. These culminate in the last example which actually implements the condition making a predicate invisible, a reformulation of the spypoint example of the previous subsection.

:- multifile user:breakpoint_expansion/2.
user:breakpoint_expansion(
            skip, [inv(I),skip(I)]).

user:breakpoint_expansion(
            gpriv(Value),
            [goal_private(GP),true(memberchk(Value,GP))]).

user:breakpoint_expansion(
            get_mode(M), true(execution_state(mode(M)))).

user:breakpoint_expansion(
            invisible,
            [silent,proceed,
                (   call -> get_mode(M), gpriv(mymode(M)), skip
                ;   exit -> gpriv(mymode(MM)), mode(MM)
                ;   true
                )]).

| ?- spy(foo/2, -invisible).

We first define the skip macro, instructing the debugger to skip the current invocation. This macro is only meaningful in the action part.

The second clause defines the gpriv/2 macro, a generalization of the earlier mode_memory/1 predicate. For example, gpriv(mymode(M)) expands to goal_private(GP),true(memberchk(mymode(M),GP)). This embodies the convention of using open-ended lists for the goal private field.

The third clause defines the get_mode/1 macro for accessing the current mode from within the action part. It uses the trick of calling execution_state/1, which always interprets its argument in the test part context. This is needed because of the restriction that a macro cannot span both the test and the action part.

Finally, the last clause implements the action macro invisible/0, which makes the predicate in question completely hidden. The last line shows how this macro can be used to make foo/2 invisible.

Although macros are very convenient, they are executed less efficiently than plain Prolog code. Therefore, if efficiency is of concern, the following variant of invisible should be used.

user:breakpoint_expansion(invisible,
        [true(invisible(NewMode)),mode(NewMode),proceed,silent]).

invisible(NewMode) :-
        execution_state([mode(M),port(P),inv(Inv),goal_private(GP)]),
        memberchk(mymode(MM), GP),
        (   P == call -> MM = M, NewMode = skip(Inv)
        ;   P = exit(_) -> NewMode = MM
        ;   NewMode = M
        ).

The second hook related to breakpoints is debugger_command_hook(DCommand, Actions). This hook serves for customizing the behavior of the interactive debugger, i.e. for introducing new interactive debugger commands. The hook is called for each debugger command read in by the debugger. DCommand contains the abstract format of the debugger command read in, as returned by the query facility (see Query Processing). If the hook succeeds, it should return in Actions an action part to be evaluated as the result of the command.

If you want to redefine an existing debugger command, you should study library('SU_messages') to learn the abstract format of this command, as returned by the query facility. If you want to add a new command, it suffices to know that unrecognized debugger commands are returned as unknown(Line,Warning). Here, Line is the list of character codes typed in, with any leading layout removed, and Warning is a warning message.

The following example defines the S interactive debugger command to behave as skip at Call and Redo ports, and as creep otherwise:

:- multifile user:debugger_command_hook/2.
user:debugger_command_hook(unknown([0'S|_],_), Actions) :-
        execution_state([port(P),inv(I)]),
        Actions = [Mode,proceed,silent],
        (   P = call -> Mode = skip(I)
        ;   P = redo -> Mode = skip(I)
        ;   Mode = trace
        ).

Note that the silent action is needed above; otherwise, the trace message will be printed a second time, before continuing the execution.

library(debugger_examples) contains some of the above hooks, as well as several others.


Node:Programming Breakpoints, Previous:Hooks Related to Breakpoints, Up:Advanced Debugging

Programming Breakpoints

We will show two examples using the advanced features of the debugger.

The first example defines a hide_exit(Pred) predicate, which will hide the Exit port for Pred (i.e. it will silently proceed), provided the current goal was already ground at the Call port, and nothing was traced inside the given invocation. The hide_exit(Pred) creates two spypoints for predicate Pred:

:- meta_predicate hide_exit(:).
hide_exit(Pred) :-
        add_breakpoint([pred(Pred),call]-
                         true(save_groundness), _),
        add_breakpoint([pred(Pred),exit,true(hide_exit)]-hide, _).

The first spypoint is applicable at the Call port, and it calls save_groundness to check if the given invocation was ground, and if so, it stores a term hide_exit(ground) in the goal_private attribute of the invocation.

save_groundness :-
        execution_state([goal(_:G),goal_private(Priv)]),
        ground(G), !, memberchk(hide_exit(ground), Priv).
save_groundness.

The second spypoint created by hide_exit/1 is applicable at the Exit port and it checks whether the hide_exit/0 condition is true. If so, it issues a hide action, which is a breakpoint macro expanding to [silent,proceed].

hide_exit :-
        execution_state([inv(I),max_inv(I),goal_private(Priv)]),
        memberchk(hide_exit(Ground), Priv), Ground == ground.

Here, hide_exit encapsulates the tests that the invocation number is the same as the last invocation number used (max_inv), and that the goal_private attribute of the invocation is identical to ground. The first test ensures that nothing was traced inside the current invocation.

If we load the above code, as well as the small example below, then the following interaction can take place. Note that the hide_exit is called with the _:_ argument, resulting in generic spypoints being created.

| ?- [user].
| cnt(0) :- !.
| cnt(N) :-
|       N > 0, N1 is N-1, cnt(N1).
|
% consulted user in module user, 0 msec 424 bytes

yes
| ?- hide_exit(_:_), trace, cnt(1).
% The debugger will first zip -- showing spypoints (zip)
% Generic spypoint added, BID=1
% Generic spypoint added, BID=2
% The debugger will first creep -- showing everything (trace)
 #      1      1 Call: cnt(1) ? c
 #      2      2 Call: 1>0 ? c
 #      3      2 Call: _2019 is 1-1 ? c
        3      2 Exit: 0 is 1-1 ? c
 #      4      2 Call: cnt(0) ? c
        1      1 Exit: cnt(1) ? c

yes
% trace
| ?-

Invocation 1 is ground, its Exit port is not hidden, because further goals were traced inside it. On the other hand, Exit ports of ground invocations 2 and 4 are hidden.

Our second example defines a predicate call_backtrace(Goal, BTrace), which will execute Goal and build a backtrace showing the successful invocations executed during the solution of Goal.

The advantages of such a special backtrace over the one incorporated in the debugger are the following:

The call_backtrace/2 predicate is based on the advice facility. It uses the variable accessible via the private(_) condition to store a mutable holding the backtrace (see Meta Logic). Outside the call_backtrace predicate the mutable will have the value off.

The example is a module-file, so that internal invocations can be identified by the module-name. We load the lists library, because memberchk/2 will be used in the handling of the private field.

:- module(backtrace, [call_backtrace/2]).
:- use_module(library(lists)).

:- meta_predicate call_backtrace(:, ?).
call_backtrace(Goal, BTrace) :-
        Spec = [goal(M:G),advice,port(call)]
               -[true(backtrace:store_goal(M,G)),command(flit)],
        (   current_breakpoint(Spec, _, on, _) -> B = []
        ;   add_breakpoint(Spec, B)
        ),
        call_cleanup(call_backtrace1(Goal, BTrace),
                     remove_breakpoints(B)).

call_backtrace(Goal, BTrace) is a meta-predicate, which first sets up an appropriate advice-point for building the backtrace. The advice-point will be activated at each Call port, will call the store_goal/2 predicate with arguments containing the module and the goal in question. Note that the advice-point will not build a procedure box (cf. the flit command in the action part).

The advice-point will be added just once: any further (recursive) calls to call_backtrace/2 will notice the existence of the breakpoint and will skip the add_breakpoint/2 call. Note that the breakpoint spec Spec is in normalized form (e.g. the first two conditions are goal and advice), so that Spec is good both for checking the presence of a breakpoint with the given spec in current_breakpoint/4, and for creating a new breakpoint in add_breakpoint/2.

Having ensured the appropriate advice-point exists, call_backtrace/2 calls call_backtrace1/2 with a cleanup operation which removes the breakpoint added.

:- meta_predicate call_backtrace1(:, ?).
call_backtrace1(Goal, BTrace) :-
        execution_state(private(Priv)),
        memberchk(backtrace_mutable(Mut), Priv),
        (   is_mutable(Mut) -> get_mutable(Old, Mut),
            update_mutable([], Mut)
        ;   create_mutable([], Mut), Old = off
        ),
        call(Goal),
        get_mutable(BTrace, Mut), update_mutable(Old, Mut).

The predicate call_backtrace1/2 retrieves the private field of the execution state and uses it to store a mutable, wrapped in backtrace_mutable. When first called within a top-level the mutable is created with the value []. In later calls the mutable is re-initialized to []. Having set up the mutable, Goal is called. In the course of the execution of the Goal the debugger will accumulate the backtrace in the mutable. Finally, the mutable is read, its value is returned in BTrace, and it is restored to its old value (or off).

store_goal(M, G) :-
        M \== backtrace,
        G \= call(_),
        execution_state(private(Priv)),
        memberchk(backtrace_mutable(Mut), Priv),
        is_mutable(Mut),
        get_mutable(BTrace, Mut),
        BTrace \== off, !,
        update_mutable([M:G|BTrace], Mut).
store_goal(_, _).

store_goal/2 is the predicate called by the advice-point, with the module and the goal as arguments. We first ensure that calls from within the backtrace module and those of call/1 get ignored. Next, the module qualified goal term is prepended to the mutable value retrieved from the private field, provided the mutable exists and its value is not off.

Below is an example run, using a small program:

| ?- [user].
| cnt(N):- N =< 0, !.
| cnt(N) :-
     N > 0, N1 is N-1, cnt(N1).
| {consulted user in module user, 0 msec 224 bytes}

yes
| ?- call_backtrace(cnt(1), B).
% Generic advice point added, BID=1
% Generic advice point, BID=1, removed (last)

B = [user:(0=<0),user:cnt(0),user:(0 is 1-1),user:(1>0),user:cnt(1)] ?

yes
| ?-

Note that the backtrace produced by call_backtrace/2 can not contain any information regarding failed branches. For example, the very first invocation within the above execution, 1 =< 0, is first put on the backtrace at its Call port, but this is immediately undone because the goal fails. If you would like to build a backtrace that preserves failed branches, you have to use side-effects, e.g. dynamic predicates.

Further examples of complex breakpoint handling are contained in library(debugger_examples).


Node:Breakpoint Predicates, Next:, Previous:Advanced Debugging, Up:Debug Intro

Breakpoint Handling Predicates

This section describes the advanced built-in predicates for creating and removing breakpoints.

add_breakpoint(:Spec, ?BID)

Adds a breakpoint with a spec Spec, the breakpoint identifier assigned is unified with BID. Spec is one of the following:

Tests-Actions
Tests
standing for Tests-[]
-Actions
standing for []-Actions

Here, both Tests and Actions are either a simple Condition, see Breakpoint Conditions, or a composite Condition. Conditions can be composed by forming lists, or by using the ,, ;, ->, and \+ operators, with the usual meaning of conjunction, disjunction, if-then-else and negation. A list of conditions is equivalent to a conjunction of the same conditions ([A|B] is treated as (A,B)).

The add_breakpoint/2 predicate first normalizes the Conditions, before adding the breakpoint. In both the test and action parts the outermost conjunctions are transformed into lists. The goal and pred conditions are then extracted from the outermost list of the test part and their consistency is checked. Subsequently, a goal condition is inserted as the first element of the tests list, encapsulating the possibly implicit module qualification, all extracted goal conditions, and those extracted pred conditions which can be transformed to a goal condition. Furthermore the debugger condition is removed, and the advice condition is moved to the second element of the tests list. Finally, a pred condition is inserted in front of the remaining tests, in the rare cases when it can not be made part of the preceding goal test. The rest of the test part and the action part is the same as supplied, with the extracted conditions removed.

There can only be a single plain spypoint for each predicate. If a plain spypoint is added, and there is already a plain spypoint for the given predicate, then:

  1. the old spypoint is deleted and a new added as the most recent breakpoint, if this change affects the breakpoint selection mechanism.
  2. otherwise, the old spypoint is kept and enabled if needed.

spy(:PredSpec, :Spec)

Adds a conditional spypoint with a breakpoint spec formed by adding pred(Pred) to the test part of Spec, for each predicate Pred designated by the generalized predicate spec PredSpec.

current_breakpoint(:Spec, ?BID, ?Status, ?Kind)

There is a breakpoint with breakpoint spec Spec, identifier BID, status Status and kind Kind. Status is one of on or off, referring to enabled and disabled breakpoints. Kind is one of plain, conditional or generic. current_breakpoint/4 enumerates all breakpoints on backtracking.

The Spec as returned by current_breakpoint/4 may not be exactly the same as supplied at the creation of the breakpoint, because of the transformations done at creation, see the description of add_breakpoint/2 above.

remove_breakpoints(+BIDs)
disable_breakpoints(+BIDs)
enable_breakpoints(+BIDs)

Removes, disables or enables the breakpoints with identifiers specified by BIDs. BIDs can be a number, a list of numbers or one of the atoms: all, debugger, advice. The atoms specify all breakpoints, debugger type breakpoints and advice type breakpoints, respectively.

execution_state(:Tests)

Tests are satisfied in the current state of the execution. Arbitrary tests can be used in this predicate, if it is called from inside the debugger, i.e. from within a true condition. Otherwise only those tests can be used, which query the data stored in the backtrace. An exception is raised if the latter condition is violated, i.e. a non-backtraced test (see Breakpoint Conditions) occurs in a call of execution_state/1 from outside the debugger.

execution_state(+FocusConditions, :Tests)

Tests are satisfied in the state of the execution pointed to by FocusConditions (see Past States). An exception is raised if there is a non-backtraced test among Tests.

Note that the built-in predicate arguments holding a breakpoint spec (Spec or Tests above) are subject to module name expansion. The first argument within simple tests goal(_), pred(_), ancestor(_,_), and true(_) will inherit the module name from the (module name expanded) breakpoint spec argument, in the absence of explicit module qualification within the simple condition.

The following hook predicate can be used to customize the behavior of the interactive debugger.

debugger_command_hook(+DCommand,?Actions) [Hook]
user:debugger_command_hook(+DCommand,?Actions)

This predicate is called for each debugger command SICStus Prolog reads in. The first argument is the abstract format of the debugger command DCommand, as returned by the query facility (see Query Processing). If it succeeds, Actions is taken as the list of actions (see Action Conditions) to be done for the given debugger command. If it fails, the debugger command is interpreted in the standard way.

Note that if a line typed in in response to the debugger prompt can not be parsed as a debugger command, debugger_command_hook/2 is called with the term unknown(Line,Warning). Here, Line is the list of character codes typed in, with any leading layout removed, and Warning is a warning message. This allows the user to define new debugger commands, see Hooks Related to Breakpoints for an example.


Node:Breakpoint Processing, Next:, Previous:Breakpoint Predicates, Up:Debug Intro

The Processing of Breakpoints

This section describes in detail how the debugger handles the breakpoints. For the purpose of this section disabled breakpoints are not taken into account: whenever we refer to the existence of some breakpoint(s), we always mean the existence of enabled breakpoint(s).

The Prolog engine can be in one of the following three states with respect to the debugger:

no debugging
if there are no advice-points and the debugger is either switched off, or doing a skip;
full debugging
if the debugger is in trace or debug mode (creeping or leaping), or there are any generic breakpoints;
selective debugging
in all other cases.

In the selective debugging state only those predicate invocations are examined, for which there exists a specific breakpoint. In the full debugging state all invocations are examined, except those calling a non-exported predicate of a hidden module (but even these will be examined, if there is a specific breakpoint for them). In the no debugging state the debugger is not entered at predicate invocations.

Now we describe what the debugger does when examining an invocation of a predicate, i.e. executing its Call port. The debugger activities can be divided into three stages: advice-point processing, spypoint processing and interaction with the user. The last stage may be repeated several times before program execution continues.

The first two stages are similar, as they both search for an applicable breakpoint (spypoint or advice-point). This breakpoint search is carried out as follows. The debugger considers all breakpoints of the given type, most recent first. The first breakpoint, for which the evaluation of the test part succeeds is selected. Next, the action part of the selected breakpoint is evaluated, normally setting some debugger action variables. If the action part succeeds, then the breakpoint search is said to complete successfully. If the action part fails, then the breakpoint search is still considered successful. As a side effect, however, it is ensured that a procedure box is built (if the command action variable is flit, it is changed to proceed). If none of the test parts evaluated successfully then the search is said to have failed.

Now let us look at the details of the first stage, advice-point processing. This stage is executed only if there are any advice-points set. First, the debugger action variables are initialized: mode is set to the current debugger mode, command to proceed and show to silent. Next, advice-point search takes place. If this fails, command is set to flit, otherwise its value is unchanged.

Having completed the advice-point search, the command variable is examined. If its value is divertive, i.e. different from proceed and flit, then the spypoint search stage is omitted, and the debugger continues with the third stage. Otherwise, it is noted if advice-point processing has requested the building of a procedure box (i.e. command = proceed), and the debugger continues with the second stage.

The second stage is spypoint processing. This stage is skipped if the debugger is switched off or doing a skip (mode is off or skip(_)). First the the show and command variables are re-assigned, based on the hiddenness of the predicate being invoked, the debugger mode and the leashing status of the port. If the predicate is both defined in, and called from a hidden module, then their values will be silent and flit. An example of this is when a built-in predicate is called from a hidden module, e.g. from a library. Otherwise, in trace mode, their values are print and ask for leashed ports, and print and proceed for unleashed ports. In debug mode, the variables are set to silent and proceed, while in zip mode to silent and flit (Breakpoint Actions contains a tabulated listing of these initialization values).

Having initialized the debugger action variables, spypoint search is performed. If an empty action part has been selected in a successful search, then show and command are set to print and ask. The failure of the search is ignored.

The third stage is the interactive part. First, the goal in question is displayed according to the value of show. Next, the value of command is checked: if it is other than ask, then the interactive stage ends. Otherwise, (it is ask), the variable show is re-initialized to print, or to print-Sel, if its value was of form Method-Sel. Next, the debugger prompts the user for a command which is interpreted either in the standard way, or through user:debugger_command_hook/2. In both cases the debugger action variables are modified as requested, and the interactive part is repeated.

After the debugger went through all the three stages, it decides whether to build a procedure box. This will happen if either the advice-point stage or the other two stages require it. The latter is decided by checking the command variable: if that is flit or flit(Old,New), then no procedure box is required by the spypoint part. If the advice-point does require the building of a procedure box, then the above command values are replaced by proceed and proceed(Old,New), respectively.

At the end of the process the value of mode will be the new debugging mode, and command will determine what the debugger will do; see Action Variables.

A similar three-stage process is carried out when the debugger arrives at a non-Call port of a predicate. The only difference is that the building of a procedure box is not considered (flit is equivalent to proceed), and the hiddenness of the predicate is not taken into account.

While the Prolog system is executing the above three-stage process for any of the ports, it is said to be inside the debugger. This is relevant, because some of the conditions can only be evaluated in this context.


Node:Breakpoint Conditions, Next:, Previous:Breakpoint Processing, Up:Debug Intro

Breakpoint Conditions

This section describes the format of simple breakpoint conditions. We first list the tests that can be used to enquire the state of execution. We then proceed to describe the conditions usable in the actions part and the options for focusing on past execution states. Finally, we describe condition macros and the valid values for the debugger action variables.

We distinguish between two kinds of tests, based on whether they refer to information stored in the backtrace or not. The latter category, the non-backtraced tests, contains the conditions related to the current port (port, bid, mode, show, command) and the breakpoint type selection conditions (advice and debug). All remaining tests refer to information stored in the backtrace.

Non-backtraced tests will raise an exception, if they appear in calls to execution_state/1 from outside the debugger, or in queries about past execution state, in execution_state/2.

Backtraced tests are allowed both inside and outside the debugger. However such tests can fail if the given query is not meaningful in the given context, e.g. if execution_state(goal(G)) is queried before any breakpoints were encountered.

Note that if a test is used in the second argument of execution_state/2, then the term current, in the following descriptions, should be interpreted as referring to the execution state focused on.


Node:Goal Tests, Next:, Previous:Breakpoint Conditions, Up:Breakpoint Conditions

Tests Related to the Current Goal

The following tests give access to basic information about the current invocation.

inv(Inv)
The invocation number of the current goal is Inv.
depth(Depth)
The current execution depth is Depth.
goal(MGoal)
The module name expanded MGoal template matches the current goal. The unification required for matching is carried out.
pred(MFunc)
The module name expanded MFunc template matches the functor (M:F/N) of the current goal. The unification required for matching is carried out.
module(Module)
The current goal is invoked from module Module. For compiled calls to built-in predicates Module will always be prolog.
goal_private(GoalPriv)
The private information associated with the current goal is GoalPriv. This is initialized to an unbound variable at the Call port. It is strongly recommended that GoalPriv is used as an open ended list, see Storing User Information in the Backtrace.
last_port(LastPort)
LastPort is the last completed port of the invocation present on the backtrace. Practically, this is only useful when looking at past execution states. LastPort is exit(nondet) if the invocation has been exited, and call otherwise.
parent_inv(Inv)
The invocation number of the debugger-parent of the current goal is Inv.
ancestor(AncGoal,Inv)
The youngest debugger-ancestor of the current goal, which matches the module name expanded AncGoal template, is at invocation number Inv. The unification required for matching is carried out.

Notes:

The debugger-parent of a goal is the youngest ancestor of the goal present on the backtrace. This will differ from the ordinary parent if not all goals are traced, e.g. if the goal in question is reached in zip mode. A debugger-ancestor of a goal is any of its ancestors on the backtrace.

In the goal and ancestor tests above, there is a given module qualified goal template, say ModT:GoalT, and it is matched against a concrete goal term Mod:Goal in the execution state. This matching is carried out as follows:

  1. For the match to succeed, Goal and GoalT have to be unifiable and are unified.
  2. Mod and ModT are either unifiable (and are unified), or name such modules in which Goal has the same meaning, i.e. either one of Mod:Goal and ModT:Goal is an exported variant of the other, or both are imported from the same module.

The above matching rules also apply for predicate functors, in the pred condition.


Node:Source Tests, Next:, Previous:Goal Tests, Up:Breakpoint Conditions

Tests Related to Source Information

These tests provide access to source related information. The file and line tests will fail if no source information is present. The parent_clause and parent_pred tests are available for interpreted code only.

file(File)
The current goal is invoked from a file whose absolute name is File.
line(File,Line)
The current goal is invoked from line Line, from within a file whose absolute name is File.
line(Line)
The current goal is invoked from line Line.
parent_clause(Cl)
The current goal is invoked from clause Cl.
parent_clause(Cl,Sel)
The current goal is invoked from clause Cl and within its body it is pointed to by the subterm selector Sel.
parent_clause(Cl,Sel,I)
The current goal is invoked from clause Cl, it is pointed to by the subterm selector Sel within its body, and it is the Ith goal within it. The goals in the body are counted following their textual occurrence.
parent_pred(Pred)
The current goal is invoked from predicate Pred.
parent_pred(Pred,N)
The current goal is invoked from predicate Pred, clause number N.


Node:Port Tests, Next:, Previous:Source Tests, Up:Breakpoint Conditions

Tests Related to the Current Port

These tests can only be used inside the debugger and only when focused on the current invocation. If they appear in execution_state/2 or in execution_state/1 called outside the debugger, an exception will be raised.

The notion of port in breakpoint handling is more general than outlined earlier in Procedure Box. Here, the following terms are used to describe a port:

call, exit(nondet), exit(det), redo, fail,
exception(Exception), block, unblock

Furthermore, the atoms exit and exception can be used in the port condition (see below), to denote any of the two exit ports and an arbitrary exception port, respectively.

port(Port)
The current execution port matches Port in the following sense: either Port and the current port unify, or Port is the functor of the current port (e.g. port(exit) holds for both exit(det) and exit(nondet) ports).

As explained earlier, the port condition for a non Call port is best placed in the action part. This is because the failure of the action part will cause the debugger to pass through the Call port silently, and to build a procedure box, even in zip mode. The following idiom is suggested for creating breakpoints at non Call ports:

add_breakpoint(Tests-[port(Port),Actions], BID).

bid(BID)
The breakpoint being examined has a breakpoint identifier BID. (BID = none if no breakpoint was selected.)
mode(Mode)
Mode is the value of the mode variable, which reflects the current debugger mode.
command(Command)
Command is the value of the command variable, which is the command to be executed by default, if the breakpoint is selected.
show(Show)
Show is the value of the show variable, i.e. the default show method (the method for displaying the goal in the trace message).

The last three of the above tests access the debugger action variables. For example, the condition mode(trace), if it occurs in the tests, checks if the current debugger mode is trace. On the other hand, if the same term occurs within the action part, it sets the debugger mode to trace.

For the port, mode, command and show conditions, the condition can be replaced by its argument, if that is not a variable. For example the condition call can be used instead of port(call). Conditions matching the terms listed above as valid port values will be converted to a port condition. Similarly, any valid value for the three debugger action variables is converted to an appropriate condition. These valid values are described in Action Variables.


Node:Break Tests, Next:, Previous:Port Tests, Up:Breakpoint Conditions

Tests Related to the Break Level

These tests can be used both inside and outside the condition evaluation process, and also can be used in queries about past break levels.

break_level(N)
We are at (or focused on) break level N (N = 0 for the outermost break level).
max_inv(MaxInv)
The last invocation number used within the break level is MaxInv. Note that this invocation number may not be present in the backtrace (because the corresponding call exited deterministically).
private(Priv)
The private information associated with the break level is Priv. Similarly to goal_private/1, this condition refers initially to an unbound variable and can be used to store an arbitrary Prolog term. However, it is strongly recommended that Priv is used as an open ended list, see Storing User Information in the Backtrace.


Node:Other Tests, Next:, Previous:Break Tests, Up:Breakpoint Conditions

Other Conditions

The following conditions are for prescribing or checking the breakpoint type. They cause an exception if used outside the debugger or in execution_state/2.

advice
The breakpoint in question is of advice type.
debugger
The breakpoint in question is of debugger type.

The following construct converts an arbitrary Prolog goal into a condition.

true(Cond)
The Prolog goal Cond is true, i.e. once(Cond) is executed and the condition is satisfied iff this completes successfully. If an exception is raised during execution, then an error message is printed and the condition fails.

The substitutions done on executing Cond are carried out. Cond is subject to module name expansion. If used in the test part of spypoint conditions, the goal should not have any side effects, as the test part may be evaluated several times.

The following conditions represent the Boolean constants.

true
[]
A condition which is always true. Useful e.g. in conditionals.
false
A condition which is always false.


Node:Action Conditions, Next:, Previous:Other Tests, Up:Breakpoint Conditions

Conditions Usable in the Action Part

mode(Mode)
Set the debugger mode to Mode.
command(Command)
Set the command to be executed to Command.
show(Show)
Set the show method to Show.

The values admissible for Mode, Command and Show are described below; see Action Variables.

Furthermore, any other condition can be used in the action part, except for the ones specifying the breakpoint type (advice or debugger).


Node:Past States, Next:, Previous:Action Conditions, Up:Breakpoint Conditions

Options for Focusing on a Past State

The following ground terms can be used in the first argument of execution_state/2 (see Breakpoint Predicates). Alternatively, a list containing such terms can be used. In the latter case the focusing operations, described below, are performed in the specified order. Therefore, when both conditions are used, the list normally will have to be of form [break_level(...),inv(...)].

break_level(BL)
Focus on the current invocation of break level BL. BL is the break level number, the top-level being break_level(0). For past break levels, the current invocation is the one from which the next break level was entered.
inv(Inv)
Focus on the invocation number Inv of the currently focused break level.


Node:Condition Macros, Next:, Previous:Past States, Up:Breakpoint Conditions

Condition Macros

There are a few condition macros expanding to a list of other conditions:

unleash
Expands to [show(print),command(proceed)]
hide
Expands to [show(silent),command(proceed)]
leash
Expands to [show(print),command(ask)]

The user can also define condition macros using the hook below.

breakpoint_expansion(+Macro, -Body) [Hook]
user:breakpoint_expansion(+Macro, -Body)

This predicate is called with each (non-composite) breakpoint test or action, as its first argument. If it succeeds, then the term returned in the second argument (Body) is substituted for the original condition. The expansion is done both at the time the breakpoint is added (for syntax checking) and each time the Macro is evaluated.

Note that Body can be composite, but it cannot be of form Tests-Actions. This means that the whole Body will be interpreted as being in either the test or the action part, depending on the context.


Node:Action Variables, Previous:Condition Macros, Up:Breakpoint Conditions

The Action Variables

In this section we list the possible values of the debugger action variables, and their meaning.

Note that the Prolog terms, supplied as values, are copied when a variable is set. This is relevant primarily in case of the proceed/2 and flit/2 values.

Values allowed in the show condition:

print
Write using options stored in the debugger_print_options Prolog flag.
silent
Display nothing.
display
Write using display.
write
Write using writeq.
write_term(Options)
Write using options Options.
Method-Sel
Display only the subterm selected by Sel, using Method. Here, Method is one of the methods above, and Sel is a subterm selector.

Values allowed in the command condition:

ask
Ask the user what to do next.
proceed
Continue the execution without interacting with the user (cf. unleashing).
flit
Continue the execution without building a procedure box for the current goal (and consequently not encountering any other ports for this invocation). Only meaningful at Call ports, at other ports it is equivalent to proceed.
proceed(Goal,New)
Unify the current goal with Goal and execute the goal New in its place. Goal and New are module name expanded only at execution time with the current type-in module as the default. Only available at Call ports. This construct is used by the u (unify) interactive debugger command.

The term proceed(Goal,New) will be copied when the command action variable is set. Therefore breakpoint specs of form

goal(foo(X))-proceed(_,bar(X))
should be avoided, and
goal(foo(_))-proceed(foo(X),bar(X))
should be used instead. The first variant will not work as expected if X is non-ground, as the variables in the bar/1 call will be detached from the original ones in foo/1. Even if X is ground, the first variant may be much less efficient, as it will copy the possibly huge term X.
flit(Goal,New)
Unify the current goal with Goal and execute the goal New in its place, without creating a procedure box for Goal (and consequently not encountering any other ports for this invocation). Only available at Call ports. Notes for proceed/2, on module name expansion and copying, also apply for flit/2.
exception(E)
Raise the exception E.
abort
Abort the execution.
retry(Inv)
Retry the the most recent goal in the backtrace with an invocation number less or equal to Inv (go back to the Call port of the goal). This is used by the interactive debugger command r, retry; see Debug Commands.
reexit(Inv)
Re-exit the the invocation with number Inv (go back to the Exit port of the goal). Inv must be an exact reference to an exited invocation present in the backtrace (exited nondeterministically, or currently being exited). This is used by the interactive debugger command je, jump to Exit port; see Debug Commands.
redo(Inv)
Redo the the invocation with number Inv (go back to the Redo port of the goal). Inv must be an exact reference to an exited invocation present in the backtrace. This is used by the interactive debugger command jr, jump to Redo port; see Debug Commands.
fail(Inv)
Fail the most recent goal in the backtrace with an invocation number less or equal to Inv (transfer control back to the Fail port of the goal). This is used by the interactive debugger command f, fail; see Debug Commands.

Values allowed in the mode condition:

qskip(Inv)
Quasi-skip until the first port with invocation number less or equal to Inv is reached. Having reached that point, mode is set to trace. Valid only if Inv >= 1 and furthermore Inv =< CurrInv for entry ports (Call, Redo), and Inv < CurrInv for all other ports, where CurrInv is the invocation number of the current port.
skip(Inv)
Skip until the first port with invocation number less or equal to Inv is reached, and set mode to trace there. Inv should obey the same rules as for qskip.
trace
Creep.
debug
Leap.
zip
Zip.
off
Continue without debugging.


Node:Consult, Next:, Previous:Breakpoint Conditions, Up:Debug Intro

Consulting during Debugging

It is possible, and sometimes useful, to consult a file whilst in the middle of program execution. Predicates, which have been successfully executed and are subsequently redefined by a consult and are later reactivated by backtracking, will not notice the change of their definitions. In other words, it is as if every predicate, when called, creates a copy of its definition for backtracking purposes.


Node:Exceptions Debug, Previous:Consult, Up:Debug Intro

Catching Exceptions

Usually, exceptions that occur during debugging sessions are displayed only in trace mode and for invocation boxes for predicates with spypoints on them, and not during skips. However, it is sometimes useful to make exceptions trap to the debugger at the earliest opportunity instead. The hook predicate user:error_exception/1 provides such a possibility:

error_exception(+Exception) [Hook]
user:error_exception(+Exception)

This predicate is called at all Exception ports. If it succeeds, the debugger enters trace mode and prints an exception port message. Otherwise, the debugger mode is unchanged and a message is printed only in trace mode or if a spypoint is reached, and not during skips.

Note that this hook takes effect when the debugger arrives at an Exception port. For this to happen, procedure boxes have to be built, e.g. by running (the relevant parts of) the program in debug mode.


Node:Built Intro, Next:, Previous:Debug Intro, Up:Top

Built-In Predicates

It is not possible to redefine built-in predicates. An attempt to do so will give an error message. See Pred Summary.

SICStus Prolog provides a wide range of built-in predicates to perform the following tasks:

Input / Output
     Reading-in Programs
     Term and Goal Expansion
     Input and Output of Terms
     Character I/O
     Stream I/O
     Dec-10 Prolog File I/O
Arithmetic
Comparison of Terms
Control
Error and Exception Handling
Information about the State of the Program
Meta-Logic
Modification of Terms
Modification of the Program
Internal Database
Blackboard Primitives
All Solutions
Messages and Queries
Coroutining
Debugging
Execution Profiling
Miscellaneous

When introducing a built-in predicate, we shall present its usage with a mode spec, and optionally with an annotation containing one or more of:

ISO
The predicate complies with the ISO Prolog Standard.
ISO only
The predicate variant described complies with the ISO Prolog Standard and is valid in the iso execution mode only.
SICStus only
The predicate variant described is valid in the sicstus execution mode only.
declaration
A declaration that can't be redefined as a predicate.
hook
The predicate is a hook predicate.
hookable
The predicate is a hookable predicate.
obsolescent
The predicate is obsolescent and should be avoided in new code.
reserved
A reserved construct that can't be defined as a predicate.

The following descriptions of the built-in predicates are grouped according to the above categorization of their tasks.


Node:Input Output, Next:, Previous:Built Intro, Up:Built Intro

Input / Output

There are two sets of file manipulation predicates in SICStus Prolog. One set is inherited from DEC-10 Prolog. These predicates always refer to a file by name. The other set of predicates is modeled after Quintus Prolog and refer to files as streams. Streams correspond to the file pointers used at the operating system level.

This second set of file manipulation predicates, the one involving streams, is supported by the ISO Prolog standard. Note that the notion of file is used here in a generalized sense; it may refer to a name file, the user's terminal, or some other device. The ISO Prolog standard refers to this generalized notion of file using the term source/sink.

A stream can be opened and connected to a filename or file descriptor for input or output by calling the predicates open/[3,4]. These predicates will return a reference to a stream which may then be passed as an argument to various I/O predicates. Alternatively, a stream can be assigned an alias at the time of opening, and referred to by this alias afterwards. The predicate close/1 is used for closing a stream.

There are two types of streams, binary or text. Binary streams are seen as a sequence of bytes, i.e. integers in the range 0-255. Text streams, on the other hand, are considered a sequence of characters, represented by their character codes. SICStus Prolog handles wide characters, i.e. characters with codes larger than 255. The WCX (Wide Character eXtension) component of SICStus Prolog allows selecting various encoding schemes via environment variables or hook procedures; see Handling Wide Characters.

The predicates current_stream/3 and stream_property/2 are used for retrieving information about a stream, and for finding the currently existing streams.

Prolog streams can be accessed from C functions as well. See SICStus Streams, for details.

The possible formats of a stream are:

'$stream'(X)
A stream connected to some file. X is an integer.
Atom
A stream alias. Aliases can be associated with streams using the alias(Atom) option of open/4. There are also three predefined aliases:

user_input
An alias initially referring to the UNIX stdin stream. The alias can be changed with prolog_flag/3 and accessed by the C variable SP_stdin.
user_output
An alias initially referring to the UNIX stdout stream. The alias can be changed with prolog_flag/3 and accessed by the C variable SP_stdout.
user_error
An alias initially referring to the UNIX stderr stream. The alias can be changed with prolog_flag/3 and accessed by the C variable SP_stderr.

This stream is used by the Prolog top-level and debugger, and for system messages.

Certain I/O predicates manipulate streams implicitly, by maintaining the notion of a current input stream and a current output stream. The current input and output streams are set to the user_input and user_output initially and for every new break (see Nested). The predicate see/1 (tell/1) can be used for setting the current input (output) stream to newly opened streams for particular files. The predicate seen/0 (told/0) closes the current input (output) stream, and resets it to the standard input (output) stream. The predicate seeing/1 (telling/1) is used for retrieving the filename associated with the current input (output) streams.

The filename user stands for the standard input or output stream, depending on context. Terminal output is only guaranteed to be displayed if the output stream is explicitly flushed.

A filename RelFileSpec other than user must be an atom or a compound term. It is subject to syntactic rewriting. Depending on the operation, the resulting absolute filename is subject to further processing. Syntactic rewriting is performed wrt. a context directory Context, in the follows steps:

For example, asssuming the user's home directory is /users/clyde' and given the clauses

file_search_path(home, '$HOME').
file_search_path(demo, home(prolog(demo))).
file_search_path(prolog, prolog).

the filename demo(mydemo) would be rewritten to '/users/clyde/prolog/demo/mydemo', since $HOME is interpreted as an environment variable (On UNIX, this is the user's home directory).

Failure to open a file normally causes an exception to be raised. This behavior can be turned off and on by of the built-in predicates nofileerrors/0 and fileerrors/0 described below.


Node:Read In, Next:, Previous:Input Output, Up:Input Output

Reading-in Programs

When the predicates discussed in this section are invoked, filenames are treated as relative to the current working directory. While loading code, however, filenames are treated as relative to the directory containing the file being read in. This has the effect that if one of these predicates is invoked recursively, the filename of the recursive load is relative to the directory of the enclosing load. See Load Intro, for an introduction to these predicates.

Directives will be executed in order of occurrence. Be aware of the rules governing relative filenames as they could have an effect on the semantics of directives. Only the first solution of directives is produced, and variable bindings are not displayed. Directives that fail or raise exceptions give rise to warning or error messages, but do not terminate the load. However, these warning or error messages can be intercepted by the hook user:portray_message/2 which can call abort/0 to terminate the load, if that is the desired behavior.

Predicates loading source code are affected by the character-conversion mapping, cf. char_conversion/2; see Term I/O.

Most of the predicates listed below take an argument Files which is a single file name or a list of file names. Source, object and QL files usually end with a .pl, .po and .ql suffix respectively. These suffixes are optional. Each file name may optionally be prefixed by a module name. The module name specifies where to import the exported predicates of a module-file, or where to store the predicates of a non-module-file. The module is created if it doesn't exist already.

absolute_file_name/3 (see Stream Pred) is used to look up the files. The file name user is reserved and denotes the standard input stream.

These predicates are available in runtime systems with the following limitations:


load_files(:Files)
load_files(:Files, +Options)

A generic predicate for loading files with a list of options to provide extra control. This predicate in fact subsumes the other predicates except use_module/3 which also returns the name of the loaded module, or imports a set of predicates from an existing module. Options is a list of zero or more of the following:

if(X)
true (the default) to always load, or changed to load only if the file has not yet been loaded or if it has been modified since it was last loaded. A non-module-file is not considered to have been previously loaded if it was loaded into a different module. The file user is never considered to have been previously loaded.
when(When)
always (the default) to always load, or compile_time to load only if the goal is not in the scope of another load_files/[1,2] directive occurring in a .po or .ql file.

The latter is intended for use when the file only defines predicates that are needed for proper term or goal expansion during compilation of other files.

load_type(LoadType)
source to load source files only, object to load object (.po) files only, ql (obsolescent) to load .ql files only, or latest (the default) to load any type of file, whichever is newest. If the file is user, source is forced.
imports(Imports)
all (the default) to import all exported predicates if the file is a module-file, or a list of predicates to import.
compilation_mode(Mode)
compile to translate into compiled code, consult to translate into static, interpreted code, or assert_all to translate into dynamic, interpreted code.

The default is the compilation mode of any ancestor load_files/[1,2] goal, or compile otherwise. Note that Mode has no effect when an .po or .ql file is loaded, and that it is recommended to use assert_all in conjunction with load_type(source), to ensure that the source file will be loaded even in the presence of a .po or .ql file.

wcx(Wcx)
To pass the term Wcx to the wide character extension component; see Prolog Level WCX Features.

consult(:Files)
reconsult(:Files) [Obsolescent]
[]
[:File|+Files]

Consults the source file or list of files specified by File and Files. Same as load_files(Files, [load_type(source),compilation_mode(consult)]).

compile(:Files)

Compiles the source file or list of files specified by Files. The compiled code is placed in-core, i.e. is added incrementally to the Prolog database. Same as load_files(Files, [load_type(source),compilation_mode(compile)]).

load(:Files) [Obsolescent]

Loads the .ql file or list of files specified by Files. Same as load_files(Files, [load_type(ql)]).

ensure_loaded(:Files) [ISO]

Compiles or loads the file or files specified by Files that have been modified after the file was last loaded, or that have not yet been loaded. The recommended style is to use this predicate for non-module-files only, but if any module-files are encountered, their public predicates are imported. Same as load_files(Files, [if(changed)]).

use_module(:File)

Compiles or loads the module-file specified by File if it has been modified after it was last loaded, or not yet been loaded. Its public predicates are imported. The recommended style is to use this predicate for module-files only, but any non-module-files encountered are simply compiled or loaded. Same as load_files(File, [if(changed)]).

use_module(:File, +Imports)

Loads the module-file File like ensure_loaded/1 and imports the predicates in Imports. If any of these are not public, a warning is issued. Imports may also be set to the atom all in which case all public predicates are imported. Same as load_files(File, [if(changed),imports(Imports)]).

use_module(-Module, :File, +Imports)
use_module(+Module, :File, +Imports)

If used with +Module, and that module has already been loaded, this merely imports Imports from that module. Otherwise, this is equivalent to use_module(File, Imports) with the addition that Module is unified with the loaded module.

fcompile(:Files) [Obsolescent]

Compiles the source file or list of files specified by Files. If Files are prefixed by a module name, that module name will be used for module name expansion during the compilation (see Considerations). The suffix .pl is added to the given filenames to yield the real source filenames. The compiled code is placed on the .ql file or list of files formed by adding the suffix .ql to the given filenames. (This predicate is not available in runtime systems.)

source_file(?File)

File is the absolute name of a source file currently in the system.

source_file(:Head,?File)
source_file(-Head,?File)

Head is the most general goal for a predicate loaded from File.

require(:PredSpecOrSpecs)

PredSpecOrSpecs is a predicate spec or a list or a conjunction of such. The predicate will check if the specified predicates are loaded and if not, will try to load or import them using use_module/2. The file containing the predicate definitions will be located in the following way:


Node:Definite, Next:, Previous:Read In, Up:Input Output

Term and Goal Expansion

When a program is being read in, SICStus Prolog provides hooks that enable the terms being read in to be source-to-source transformed before the usual processing of clauses or directives. The hooks consist in user-defined predicates that define the transformations. One transformation is always available, however: definite clause grammars, a convenient notation for expressing grammar rules. See [Colmerauer 75] and [Pereira & Warren 80].

Definite clause grammars are an extension of the well-known context-free grammars. A grammar rule in Prolog takes the general form

head --> body.

meaning "a possible form for head is body". Both body and head are sequences of one or more items linked by the standard Prolog conjunction operator ,.

Definite clause grammars extend context-free grammars in the following ways:

  1. A non-terminal symbol may be any Prolog term (other than a variable or number).
  2. A terminal symbol may be any Prolog term. To distinguish terminals from non-terminals, a sequence of one or more terminal symbols is written within a grammar rule as a Prolog list. An empty sequence is written as the empty list []. If the terminal symbols are character codes, such lists can be written (as elsewhere) as strings. An empty sequence is written as the empty list, [] or "".
  3. Extra conditions, in the form of Prolog procedure calls, may be included in the right-hand side of a grammar rule. Such procedure calls are written enclosed in {} brackets.
  4. The left-hand side of a grammar rule consists of a non-terminal, optionally followed by a sequence of terminals (again written as a Prolog list).
  5. Disjunction, if-then, if-then-else, and not-provable may be stated explicitly in the right-hand side of a grammar rule, using the operators ; (|), ->, and \+ as in a Prolog clause.
  6. The cut symbol may be included in the right-hand side of a grammar rule, as in a Prolog clause. The cut symbol does not need to be enclosed in {} brackets.

As an example, here is a simple grammar which parses an arithmetic expression (made up of digits and operators) and computes its value.

expr(Z) --> term(X), "+", expr(Y), {Z is X + Y}.
expr(Z) --> term(X), "-", expr(Y), {Z is X - Y}.
expr(X) --> term(X).

term(Z) --> number(X), "*", term(Y), {Z is X * Y}.
term(Z) --> number(X), "/", term(Y), {Z is X / Y}.
term(Z) --> number(Z).

number(C) --> "+", number(C).
number(C) --> "-", number(X), {C is -X}.
number(X) --> [C], {"0"=<C, C=<"9", X is C - "0"}.

In the last rule, C is the character code of some digit.

The query

| ?- expr(Z, "-2+3*5+1", []).

will compute Z=14. The two extra arguments are explained below.

Now, in fact, grammar rules are merely a convenient "syntactic sugar" for ordinary Prolog clauses. Each grammar rule takes an input string, analyses some initial portion, and produces the remaining portion (possibly enlarged) as output for further analysis. The arguments required for the input and output strings are not written explicitly in a grammar rule, but the syntax implicitly defines them. We now show how to translate grammar rules into ordinary clauses by making explicit the extra arguments.

A rule such as

p(X) --> q(X).

translates into

p(X, S0, S) :- q(X, S0, S).

If there is more than one non-terminal on the right-hand side, as in

p(X, Y) -->
        q(X),
        r(X, Y),
        s(Y).

then corresponding input and output arguments are identified, as in

p(X, Y, S0, S) :-
        q(X, S0, S1),
        r(X, Y, S1, S2),
        r(Y, S2, S).

Terminals are translated using the built-in predicate 'C'(S1, X, S2), read as "point S1 is connected by terminal X to point S2", and defined by the single clause

'C'([X|S], X, S).

(This predicate is not normally useful in itself; it has been given the name upper-case c simply to avoid using up a more useful name.) Then, for instance

p(X) --> [go,to], q(X), [stop].

is translated by

p(X, S0, S) :-
        'C'(S0, go, S1),
        'C'(S1, to, S2),
        q(X, S2, S3),
        'C'(S3, stop, S).

Extra conditions expressed as explicit procedure calls naturally translate as themselves, e.g.

p(X) --> [X], {integer(X), X>0}, q(X).

translates to

p(X, S0, S) :-
        'C'(S0, X, S1),
        integer(X),
        X>0,
        q(X, S1, S).

Similarly, a cut is translated literally.

Terminals are translated using the built-in predicate 'C'(S1, X, S2), read as "point S1 is connected by terminal X to point S2", and defined by the single clause

Terminals on the left-hand side of a rule are also translated using 'C'/3, connecting them to the output argument of the head non-terminal, e.g.

is(N), [not] --> [aint].

becomes

is(N, S0, S) :-
        'C'(S0, aint, S1),
        'C'(S, not, S1).

Disjunction has a fairly obvious translation, e.g.

args(X, Y) -->
        (   dir(X), [to], indir(Y)
        ;   indir(Y), dir(X)
        ).

translates to

args(X, Y, S0, S) :-
        (   dir(X, S0, S1),
            'C'(S1, to, S2),
            indir(Y, S2, S)
        ;   indir(Y, S0, S1),
            dir(X, S1, S)
        ).

Similarly for if-then, if-then-else, and not-provable.

The built-in predicates which are concerned with grammar rules and other compile/consult time transformations are as follows:


expand_term(+Term1,?Term2)

If Term1 is a term that can be transformed, Term2 is the result. Otherwise Term2 is just Term1 unchanged. This transformation takes place automatically when grammar rules are read in, but sometimes it is useful to be able to perform it explicitly. Grammar rule expansion is not the only transformation available; the user may define clauses for the predicate user:term_expansion/[2,4] to perform other transformations. user:term_expansion(Term1[,Layout1],Term2[,Layout2]) is called first, and only if it fails is the standard expansion used.

term_expansion(+Term1,?TermOrTerms) [Hook]
term_expansion(+Term1,+Layout1,?TermOrTerms,?Layout2) [Hook]
user:term_expansion(+Term1,?TermOrTerms)
user:term_expansion(+Term1,+Layout1,?TermOrTerms,?Layout2)

Defines transformations on terms read while a program is consulted or compiled. It is called for every Term1 read, including at end of file, represented as the term end_of_file. If it succeeds, TermOrTerms is used for further processing; otherwise, the default grammar rule expansion is attempted. It is often useful to let a term expand to a list of directives and clauses, which will then be processed sequentially.

The 4 arguments version also defines transformations on the layout of the term read, so that the source-linked debugger can display accurate source code lines if the transformed code needs debugging. Layout1 is the layout corresponding to Term1, and Layout2 should be a valid layout of TermOrTerms (see Term I/O).

For accessing aspects of the load context, e.g. the name of the file being compiled, the predicate prolog_load_context/2 (see State Info) can be used.

user:term_expansion/[2,4] may also be used to transform queries entered at the terminal in response to the | ?- prompt. In this case, it will be called with Term1 = ?-(Query) and should succeed with TermOrTerms = ?-(ExpandedQuery).

goal_expansion(+Goal,+Module,?NewGoal) [Hook]
user:goal_expansion(+Goal,+Module,?NewGoal)

Defines transformations on goals while clauses are being consulted, compiled or asserted, after any processing by user:term_expansion/[2,4] of the terms being read in. It is called for every simple Goal in the calling context Module found while traversing the clause bodies. If it succeeds, Goal is replaced by NewGoal; otherwise, Goal is left unchanged. NewGoal may be an arbitrarily complex goal, and user:goal_expansion/3 is recursively applied to its subgoals.

NOTE: the arguments of built-in meta-predicates such as call/1, setof/3 and on_exception/3 are not subject to such compile-time processing.

This predicate is also used to resolve any meta-calls to Goal at runtime via the same mechanism. If the transformation succeeds, NewGoal is simply called instead of Goal. Otherwise, if Goal is a goal of an existing predicate, that predicate is invoked. Otherwise, error recovery is attempted by user:unknown_predicate_handler/3 as described below.

user:goal_expansion/3 can be regarded as a macro expansion facility. It is used for this purpose to support the interface to attributed variables in library(atts), which defines the predicates M:get_atts/2 and M:put_atts/2 to access module-specific variable attributes. These "predicates" are actually implemented via the user:goal_expansion/3 mechanism. This has the effect that calls to the interface predicates are expanded at compile time to efficient code.

For accessing aspects of the load context, e.g. the name of the file being compiled, the predicate prolog_load_context/2 (see State Info) can be used.

phrase(:Phrase,?List)
phrase(:Phrase,?List,+Remainder)

The list List is a phrase of type Phrase (according to the current grammar rules), where Phrase is either a non-terminal or more generally a grammar rule body. Remainder is what remains of the list after a phrase has been found. If called with 2 arguments, the remainder has to be the empty list.

'C'(?S1,?Terminal,?S2)

Not normally of direct use to the user, this built-in predicate is used in the expansion of grammar rules (see above). It is defined as if by the clause 'C'([X|S], X, S).


Node:Term I/O, Next:, Previous:Definite, Up:Input Output

Input and Output of Terms

Most of the following predicates come in two versions, with or without a stream argument. Predicates without a stream argument operate on the current input or output stream, depending on context. Predicates with a stream argument can take stream reference or an alias in this argument position, the alias being replaced by the stream it was associated with.

Some of these predicates support a notation for terms containing multiple occurrences of the same subterm (cycles and DAGs). The notation is @(Template,Substitution) where Substitution is a list of Var=Term pairs where the Var occurs in Template or in one of the Terms. This notation stands for the instance of Template obtained by binding each Var to its corresponding Term. The purpose of this notation is to provide a finite printed representation of cyclic terms. This notation is not used by default, and @/2 has no special meaning except in this context.

read(?Term) [ISO]
read(+Stream,?Term) [ISO]

The next term, delimited by a full-stop (i.e. a ., possibly followed by layout text), is read from Stream and is unified with Term. The syntax of the term must agree with current operator declarations. If a call read(Stream, Term) causes the end of Stream to be reached, Term is unified with the term end_of_file. Further calls to read/2 for the same stream will then raise an exception, unless the stream is connected to the terminal. The characters read are subject to character-conversion, see below.

read_term(?Term,+Options) [ISO]
read_term(+Stream,?Term,+Options) [ISO]

Same as read/[1,2] with a list of options to provide extra control or information about the term. Options is a list of zero or more of:

syntax_errors(+Val)
Controls what action to take on syntax errors. Val must be one of the values allowed for the syntax_errors Prolog flag. The default is set by that flag.
variables(?Vars)
Vars is bound to the list of variables in the term input, in left-to-right traversal order.
variable_names(?Names)
Names is bound to a list of Name=Var pairs, where each Name is an atom indicating the name of a non-anonymous variable in the term, and Var is the corresponding variable.
singletons(?Names)
Names is bound to a list of Name=Var pairs, one for each variable appearing only once in the term and whose name does not begin with _.
cycles(+Boolean)
Boolean must be true or false. If selected, any occurrences of @/2 in the term read in are replaced by the potentially cyclic terms they denote as described above. Otherwise (the default), Term is just unified with the term read in.
layout(?Layout)
Layout is bound to a layout term corresponding to Term. The layout Y of a term X is one of:
  • If X is a variable or atomic term, Y is the number of the line where X occurs.
  • If X is a compound term, Y is a list whose head is the number of the line where the first token of X occurs, and whose remaining elements are the layouts of the arguments of X.
  • [], if no line number information is available for X.

consume_layout(+Boolean)
Boolean must be true or false. If this option is true, read_term/[2,3] will consume the layout-text-item which follows the terminating . (this layout-text-item can either be a layout-char or a comment starting with a %). If the option is false, the layout-text-item will remain in the input stream, so that subsequent character input predicates will see it. The default of the consume_layout option is true in sicstus execution mode, and it is false is iso execution mode.
| ?- read_term(T, [layout(L), variable_names(Va), singletons(S)]).
|: [
     foo(X),
     X = Y
     ].

L = [35,[36,36],[36,[37,37,37],38]],
S = ['Y'=_A],
T = [foo(_B),_B=_A],
Va = ['X'=_B,'Y'=_A] ?
yes
| ?- read_term(T, [consume_layout(false)]), get_code(C).
|: 1.

C = 10,
T = 1 ?
yes
| ?- read_term(T, [consume_layout(true)]), get_code(C).
|: 1.
|: a

C = 97,
T = 1 ? yes

char_conversion(+InChar, +OutChar) [ISO]

InChar and OutChar should be one-char atoms. If they are not the same, then the mapping of InChar to OutChar is added to the character-conversion mapping. This means that in all subsequent term and program input operations any unquoted occurrence of InChar will be replaced by OutChar. The rationale for providing this facility is that in some extended character sets (such as Japanese JIS character sets) the same character can appear several times and thus have several codes, which the users normally expect to be equivalent. It is advisable to always quote the arguments of char_conversion/2.

If InChar and OutChar are the same, the effect of char_conversion/2 is to remove any mapping of InChar from the character-conversion mapping.

current_char_conversion(?InChar, ?OutChar) [ISO]

The character of one-char atom InChar is mapped to that of the one-char atom OutChar in the current character-conversion mapping. Enumerates all such pairs on backtracking.

write(?Term) [ISO]
write(+Stream,?Term) [ISO]

The term Term is written onto Stream according to current operator declarations. Same as write_term([Stream,] Term, [numbervars(true)]).

display(?Term)

The term Term is displayed onto the standard output stream (which is not necessarily the current output stream) in standard parenthesized prefix notation. Same as write_term(user, Term, [ignore_ops(true)]).

write_canonical(?Term) [ISO]
write_canonical(+Stream,?Term) [ISO]

Similar to write(Stream,Term). The term will be written according to the standard syntax. The output from write_canonical/2 can be parsed by read/2 even if the term contains special characters or if operator declarations have changed. Same as write_term([Stream,] Term, [quoted(true),ignore_ops(true)]).

writeq(?Term) [ISO]
writeq(+Stream,?Term) [ISO]

Similar to write(Stream,Term), but the names of atoms and functors are quoted where necessary to make the result acceptable as input to read/2, provided the same operator declarations are in effect. Same as write_term([Stream,] Term, [quoted(true),numbervars(true)]).

print(?Term) [Hookable]
print(+Stream,?Term) [Hookable]

Prints Term onto Stream. This predicate provides a handle for user defined pretty printing:

In particular, the debugging package prints the goals in the tracing messages, and the top-level prints the final values of variables. Thus you can vary the forms of these messages if you wish.

Note that on lists ([_|_]), print/2 will first give the whole list to user:portray/1, but if this fails it will only give each of the (top-level) elements to user:portray/1. That is, user:portray/1 will not be called on all the tails of the list.

Same as write_term([Stream,] Term, [portrayed(true),numbervars(true)]).

portray(+Term) [Hook]
user:portray(+Term)

This should either print the Term and succeed, or do nothing and fail. In the latter case, the default printer (write/1) will print the Term.

portray_clause(?Clause)
portray_clause(+Stream,?Clause)

Writes the clause Clause onto Stream exactly as listing/[0,1] would have written it. Same as write_term([Stream,] Term, [quoted(true),numbervars(true),indented(true)]) followed by a period and a newline % removing redundant module prefixes and binding variables to terms of the form '$VAR'(N) yielding friendlier variable names.

write_term(+Term,+Options) [ISO]
write_term(+Stream,+Term,+Options) [ISO]

Same as write/[1,2] etc. with a list of options to provide extra control. This predicate in fact subsumes the above output predicates except portray_clause/[1,2] which additionally prints a period and a newline, and removes module prefixes that are redundant wrt. the current type-in module. Options is a list of zero or more of the following, where Boolean must be true or false (false is the default).

quoted(+Boolean)
If selected, functors are quoted where necessary to make the result acceptable as input to read/1. write_canonical/1, writeq/1, and portray_clause/1 select this.
ignore_ops(+Boolean)
If selected, Term is written in standard parenthesized notation instead of using operators. write_canonical/1 and display/1 select this.
portrayed(+Boolean)
If selected, user:portray/1 is called for each subterm. print/1 selects this.
numbervars(+Boolean)
If selected, terms of the form '$VAR'(N) where N is an integer >= 0, an atom, or a list of character codes, are treated specially (see numbervars/3). print/1, write/1, writeq/1, and portray_clause/1 select this.
cycles(+Boolean)
If selected, the potentially cyclic term is printed in finite @/2 notation, as discussed above.
indented(+Boolean)
If selected, the term is printed with the same indentation as is used by portray_clause/1 and listing/[0,1].
max_depth(N)
Depth limit on printing. N is an integer. 0 (the default) means no limit.

format(+Format,:Arguments)
format(+Stream,+Format,:Arguments)

Prints Arguments onto Stream according to format Format. Format is a list of formatting characters or character codes. If Format is an atom then is will be used to translate it into a list of character codes. Thus:

| ?- format("Hello world!", []).

has the same effect as

| ?- format('Hello world!', []).

no matter which value the double_quotes Prolog flag has.

format/2 and format/3 is a Prolog interface to the C stdio function printf(). It is modeled after and compatible with Quintus Prolog.

Arguments is a list of items to be printed. If there are no items then an empty list should be supplied.

The default action on a format character is to print it. The character ~ introduces a control sequence. To print a ~ repeat it:

| ?- format('Hello ~~world!', []).

will result in

Hello ~world!

Unless character escapes have been switched off, the escape sequence (see Escape Sequences) \c (c for continue) is useful when formatting a string for readability. It causes all characters up to, but not including, the next non-layout character to be ignored.

| ?- format('Hello \c
             world!', []).

will result in

Hello world!

The general format of a control sequence is ~NC. The character C determines the type of the control sequence. N is an optional numeric argument. An alternative form of N is *. * implies that the next argument in Arguments should be used as a numeric argument in the control sequence. Example:

| ?- format('Hello~4cworld!', [0'x]).

and

| ?- format('Hello~*cworld!', [4,0'x]).

both produce

Helloxxxxworld!

The following control sequences are available.

~a
The argument is an atom. The atom is printed without quoting.
~Nc
(Print character.) The argument is a number that will be interpreted as a character code. N defaults to one and is interpreted as the number of times to print the character.
~Ne
~NE
~Nf
~Ng
~NG
(Print float). The argument is a float. The float and N will be passed to the C printf() function as
printf("%.Ne", Arg)
printf("%.NE", Arg)
printf("%.Nf", Arg)
printf("%.Ng", Arg)
printf("%.NG", Arg)

respectively.

If N is not supplied the action defaults to

printf("%e", Arg)
printf("%E", Arg)
printf("%f", Arg)
printf("%g", Arg)
printf("%G", Arg)

respectively.

~Nd
(Print decimal.) The argument is an integer. N is interpreted as the number of digits after the decimal point. If N is 0 or missing, no decimal point will be printed. Example:
| ?- format('Hello ~1d world!', [42]).
Hello 4.2 world!

| ?- format('Hello ~d world!', [42]).
Hello 42 world!

~ND
(Print decimal.) The argument is an integer. Identical to ~Nd except that , will separate groups of three digits to the left of the decimal point. Example:
| ?- format('Hello ~1D world!', [12345]).
Hello 1,234.5 world!

~Nr
(Print radix.) The argument is an integer. N is interpreted as a radix, 2 =< N =< 36. If N is missing the radix defaults to 8. The letters a-z will denote digits larger than 9. Example:
| ?- format('Hello ~2r world!', [15]).
Hello 1111 world!

| ?- format('Hello ~16r world!', [15]).
Hello f world!

~NR
(Print radix.) The argument is an integer. Identical to ~Nr except that the letters A-Z will denote digits larger than 9. Example:
| ?- format('Hello ~16R world!', [15]).
Hello F world!

~Ns
(Print string.) The argument is a list of character codes. Exactly N characters will be printed. N defaults to the length of the string. Example:
| ?- format('Hello ~4s ~4s!', ["new","world"]).
Hello new  worl!

| ?- format('Hello ~s world!', ["new"]).
Hello new world!

~i
(Ignore.) The argument, which may be of any type, is ignored. Example:
| ?- format('Hello ~i~s world!', ["old","new"]).
Hello new world!

~k
(Print canonical.) The argument may be of any type. The argument will be passed to write_canonical/1 (see Term I/O). Example:
| ?- format('Hello ~k world!', [[a,b,c]]).
Hello .(a,.(b,.(c,[]))) world!

~p
(Print.) The argument may be of any type. The argument will be passed to print/1 (see Term I/O). Example:
| ?- assert((portray([X|Y]) :- print(cons(X,Y)))).
| ?- format('Hello ~p world!', [[a,b,c]]).
Hello cons(a,cons(b,cons(c,[]))) world!

~q
(Print quoted.) The argument may be of any type. The argument will be passed to writeq/1 (see Term I/O). Example:
| ?- format('Hello ~q world!', [['A','B']]).
Hello ['A','B'] world!

~w
(Write.) The argument may be of any type. The argument will be passed to write/1 (see Term I/O). Example:
| ?- format('Hello ~w world!', [['A','B']]).
Hello [A,B] world!

~@
(Call.) The argument is a goal, which will be called and expected to print on the current output stream. If the goal performs other side-effects or does not succeed deterministically, the behavior is undefined. Example:
| ?- format('Hello ~@ world!', [write(new)]).
Hello new world!

~~
(Print tilde.) Takes no argument. Prints ~. Example:
| ?- format('Hello ~~ world!', []).
Hello ~ world!

~Nn
(Print newline.) Takes no argument. Prints N newlines. N defaults to 1. Example:
| ?- format('Hello ~n world!', []).
Hello
 world!

~N
(Print Newline.) Prints a newline if not at the beginning of a line.

The following control sequences set column boundaries and specify padding. A column is defined as the available space between two consecutive column boundaries on the same line. A boundary is initially assumed at line position 0. The specifications only apply to the line currently being written.

When a column boundary is set (~| or ~+) and there are fewer characters written in the column than its specified width, the remaining space is divided equally amongst the pad sequences (~t) in the column. If there are no pad sequences, the column is space padded at the end.

If ~| or ~+ specifies a position preceding the current position, the boundary is set at the current position.

~N|
Set a column boundary at line position N. N defaults to the current position.
~N+
Set a column boundary at N positions past the previous column boundary. N defaults to 8.
~Nt
Specify padding in a column. N is the fill character code. N may also be specified as `C where C is the fill character. The default fill character is <SPC>. Any (~t) after the last column boundary on a line is ignored.
Example:
| ?-
        format('~`*t NICE TABLE ~`*t~61|~n', []),
        format('*~t*~61|~n', []),
        format('*~t~a~20|~t~a~t~20+~a~t~20+~t*~61|~n',
               ['Right aligned','Centered','Left aligned']),
        format('*~t~d~20|~t~d~t~20+~d~t~20+~t*~61|~n',
               [123,45,678]),
        format('*~t~d~20|~t~d~t~20+~d~t~20+~t*~61|~n',
               [1,2345,6789]),
        format('~`*t~61|~n', []).

************************ NICE TABLE *************************
*                                                           *
*      Right aligned      Centered      Left aligned        *
*                123         45         678                 *
*                  1        2345        6789                *
*************************************************************


Node:Char I/O, Next:, Previous:Term I/O, Up:Input Output

Character Input/Output

Most of character I/O predicates have several variants:

bytes vs. characters
There are separate predicates for binary I/O, which work on bytes, and for text I/O, which work on characters. The former have the suffix _byte, e.g. put_byte.
character codes vs. one-char atoms
The text I/O predicates come in two variants, those which use character codes (suffix _code, e.g. put_code), and those using one-char atoms (suffix _char, e.g. put_char).
SICStus compatibility predicates
The SICStus compatibility predicates work on both binary and text streams and use character codes or bytes, depending on the stream type. They normally have no suffix (e.g. put), with the exception of peek_char.
explicit vs. implicit stream
Each of the above predicates comes in two variants: with an explicit first argument, which is the stream or alias to which the predicate applies (e.g. put_byte(Stream, Byte)), or without the stream argument, in which case the current input or output stream is used, depending on the context (e.g. put_byte(Byte)).
I/O on standard streams
These are variants of SICStus compatibility predicates which always work on the standard input or output. These predicates have the prefix tty, e.g. ttyput(Code).
nl [ISO]
nl(+Stream) [ISO]

A new line is started on the text stream Stream by printing an <LFD>. If Stream is connected to the terminal, its buffer is flushed.

get_code(?Code) [ISO]
get_code(+Stream,?Code) [ISO]

Code is the character code of the next character read from text stream Stream. If all characters of Stream have been read, Code is -1, and further calls to get_code/2 for the same stream will normally raise an exception, unless the stream is connected to the terminal (but see the eof_action option of open/4; see Stream Pred).

get_char(?Char) [ISO]
get_char(+Stream,?Char) [ISO]

Char is the one-char atom naming the next character read from text stream Stream. If all characters of Stream have been read, Char is end_of_file, and further calls to get_char/2 for the same stream will normally raise an exception, unless the stream is connected to the terminal (but see the eof_action option of open/4; see Stream Pred).

get_byte(?Byte) [ISO]
get_byte(+Stream,?Byte) [ISO]

Byte is the next byte read from the binary stream Stream. It has the same behavior at the end of stream as get_code.

get0(?Code) [Obsolescent]
get0(+Stream,?Code) [Obsolescent]

A combination of get_code and get_byte: Code is the next character code or byte read from the arbitrary stream Stream.

get(?N) [Obsolescent]
get(+Stream,?N) [Obsolescent]

Same as get0/2, except N is the character code of the next character that is not a layout-char (see Token String) read from Stream.

peek_code(?Code) [ISO]
peek_code(+Stream,?Code) [ISO]

Code is the character code of the next character from text stream Stream, or -1, if all characters of Stream have been read. The character is not actually read, it is only looked at and is still available for subsequent input.

peek_char(?Char) [ISO only]
peek_char(+Stream,?Char) [ISO only]

Char is the one-char atom naming the next character from text stream Stream, or end_of_file, if all characters of Stream have been read. The character is not actually read.

peek_char(?Code) [SICStus only]
peek_char(+Stream,?Code) [SICStus only]

Identical to peek_code.

peek_byte(?Byte) [ISO]
peek_byte(+Stream,?Byte) [ISO]

Byte is the next byte from binary stream Stream, or -1, if all bytes of Stream have been read. The byte is not actually read.

skip(+Code) [Obsolescent]
skip(+Stream,+Code) [Obsolescent]

Skips just past the next character code Code from Stream. Code may be an arithmetic expression.

skip_line
skip_line(+Stream)

Skips just past the next <LFD> from the text stream Stream.

read_line(-Line)
read_line(+Stream, -Line)

Reads one line of input from Stream, and returns the list of character codes Line. When the end of file is reached, Line is the atom end_of_file, and on subsequent calls an exception is raised.

put_code(+Code) [ISO]
put_code(+Stream,+Code) [ISO]

Character code Code is output onto text stream Stream.

put_char(+Char) [ISO]
put_char(+Stream,+Char) [ISO]

The character named by the one-char atom Char is output onto text stream Stream.

put_byte(+Byte) [ISO]
put_byte(+Stream,+Byte) [ISO]

Byte Byte is output onto binary stream Stream.

put(+Code) [Obsolescent]
put(+Stream,+Code) [Obsolescent]

A combination of put_code and put_byte: Code is output onto (an arbitrary stream) Stream. Code may be an arithmetic expression.

tab(+N) [Obsolescent]
tab(+Stream,+N) [Obsolescent]

N spaces are output onto text stream Stream. N may be an arithmetic expression.

The above predicates are the ones which are the most commonly used, as they can refer to any streams. The predicates listed below always refer to the standard input and output streams. They are provided for compatibility with DEC-10 character I/O, and are actually redundant and easily recoded in terms of the above predicates.

ttynl [Obsolescent]

Same as nl(user_output).

ttyflush [Obsolescent]

Same as flush_output(user_output).

ttyget0(?N) [Obsolescent]

Same as get0(user_input, N).

ttyget(?N) [Obsolescent]

Same as get(user_input, N).

ttyput(+N) [Obsolescent]

Same as put(user_output, N).

ttyskip(+N) [Obsolescent]

Same as skip(user_input, N).

ttytab(+N) [Obsolescent]

Same as tab(user_output, N).


Node:Stream Pred, Next:, Previous:Char I/O, Up:Input Output

Stream I/O

The following predicates are relevant to stream I/O. Character, byte and line counts are maintained per stream. All streams connected to the terminal, however, share the same set of counts. For example, writing to user_output will advance the counts for user_input, if both are connected to the terminal. Bidirectional streams use the same counters for input and output.

Wherever a stream argument appears as input (+Stream), a stream alias can be used instead.

absolute_file_name(+RelFileSpec,-AbsFileName)
absolute_file_name(+RelFileSpec,-AbsFileName,+Options)

If RelFileSpec is user, then AbsFileName is unified with user; this "filename" stands for the standard input or output stream, depending on context. Otherwise, unifies AbsFileName with the first absolute file name that corresponds to the relative file specification RelFileSpec and that satisfies the access modes given by Options. Options is a list of zero or more of the following, the default being the empty list:

ignore_underscores(+Boolean)
Boolean must be true or false. If true, when constructing an absolute file name that matches the given access modes, two names are tried: First the absolute file name derived directly from RelFileSpec, and then the file name obtained by first deleting all underscores from RelFileSpec. If false (default), suppresses any deletion of underscores.
extensions(+Ext)
Has no effect if RelFileSpec contains a file extension. Ext is an atom or a list of atoms, each atom representing an extension (e.g. '.pl') that should be tried when constructing the absolute file name. The extensions are tried in the order they appear in the list. Default value is Ext = ["], i.e. only the given RelFileSpec is tried, no extension is added. To specify extensions('') or extensions([]) is equal not to give any extensions option at all.
file_type(+Type)
Has no effect if RelFileSpec contains a file extension. Picks an adequate extension for the operating system currently running, which means that programs using this option instead of extensions(Ext) will be more portable between operating systems. Type must be one of the following atoms:
text
implies extensions(["]). RelFileSpec is a file without any extension. (Default)
source
implies extensions(['.pl',"]). RelFileSpec is a Prolog source file, maybe with a .pl extension.
object
implies extensions(['.po']). RelFileSpec is a Prolog object file.
ql
implies extensions(['.ql']). RelFileSpec is a QL file. Obsolescent.
saved_state
implies extensions(['.sav',"]). RelFileSpec is a saved state, maybe with a .sav extension.
foreign_file
RelFileSpec is a foreign language object file, maybe with a system dependent extension.
foreign_resource
RelFileSpec is a foreign language shared object file, maybe with a system dependent extension.
directory
implies extensions(["]). RelFileSpec is a directory, not a regular file. Only when this option is present can absolute_file_name/3 access directories without raising an exception.

access(+Mode)
Mode must be an atom or a list of atoms. If a list is given, AbsFileName must obey every specified option in the list. This makes it possible to combine a read and write, or write and exist check, into one call. Each atom must be one of the following:
read
AbsFileName must be readable.
write
append
If AbsFileName exists, it must be writable. If it doesn't exist, it must be possible to create.
exist
The file represented by AbsFileName must exist.
none
The file system is not accessed. The first absolute file name that is derived from RelFileSpec is returned. Note that if this option is specified, no existence exceptions can be raised. (Default)

file_errors(+Val)
fileerrors(+Val)
Val is one of the following, where the default is determined by the current value of the fileerrors Prolog flag:
error
Raise an exception if a file derived from RelFileSpec has the wrong permissions, that is, can't be accessed at all, or doesn't satisfy the the access modes specified with the access option.
fail
Fail if a file derived from RelFileSpec has the wrong permissions. Normally an exception is raised, which might not always be a desirable behavior, since files that do obey the access options might be found later on in the search. When this option is given, the search space is guaranteed to be exhausted.

solutions(+Val)
Val is one of the following:
first
As soon as a file derived from RelFileSpec is found, commit to that file. Makes absolute_file_name/3 deterministic. (Default)
all
Return each file derived from RelFileSpec that is found. The files are returned through backtracking. This option is probably most useful in combination with the option file_errors(fail).

relative_to(+FileOrDirectory)
FileOrDirectory should be an atom, and controls how to resolve relative filenames. If it is '', filenames will be treated as relative to the current working directory. If a regular, existing file is given, filenames will be treated as relative to the directory containing FileOrDirectory. Otherwise, filenames will be treated as relative to FileOrDirectory.

If absolute_file_name/3 is called from a goal in a file being loaded, the default is the directory containing that file. Otherwise, the default is the current working directory.

The functionality of absolute_file_name/3 is most easily described as a four phase process, in which each phase gets an infile from the preceding phase, and constructs one or more outfiles to be consumed by the succeeding phases. The phases are:

  1. Syntactic rewriting
  2. Underscore deletion
  3. Extension expansion
  4. Access checking

Each of the three first phases modifies the infile and produces variants that will be fed into the succeeding phases. The functionality of all phases but the first are decided with the option list. The last phase checks if the generated file exists, and if not asks for a new variant from the preceding phases. If the file exists, but doesn't obey the access mode option, a permission exception is raised. If the file obeys the access mode option, absolute_file_name/3 commits to that solution, subject to the solutions option, and unifies AbsFileName with the file name. For a thorough description, see below.

Note that the relative file name RelFileSpec may also be of the form PathAlias(FileSpec), in which case the absolute file name of the file FileSpec in one of the directories designated by PathAlias is returned (see the description of each phase below).

Phase 1
This phase translates the relative file specification given by RelFileSpec into the corresponding absolute file name. See Input Output, for a description of syntactic rewriting. The rewrite is done wrt. the value of the relative_to option. There can be more than one solution, in which case the outfile becomes the solutions in the order they are generated. If the succeeding phase fails, and there is no more solutions, an existence exception is raised.
Phase 2
See the ignore_underscores option.
Phase 3
See the extensions and file_type options.
Phase 4
See the access option.

Comments:

To check whether the file my_text exists in the home directory, with one of the extensions .text or .txt, and is both writable and readable:

| ?- absolute_file_name('~/my_text', File,
                        [extensions(['.text','.txt']),
                        access([read,write])]).

To check if the Prolog file same_functor exists in some library, and also check if it exists under the name samefunctor:

| ?- absolute_file_name(library(same_functor), File,
                        [file_type(source), access(exist),
                         ignore_underscores(true)]).

file_search_path(+Alias,-Expansion) [Hook]
user:file_search_path(+Alias,-Expansion)

Specifies how to rewrite compound filenames to atomic ones, as described in Input Output. Alias should be an atom and Expansions a filename. The predicate may succeed nondeterministically in this search for an atomic filename.

The predicate exists as a dynamic, multifile predicate at startup with the following clauses. See State Info for more info on the Prolog flag host_type. SP_APP_DIR denotes the absolute path to the directory that contains the executable. SP_RT_DIR denotes the absolute path to the directory that contains the SICStus run-time.

file_search_path(library, Path) :-
        library_directory(Path).
file_search_path(system, Platform) :-
        prolog_flag(host_type, Platform).
file_search_path(application, SP_APP_DIR).
file_search_path(runtime, SP_RT_DIR).

library_directory(-Directory) [Hook]
user:library_directory(-Directory)

Specifies a directory to be searched when a filename of the form library(Name) is used. The predicate exists as a dynamic, multifile predicate at startup with a single clause defining the location of the Prolog library. It may succeed nondeterministically in this search for a library directory.

open(+FileName,+Mode,-Stream) [ISO]
open(+FileName,+Mode,-Stream,+Options) [ISO]

If FileName is a valid file name, the file is opened in mode Mode (invoking the UNIX function fopen) and the resulting stream is unified with Stream. Mode is one of:

read
Open the file for input.
write
Open the file for output. The file is created if it does not already exist, the file will otherwise be truncated.
append
Open the file for output. The file is created if it does not already exist, the file will otherwise be appended to.

If FileName is an integer, it is assumed to be a file descriptor passed to Prolog from C. The file descriptor is connected to a Prolog stream (invoking the POSIX function fdopen) which is unified with Stream.

Options is a list of zero or more of:

type(+T)
Specifies whether the stream is a text or binary stream. Default is text.
reposition(+Boolean)
Specifies whether repositioning is required for the stream (true), or not (false). The latter is the default.
alias(+A)
Specifies that the atom A is to be an alias for the stream.
eof_action(+Action)
Specifies what action is to be taken when the end of stream has already been reported (by returning -1 or end_of_file), and a further attempt to input is made. Action can have the following values:
error
An exception is raised. This is the default.
eof_code
An end of stream indicator (-1 or end_of_file) is returned again.
reset
The stream is considered not to be at end of stream and another attempt is made to input from it.

wcx(Wcx)
Specifies to pass the term Wcx to the wide character extension component; see Prolog Level WCX Features.

close(+X) [ISO]
close(+X, +Options) [ISO]

If X is a stream or alias, the stream is closed. If X is the name of a file opened by see/1 or tell/1, the corresponding stream is closed. Options is a list possibly containing the following element:

force(Boolean)
Specifies whether SICStus Prolog is to close the stream forcefully, even in the presence of errors (true), or not (false). The latter is the default. Currently this option has no effect.

current_input(?Stream) [ISO]

Stream is the current input stream. The current input stream is also accessed by the C variable SP_curin.

current_output(?Stream) [ISO]

Stream is the current output stream. The current output stream is also accessed by the C variable SP_curout.

current_stream(?FileName,?Mode,?Stream)

Stream is a stream which was opened in mode Mode and which is connected to the absolute file name Filename (an atom) or to the file descriptor Filename (an integer). This predicate can be used for enumerating all currently open streams through backtracking.

set_input(+Stream) [ISO]

Sets the current input stream to Stream.

set_output(+Stream) [ISO]

Sets the current output stream to Stream.

flush_output [ISO]
flush_output(+Stream) [ISO]

Flushes all internally buffered characters or bytes for Stream to the operating system.

open_null_stream(-Stream)

Opens a text output stream. Everything written to this stream will be thrown away.

character_count(+Stream,?N)

N is the number of characters read/written on text stream Stream. The count is reset by set_stream_position/2.

byte_count(+Stream,?N)

N is the number of bytes read/written on stream Stream. Meaningful for both binary and text streams. In the latter case it will differ from the number returned by character_count/2 in the presence of wide characters. The count is reset by set_stream_position/2.

line_count(+Stream,?N)

N is the number of lines read/written on text stream Stream. The count is reset by set_stream_position/2.

line_position(+Stream,?N)

N is the number of characters read/written on the current line of text stream Stream. The count is reset by set_stream_position/2.

stream_position(+Stream,?Position)

Position is a term representing the current stream position of Stream. This operation is available for any Prolog stream. You can retrieve certain data from a stream position term using stream_position_data/3.

stream_position_data(?Field, +Pos, ?Data)

The Field field of the Pos term is Data. Pos is a stream position; Field is one of: line_count, character_count, line_position, byte_count.

stream_property(?Stream, ?Property)) [ISO]

Stream Stream has property Property. Enumerates through backtracking all currently open streams, including the standard input/output/error streams, and all their properties.

Property can be one of the following:

file_name(?F)
F is the file name associated with the Stream.
mode(?M)
Stream has been opened in mode M.
input
Stream is an input stream.
output
Stream is an output stream.
alias(?A)
Stream has an alias A.
position(?P)
P is a term representing the current stream position of Stream. Same as stream_position(Stream, P).
end_of_stream(?E)
E describes the position of the input stream Stream, with respect to the end of stream. If not all characters have been read, then E is unified with not; otherwise, (all characters read) but no end of stream indicator (-1 or end_of_file) was reported yet, then E is unified with at; otherwise, E is unified with past.
eof_action(?A)
A is the end-of-file action applicable to Stream, cf. the eof_action option of open/4.
type(?T)
Stream is of type T.
wcx(?Wcx)
Wide character extension information Wcx was supplied at opening Stream; see Prolog Level WCX Features.

set_stream_position(+Stream,+Position) [ISO]

Position is a term representing a new stream position of Stream, which is then set to the new position. This operation is only available for Prolog streams connected to "seekable devices" (disk files, usually). If the option reposition(true) was supplied at the successful opening of the stream, then set_stream_position/2 is guaranteed to be successful.

seek(+Stream,+Offset,+Method,-NewLocation)

True if the stream Stream can be set to the byte offset Offset relative to Method, and NewLocation is the new byte offset from the beginning of the file after the operation. Method must be one of:

bof
Seek from the beginning of the file stream.
current
Seek from the current position of the file stream.
eof
Seek from the end of the file stream.

This operation is only available for Prolog streams connected to "seekable devices" (disk files, usually) and is an interface to the stdio functions fseek and ftell. After applying this operation, the character count, line count and line position aspects of the stream position of Stream will be undefined.

at_end_of_stream [ISO]
at_end_of_stream(+Stream) [ISO]

The end of stream has been reached for the input stream Stream. An input stream reaches end of stream when all characters (except EOF, i.e. -1) of the stream have been read. These predicates peek ahead for next input character if there is no character available on the buffer of Stream. Unless the stream is to be treated as connected to the terminal (see SP_force_interactive, Initializing the Prolog Engine), a stream remains at end of stream after EOF has been read, and any further attempt to read from the stream will raise an existence error (see Exception).

at_end_of_line
at_end_of_line(+Stream)

The end of stream or end of line has been reached for the input stream Stream. An input stream reaches end of line when all the characters except <LFD> of the current line have been read. These predicates peek ahead for next input character if there is no character available on the buffer of Stream.

fileerrors

Undoes the effect of nofileerrors/0.

nofileerrors

After a call to this predicate, failure to locate or open a file will cause the operation to fail instead of the default action, which is to raise an exception with an error message.


Node:File Pred, Next:, Previous:Stream Pred, Up:Input Output

DEC-10 Prolog File I/O

The following predicates manipulate files.

see(+File)

The file File becomes the current input stream. File may be a stream previously opened by see/1 or a filename. If it is a filename, the following action is taken: If there is a stream opened by see/1 associated with the same file already, then it becomes the current input stream. Otherwise, the file File is opened for input and made the current input stream.

seeing(?FileName)

FileName is unified with the name of the current input file, if it was opened by see/1, with the current input stream, if it is not user_input; otherwise, with user.

seen

Closes the current input stream, and resets it to user_input.

tell(+File)

The file File becomes the current output stream. File may be a stream previously opened by tell/1 or a filename. If it is a filename, the following action is taken: If there is a stream opened by tell/1 associated with the same file already, then it becomes the current output stream. Otherwise, the file File is opened for output and made the current output stream.

telling(?FileName)

FileName is unified with the name of the current output file, if it was opened by tell/1, with the current output stream, if it is not user_output; otherwise, with user.

told

Closes the current output stream, and resets it to user_output.


Node:I/O Example, Previous:File Pred, Up:Input Output

An Example

Here is an example of a common form of file processing:

process_file(F) :-
        seeing(OldInput),
        see(F),                 % Open file F
        repeat,
          read(T),              % Read a term
          process_term(T),      % Process it
          T == end_of_file,     % Loop back if not at end of file
        !,
        seen,                   % Close the file
        see(OldInput).

The above is an example of a repeat loop. Nearly all sensible uses of repeat/0 follow the above pattern. Note the use of a cut to terminate the loop.


Node:Arithmetic, Next:, Previous:Input Output, Up:Built Intro

Arithmetic

Arithmetic is performed by built-in predicates which take as arguments arithmetic expressions and evaluate them. An arithmetic expression is a term built from numbers, variables, and functors that represent arithmetic functions. At the time of evaluation, each variable in an arithmetic expression must be bound to a non-variable expression. An expression evaluates to a number, which may be an integer or a float.

The range of integers is [-2^2147483616, 2^2147483616). Thus for all practical purposes, the range of integers can be considered infinite.

The range of floats is the one provided by the C double type, typically [4.9e-324, 1.8e+308] (plus or minus). In case of overflow or division by zero, iso execution mode will raise an evaluation error exception. In sicstus execution mode no exceptions will be raised, instead appropriate infinity values, as defined by the IEEE standard, will be used.

Only certain functors are permitted in an arithmetic expression. These are listed below, together with an indication of the functions they represent. X and Y are assumed to be arithmetic expressions. Unless stated otherwise, the arguments of an expression may be any numbers and its value is a float if any of its arguments is a float; otherwise, the value is an integer. Any implicit coercions are performed with the integer/1 and float/1 functions.

The arithmetic functors are annotated with [ISO], [ISO only], or [SICStus only], with the same meaning as for the built-in predicates; see ISO Compliance.

+(X)
The value is X.
-X [ISO]
The value is the negative of X.
X+Y [ISO]
The value is the sum of X and Y.
X-Y [ISO]
The value is the difference of X and Y.
X*Y [ISO]
The value is the product of X and Y.
X/Y [ISO]
The value is the float quotient of X and Y.
X//Y [ISO]
The value is the integer quotient of X and Y. The result is always truncated towards zero. In iso execution mode X and Y have to be integers.
X rem Y [ISO]
The value is the integer remainder after dividing X by Y, i.e. integer(X)-integer(Y)*(X//Y). The sign of a nonzero remainder will thus be the same as that of the dividend. In iso execution mode X and Y have to be integers.
X mod Y [ISO only]
The value is X modulo Y, i.e. integer(X)-integer(Y)*floor(X/Y). The sign of a nonzero remainder will thus be the same as that of the divisor. X and Y have to be integers.
X mod Y [SICStus only]
The value is the same as that of X rem Y.
integer(X)
The value is the closest integer between X and 0, if X is a float; otherwise, to X itself.
float_integer_part(X) [ISO]
The same as integer(X). In iso execution mode X has to be a float.
float_fractional_part(X) [ISO]
The value is the fractional part of X, i.e. X - float_integer_part(X). In iso execution mode X has to be a float.
float(X) [ISO]
The value is the float equivalent of X, if X is an integer; otherwise, to X itself.
X/\Y [ISO]
The value is the bitwise conjunction of the integers X and Y. In iso execution mode X and Y have to be integers.
X\/Y [ISO]
The value is the bitwise disjunction of the integers X and Y. In iso execution mode X and Y have to be integers.
X#Y
The value is the bitwise exclusive or of the integers X and Y.
\(X) [ISO]
The value is the bitwise negation of the integer X. In iso execution mode X has to be an integer.
X<<Y [ISO]
The value is the integer X shifted left by Y places. In iso execution mode X and Y have to be integers.
X>>Y [ISO]
The value is the integer X shifted right by Y places. In iso execution mode X and Y have to be integers.
[X]
A list of just one number X evaluates to X. Since a quoted string is just a list of integers, this allows a quoted character to be used in place of its character code; e.g. "A" behaves within arithmetic expressions as the integer 65.

SICStus Prolog also includes an extra set of functions listed below. These may not be supported by other Prologs. All trigonometric and transcendental functions take float arguments and deliver float values. The trigonometric functions take arguments or deliver values in radians.


abs(X) [ISO]
The value is the absolute value of X.
sign(X) [ISO]
The value is the sign of X, i.e. -1, if X is negative, 0, if X is zero, and 1, if X is positive, coerced into the same type as X (i.e. the result is an integer, iff X is an integer).
gcd(X,Y)
The value is the greatest common divisor of the two integers X and Y. In iso execution mode X and Y have to be integers.
min(X,Y)
The value is the lesser value of X and Y.
max(X,Y)
The value is the greater value of X and Y.
msb(X)
The value is the position of the most significant nonzero bit of the integer X, counting bit positions from zero. It is equivalent to, but more efficient than, integer(log(2,X)). X must be greater than zero, and in iso execution mode, X has to be an integer.
round(X) [ISO only]
The value is the closest integer to X. X has to be a float. If X is exactly half-way between two integers, it is rounded up (i.e. the value is the least integer greater than X).
round(X) [SICStus only]
The value is the float that is the closest integral value to X. If X is exactly half-way between two integers, it is rounded to the closest even integral value.
truncate(X) [ISO only]
The value is the closest integer between X and 0. X has to be a float.
truncate(X) [SICStus only]
The value is the float that is the closest integer between X and 0.
floor(X) [ISO only]
The value is the greatest integer less or equal to X. X has to be a float.
floor(X) [SICStus only]
The value is the float that is the greatest integral value less or equal to X.
ceiling(X) [ISO only]
The value is the least integer greater or equal to X. X has to be a float.
ceiling(X) [SICStus only]
The value is the float that is the least integral value greater or equal to X.
sin(X) [ISO]
The value is the sine of X.
cos(X) [ISO]
The value is the cosine of X.
tan(X)
The value is the tangent of X.
cot(X)
The value is the cotangent of X.
sinh(X)
The value is the hyperbolic sine of X.
cosh(X)
The value is the hyperbolic cosine of X.
tanh(X)
The value is the hyperbolic tangent of X.
coth(X)
The value is the hyperbolic cotangent of X.
asin(X)
The value is the arc sine of X.
acos(X)
The value is the arc cosine of X.
atan(X) [ISO]
The value is the arc tangent of X.
atan2(X,Y)
The value is the four-quadrant arc tangent of X and Y.
acot(X)
The value is the arc cotangent of X.
acot2(X,Y)
The value is the four-quadrant arc cotangent of X and Y.
asinh(X)
The value is the hyperbolic arc sine of X.
acosh(X)
The value is the hyperbolic arc cosine of X.
atanh(X)
The value is the hyperbolic arc tangent of X.
acoth(X)
The value is the hyperbolic arc cotangent of X.
sqrt(X) [ISO]
The value is the square root of X.
log(X) [ISO]
The value is the natural logarithm of X.
log(Base,X)
The value is the logarithm of X in the base Base.
exp(X) [ISO]
The value is the natural exponent of X.
X ** Y [ISO]
exp(X,Y)
The value is X raised to the power of Y.
inf [SICStus only]
The value is infinity as defined in the IEEE standard.
nan [SICStus only]
The value is not-a-number as defined in the IEEE standard.

Variables in an arithmetic expression which is to be evaluated may be bound to other arithmetic expressions rather than just numbers, e.g.

evaluate(Expression, Answer) :- Answer is Expression.

| ?- evaluate(24*9, Ans).
Ans = 216 ?

yes

Arithmetic expressions, as described above, are just data structures. If you want one evaluated you must pass it as an argument to one of the built-in predicates listed below. Note that is/2 only evaluates one of its arguments, whereas all the comparison predicates evaluate both of theirs. In the following, X and Y stand for arithmetic expressions, and Z for some term.

Z is X [ISO]

X, which must be an arithmetic expression, is evaluated and the result is unified with Z.

X =:= Y [ISO]

The numeric values of X and Y are equal.

X =\= Y [ISO]

The numeric values of X and Y are not equal.

X < Y [ISO]

The numeric value of X is less than the numeric value of Y.

X > Y [ISO]

The numeric value of X is greater than the numeric value of Y.

X =< Y [ISO]

The numeric value of X is less than or equal to the numeric value of Y.

X >= Y [ISO]

The numeric value of X is greater than or equal to the numeric value of Y.


Node:Term Compare, Next:, Previous:Arithmetic, Up:Built Intro

Comparison of Terms

These built-in predicates are meta-logical. They treat uninstantiated variables as objects with values which may be compared, and they never instantiate those variables. They should not be used when what you really want is arithmetic comparison (see Arithmetic) or unification.

The predicates make reference to a standard total ordering of terms, which is as follows:

For example, here is a list of terms in standard order:

[ X, -1.0, -9, 1, fie, foe, X = Y, foe(0,2), fie(1,1,1) ]

NOTE: the standard order is only well-defined for finite (acyclic) terms. There are infinite (cyclic) terms for which no order relation holds. Furthermore, blocking goals (see Procedural) on variables or modifying their attributes (see Attributes) does not preserve their order.

These are the basic predicates for comparison of arbitrary terms:

Term1 == Term2 [ISO]

The terms currently instantiating Term1 and Term2 are literally identical (in particular, variables in equivalent positions in the two terms must be identical). For example, the query

| ?- X == Y.

fails (answers no) because X and Y are distinct uninstantiated variables. However, the query

| ?- X = Y, X == Y.

succeeds because the first goal unifies the two variables (see Misc Pred).

Term1 \== Term2 [ISO]

The terms currently instantiating Term1 and Term2 are not literally identical.

Term1 @< Term2 [ISO]

The term Term1 is before the term Term2 in the standard order.

Term1 @> Term2 [ISO]

The term Term1 is after the term Term2 in the standard order.

Term1 @=< Term2 [ISO]

The term Term1 is not after the term Term2 in the standard order.

Term1 @>= Term2 [ISO]

The term Term1 is not before the term Term2 in the standard order.

Some further predicates involving comparison of terms are:

?=(?X,?Y)

X and Y are either syntactically identical or syntactically non-unifiable.

compare(?Op,?Term1,?Term2)

The result of comparing terms Term1 and Term2 is Op, where the possible values for Op are:

=
if Term1 is identical to Term2,
<
if Term1 is before Term2 in the standard order,
>
if Term1 is after Term2 in the standard order.

Thus compare(=,Term1,Term2) is equivalent to Term1 == Term2.

sort(+List1,?List2)

The elements of the list List1 are sorted into the standard order (see Term Compare) and any identical elements are merged, yielding the list List2. (The time and space complexity of this operation is at worst O(N lg N) where N is the length of List1.)

keysort(+List1,?List2)

The list List1 must consist of pairs of the form Key-Value. These items are sorted into order according to the value of Key, yielding the list List2. No merging takes place. This predicate is stable, i.e. if K-A occurs before K-B in the input, then K-A will occur before K-B in the output. (The time and space complexity of this operation is at worst O(N lg N) where N is the length of List1.)


Node:Control, Next:, Previous:Term Compare, Up:Built Intro

Control

+P , +Q [ISO]

P and Q.

+P ; +Q [ISO]

P or Q.

! [ISO]

See Cut.

\+ +P [ISO]

Fails if the goal P has a solution, and succeeds otherwise. This is not real negation ("P is false"), but a kind of pseudo-negation meaning "P is not provable". It is defined as if by

\+(P) :- P, !, fail.
\+(_).

In sicstus execution mode no cuts are allowed in P. In iso execution mode cuts are allowed in P and their scope is the goal P.

Remember that with prefix operators such as this one it is necessary to be careful about spaces if the argument starts with a (. For example:

| ?- \+ (P,Q).

is this operator applied to the conjunction of P and Q, but

| ?- \+(P,Q).

would require a predicate \+ /2 for its solution. The prefix operator can however be written as a functor of one argument; thus

| ?- \+((P,Q)).

is also correct.

+P -> +Q ; +R [ISO]

Analogous to

if P then Q else R

and defined as if by

(P -> Q; R) :- P, !, Q.
(P -> Q; R) :- R.

except the scope of any cut in Q or R extends beyond the if-then-else construct. In sicstus execution mode no cuts are allowed in P. In iso execution mode cuts are allowed in P and their scope is the goal P.

Note that this form of if-then-else only explores the first solution to the goal P.

Note also that the ; is not read as a disjunction operator in this case; instead, it is part of the if-then-else construction.

The precedence of -> is less than that of ; (see Operators), so the expression is read as

;(->(P,Q),R)

+P -> +Q [ISO]

When occurring as a goal, this construction is read as equivalent to

(P -> Q; fail)

if(+P,+Q,+R)

Analogous to

if P then Q else R

but differs from P -> Q ; R in that if(P, Q, R) explores all solutions to the goal P. There is a small time penalty for this--if P is known to have only one solution of interest, the form P -> Q ; R should be preferred.

In sicstus execution mode no cuts are allowed in P. In iso execution mode cuts are allowed in P and their scope is the goal P.

once(+P) [ISO]

Finds the first solution, if any, of goal P. Fails if no solutions are found. Will not explore further solutions on backtracking. Equivalent to

(P -> true; fail)

otherwise
true [ISO]

These always succeed. Use of otherwise/0 is discouraged, because it is not as portable as true/0, and because the former may suggest a completely different semantics than the latter.

false
fail [ISO]

These always fail. Use of false/0 is discouraged, because it is not as portable as fail/0, and because the latter has a more procedural flavor to it.

repeat [ISO]

Generates an infinite sequence of backtracking choices. In sensible code, repeat/0 is hardly ever used except in repeat loops. A repeat loop has the structure

Head :-
        ...
        save(OldState),
        repeat,
          generate(Datum),
          action(Datum),
          test(Datum),
        !,
        restore(OldState),
        ...

The purpose is to repeatedly perform some action on elements which are somehow generated, e.g. by reading them from a stream, until some test becomes true. Usually, generate, action, and test are all determinate. Repeat loops cannot contribute to the logic of the program. They are only meaningful if the action involves side-effects.

The only reason for using repeat loops instead of a more natural tail-recursive formulation is efficiency: when the test fails back, the Prolog engine immediately reclaims any working storage consumed since the call to repeat/0.

call(:Term) [ISO]
incore(:Term) [Obsolescent]
:Term

If Term is instantiated to a term which would be acceptable as the body of a clause, then the goal call(Term) is executed exactly as if that term appeared textually in its place, except that any cut (!) occurring in Term only cuts alternatives in the execution of Term. Use of incore/1 is not recommended.

If Term is not instantiated as described above, an error message is printed and the call fails.

call_cleanup(:Goal,:Cleanup)

This construction can be used to ensure that Cleanup is executed as soon as Goal has completed execution, no matter how it finishes. In more detail:

When call_cleanup/2 with a continuation C is called or backtracked into, first Goal is called or backtracked into. Then there are four possibilities:

  1. Goal succeeds deterministically, possibly leaving some blocked subgoals. Cleanup is executed with continuation C.
  2. Goal succeeds with some alternatives outstanding. Execution proceeds to C. If a cut that removes the outstanding alternatives is encountered, Cleanup is executed with continuation to proceed after the cut. Also, if an exception E that will be caught by an ancestor of the call_cleanup/2 Goal is raised, Cleanup is executed with continuation raise_exception(E).
  3. Goal fails. Cleanup is executed with continuation fail.
  4. Goal raises an exception E. Cleanup is executed with continuation raise_exception(E).

In a typical use of call_cleanup/2, Cleanup succeeds deterministically after performing some side-effect; otherwise, unexpected behavior may result.

Note that the Prolog top-level operates as a read-execute-fail loop, which backtracks into or cuts the query when the user types ; or <RET> respectively. Also, the predicates halt/0 and abort/0 are implemented in terms of exceptions. All of these circumstances can trigger the execution of Cleanup.


Node:Exception, Next:, Previous:Control, Up:Built Intro

Error and Exception Handling

The built-in predicates described in this section are used to alter the control flow to meet exception and error conditions. The equivalent of a raise_exception/1 is also executed by the built-in predicates when errors occur.

catch(:ProtectedGoal,?Pattern,:Handler) [ISO]
on_exception(?Pattern,:ProtectedGoal,:Handler)
throw(+Exception) [ISO]
raise_exception(+Exception)

catch/3 is the same as on_exception/3 (but note different argument order), and throw/1 is the same as raise_exception/1. on_exception/3 calls ProtectedGoal. If this succeeds or fails, so does the call to on_exception/3. If however, during the execution of ProtectedGoal, there is a call to raise_exception(Exception), then Exception is copied and the stack is unwound back to the call to on_exception/3, whereupon the copy of Exception is unified with Pattern. If this unification succeeds, then on_exception/3 calls the goal Handler in order to determine the success or failure of on_exception/3. Otherwise, the stack keeps unwinding, looking for an earlier invocation of on_exception/3. Exception may be any term.

In a development system, any previously uncaught exception is caught and an appropriate error message is printed before returning to the top level. In recursive calls to Prolog from C, uncaught exceptions are returned back to C instead. The printing of these and other messages in a development system is handled by the predicate print_message/2 (see Messages and Queries).

The format of the exception raised by the built-in predicates depends on the execution mode. In iso execution mode the format is

        error(ISO_Error, SICStus_Error)

where ISO_Error is the error term prescribed by the ISO Prolog standard, while SICStus_Error is the part defined by the standard to be implementation dependent. In case of SICStus Prolog this is the SICStus error term, which normally contains additional information, such as the goal and the argument number causing the error.

In sicstus execution mode, the SICStus error term is used when raising an exception in a built-in predicate.

The list below itemizes the error terms, showing the ISO_Error and SICStus_Error form of each one, in that order. Note that the SICStus and ISO error terms do not always belong to the same error class, and that the context and consistency error classes are extensions to the ISO Prolog standard.

The goal part of the error term may optionally have the form $@(Callable,PC) where PC is an internal encoding of the line of code containing the culprit goal or one of its ancestors.

instantiation_error
instantiation_error(Goal,ArgNo)
Goal was called with insufficiently instantiated variables.
type_error(TypeName,Culprit)
type_error(Goal,ArgNo,TypeName,Culprit)
Goal was called with the wrong type of argument(s). TypeName is the expected type and Culprit what was actually found.
domain_error(Domain,Culprit)
domain_error(Goal,ArgNo,Domain,Culprit)
Goal was called with argument(s) of the right type but with illegal value(s). Domain is the expected domain and Culprit what was actually found.
existence_error(ObjectType,Culprit)
existence_error(Goal,ArgNo,ObjectType,Culprit,Reserved)
Something does not exist as indicated by the arguments. If the unknown-flag (see prolog_flag/3) is set to error, this error is raised with ArgNo set to 0 when an undefined predicate is called.
permission_error(Operation,ObjectType,Culprit)
permission_error(Goal,Operation,ObjectType,Culprit,Reserved)
The Operation is not permitted on Culprit of the ObjectType.
context_error(ContextType,CommandType)
context_error(Goal,ContextType,CommandType)
The CommandType is not permitted in ContextType.
syntax_error(Message)
syntax_error(Goal,Position,Message,Tokens,AfterError)
A syntax error was found when reading a term with read/[1,2] or assembling a number from its characters with number_chars/2. In the former case this error is raised only if the syntax_errors flag (see prolog_flag/3) is set to error.
evaluation_error(ErrorType,Culprit)
evaluation_error(Goal,ArgNo,ErrorType,Culprit)
An incorrect arithmetic expression was evaluated. Only occurs in iso execution mode.
representation_error(ErrorType)
representation_error(Goal,ArgNo,ErrorType)
A representation error occurs when the program tries to compute some well-defined value which cannot be represented, such as a compound term with arity > 255.
consistency_error(Culprit1,Culprit2,Message)
consistency_error(Goal,Culprit1,Culprit2,Message)
A consistency error occurs when two otherwise valid values or operations have been specified which are inconsistent with each other.
resource_error(ResourceType)
resource_error(Goal,ResourceType)
A resource error occurs when SICStus Prolog has insufficient resources to complete execution. The only value for ResourceType that is currently in use is memory.
system_error
system_error(Message)
An error occurred while dealing with the operating system.

It is possible to handle a particular kind of existence errors locally: calls to undefined predicates. This can be done by defining clauses for:

unknown_predicate_handler(+Goal,+Module,-NewGoal) [Hook]
user:unknown_predicate_handler(+Goal,+Module,-NewGoal)

Called as a result of a call to an undefined predicate. Goal is bound to the goal of the undefined predicate and Module to the module where the call was made. If this predicate succeeds, Module:NewGoal is called; otherwise, the action taken is governed by the unknown Prolog flag.

The following example shows an auto-loader for library packages:

user:unknown_predicate_handler(Goal, Module, Goal) :-
        functor(Goal, Name, Arity),
        require(Module:(Name/Arity)).


Node:State Info, Next:, Previous:Exception, Up:Built Intro

Information about the State of the Program

listing

Lists onto the current output stream all the clauses in the current interpreted program (in the type-in module; see Module Spec). Clauses listed onto a file can be consulted back.

listing(:Spec)

Lists all interpreted predicates covered by the generalized predicate spec Spec. For example:

| ?- listing([concatenate/3, reverse, m:go/[2-3], bar:_]).

current_atom(?Atom)

Atom is an atom known to SICStus Prolog. Can be used to enumerate (through backtracking) all currently known atoms, and return each one as Atom.

current_predicate(?Name,:Head)
current_predicate(?Name,-Head)

Name is the name of a user defined or library predicate, and Head is the most general goal for that predicate, possibly prefixed by a module name. This predicate can be used to enumerate all user defined or library predicates through backtracking.

current_predicate(?Name/?Arity) [ISO]

Name is the name of a user defined or library predicate, possibly prefixed by a module name and Arity is its arity. This predicate can be used to enumerate all user defined or library predicates through backtracking.

predicate_property(:Head,?Property)
predicate_property(-Head,?Property)

Head is the most general goal for an existing predicate, possibly prefixed by a module name, and Property is a property of that predicate, where the possible properties are

This predicate can be used to enumerate all existing predicates and their properties through backtracking.

current_module(?Module)

Module is a module in the system. It can be used to backtrack through all modules present in the system.

current_module(?Module, ?File)

Module is the module defined in File.

module(+Module)

The type-in module is set to Module.

set_prolog_flag(+FlagName,+NewValue) [ISO]
prolog_flag(+FlagName,?OldValue,?NewValue)

OldValue is the value of the Prolog flag FlagName, and the new value of FlagName is set to NewValue. The possible Prolog flag names and values are:

agc_margin
An integer Margin. The atoms will be garbage collected when Margin new atoms have been created since the last atom garbage collection. Initially 10000.
argv
A read-only flag. The value is a list of atoms of the program arguments supplied when the current SICStus Prolog process was started. For example, if SICStus Prolog were invoked with:
% sicstus -a hello world 2001

then the value will be [hello,world,'2001'].

bounded [ISO]
A read-only flag, one of the flags defining the integer type. For SICStus, its value is false, indicating that the domain of integers is practically unbounded.
char_conversion [ISO]
If this flag is on, unquoted characters in terms and programs read in will be converted, as specified by previous invocations of char_conversion/2. If the flag is off no conversion will take place. The default value is on.
compiling
Governs the mode in which compile/1 and fcompile/1 operate (see Load Intro).
compactcode
Compilation produces byte-coded abstract instructions (the default).
fastcode
Compilation produces native machine instructions. Currently only available for Sparc platforms.
profiledcode
Compilation produces byte-coded abstract instructions instrumented to produce execution profiling data.
debugcode
Compiling is replaced by consulting.

debugging
Corresponds to the predicates debug/0, nodebug/0, trace/0, notrace/0, zip/0, nozip/0 (see Debug Pred). The flag describes the mode the debugger is in, or is required to be switched to:
trace
Trace mode (the debugger is creeping).
debug
Debug mode (the debugger is leaping).
zip
Zip mode (the debugger is zipping).
off
The debugger is switched off (the default).

debug [ISO]
The flag debug, prescribed by the ISO Prolog standard, is a simplified form of the debugging flag:
off
The debugger is switched off (the default).
on
The debugger is switched on (to trace mode, if previously switched off).

(The flags debugging and debug have no effect in runtime systems.)

double_quotes [ISO]
Governs the interpretation of double quoted strings (see Compound Terms):
codes
List of character codes comprising the string.
chars
List of one-char atoms comprising the string.
atom
The atom composed of the same characters as the string.

character_escapes
on or off. If this flag is on, a backslash occurring inside integers in 0' notation or inside quoted atoms or strings has special meaning, and indicates the start of an escape sequence (see Escape Sequences). This flag is relevant when reading as well as when writing terms, and is initially on.
debugger_print_options
The value is a list of options for write_term/3 (see Term I/O), to be used in the debugger's messages. The initial value is [quoted(true),numbervars(true),portrayed(true),max_depth(10)].
discontiguous_warnings
on or off. Enable or disable warning messages when clauses are not together in source files. Initially on. (This warning is always disabled in runtime systems.)
fileerrors
on or off. Enables or disables raising of file error exceptions. Equivalent to fileerrors/0 and nofileerrors/0, respectively (see Stream Pred). Initially on (enabled).
gc
on or off. Enables or disables garbage collection of the global stack. Initially on (enabled).
gc_margin
Margin: At least Margin kilobytes of free global stack space are guaranteed to exist after a garbage collection. Also, no garbage collection is attempted unless the global stack is at least Margin kilobytes. Initially 1000.
gc_trace
Governs global stack garbage collection trace messages.
verbose
Turn on verbose tracing of garbage collection.
terse
Turn on terse tracing of garbage collection.
off
Turn off tracing of garbage collection (the default).

host_type
A read-only flag. The value is an atom identifying the platform on which SICStus was compiled, such as 'x86-linux-glibc2.1' or 'sparc-solaris-5.7'.
integer_rounding_function [ISO]
A read-only flag, one of the flags defining the integer type. In SICStus Prolog its value is toward_zero, indicating that the integer division ((//)/2) and integer remainder (rem/2) arithmetic functions use rounding toward zero; see Arithmetic.
language
iso or sicstus. Selects the execution mode specified.
max_arity [ISO]
A read-only flag, specifying the maximum arity allowed for a compound term. In SICStus Prolog this is 255.
max_integer [ISO]
A read-only flag, specifying the largest possible integer value. As in SICStus Prolog the range of integers in not bounded, prolog_flag/3 and current_prolog_flag/2 will fail, when accessing this flag.
min_integer [ISO]
A read-only flag, specifying the smallest possible integer value. As in SICStus Prolog the range of integers in not bounded, prolog_flag/3 and current_prolog_flag/2 will fail, when accessing this flag.
redefine_warnings
on or off. Enable or disable warning messages when :
  • a module or predicate is being redefined from a different file than its previous definition. Such warnings are currently not issued when a .po file is being loaded.
  • a predicate is being imported while it was locally defined already.
  • a predicate is being redefined locally while it was imported already.
  • a predicate is being imported while it was imported from another module already.

Initially on. (This warning is always disabled in runtime systems.)

single_var_warnings
on or off. Enable or disable warning messages when a clause containing variables not beginning with _ occurring once only is compiled or consulted. Initially on.
source_info
emacs or on or off. If not off while source code is being loaded, information about line numbers and filenames are stored with the loaded code. If the value is on while debugging, this information is used to print the source code location while prompting for a debugger command. If the value is on while printing an uncaught error exception message, the information is used to print the source code location of the culprit goal or one of its ancestors, as far as it can be determined. If the value is emacs in any of these cases, the appropriate line of code is instead highlighted, and no extra text is printed. The value is off initially, and that is its only available value in runtime systems.
syntax_errors
Controls what action is taken upon syntax errors in read/[1,2].
dec10
The syntax error is reported and the read is repeated.
error
An exception is raised. See Exception. (the default).
fail
The syntax error is reported and the read fails.
quiet
The read quietly fails.

system_type
A read-only flag. The value is development in development systems and runtime in runtime systems.
toplevel_print_options
The value is a list of options for write_term/3 (see Term I/O), to be used when the top-level displays variable bindings, answer constraints. It is also used when messages are displayed. The initial value is [quoted(true),numbervars(true),portrayed(true),max_depth(10)].
typein_module
Permitted values are atoms. Controls the current type-in module (see Module Spec). Corresponds to the predicate module/1.
unknown [ISO]
Corresponds to the predicate unknown/2 (see Debug Pred).
trace
Causes calls to undefined predicates to be reported and the debugger to be entered at the earliest opportunity. (This setting is not possible in runtime systems.)
fail
Causes calls to such predicates to fail.
warning
Causes calls to such predicates to display a warning message and then fail.
error
Causes calls to such predicates to raise an exception (the default). See Exception.

user_input
Permitted values are any stream opened for reading. Controls which stream is referenced by user_input and SP_stdin. It is initially set to a stream connected to UNIX stdin.
user_output
Permitted values are any stream opened for writing. Controls which stream is referenced by user_output and SP_stdout. It is initially set to a stream connected to UNIX stdout.
user_error
Permitted values are any stream opened for writing. Controls which stream is referenced by user_error and SP_stderr. It is initially set to a stream connected to UNIX stderr.
version
A read-only flag. The value is an atom containing the banner text displayed on startup and reinitialization, such as 'SICStus 3 #0: Wed Mar 15 12:29:29 MET 1995'.
wcx
The value of the flag is the default term to be passed to the wide character extension component; see Prolog Level WCX Features.

prolog_flag(?FlagName,?Value)
current_prolog_flag(?FlagName,?Value) [ISO]

Value is the current value of the Prolog flag FlagName. Can be used to enumerate all Prolog flags and their values by backtracking.

prolog_load_context(?Key,?Value)

This predicate gives access to context variables during compilation and loading of Prolog files. It unifies Value with the value of the variable identified by Key. Possible keys are:

source
The absolute path name of the file being compiled. During loading of a .po or .ql file, the corresponding source file name is returned.
file
Outside included files (see Include Declarations) this is the same as the source key. In included files this is the absolute path name of the file being included.
directory
The absolute path name of the directory of the file being compiled/loaded. In included files this is the directory of the file being included.
module
The source module (see Meta Exp). This is useful for example if you are defining clauses for user:term_expansion/[2,4] and need to access the source module at compile time.
stream
The stream being compiled or loaded from.
term_position
A term representing the stream position of the last clause read.

statistics

Displays on the standard error stream statistics relating to memory usage, run time, garbage collection of the global stack and stack shifts. The printing is handled by print_message/2; see Messages and Queries.

statistics(?Key,?Value)

This allows a program to gather various execution statistics. For each of the possible keys Key, Value is unified with a list of values, as follows:


global_stack
[size used,free]
This refers to the global stack, where compound terms are stored. The values are gathered before the list holding the answers is allocated.
local_stack
[size used,free]
This refers to the local stack, where recursive predicate environments are stored.
trail
[size used,free]
This refers to the trail stack, where conditional variable bindings are recorded.
choice
[size used,free]
This refers to the choicepoint stack, where partial states are stored for backtracking purposes.
core
memory
[size used,0]
These refer to the amount of memory actually allocated by the Prolog engine. The zero is there for compatibility with other Prolog implementations.
heap
program
[size used,size free]
These refer to the amount of memory allocated for compiled and interpreted clauses, symbol tables, and the like.
runtime
[since start of Prolog,since previous statistics] These refer to CPU time used while executing, excluding time spent garbage collecting, stack shifting, or in system calls.
walltime
[since start of Prolog,since previous statistics] These refer to absolute time elapsed.
garbage_collection
[no. of GCs,bytes freed,time spent]
stack_shifts
[no. of global shifts,no. of local/trailtrail shifts,time spent]
atoms
[no. of atoms,bytes used,bytes free]
atom_garbage_collection
[no. of AGCs,bytes freed,time spent]

Times are in milliseconds, sizes of areas in bytes.

trimcore

Trims the stacks, reclaims any dead clauses and predicates, defragmentizes Prolog's memory, and attempts to return any unused memory to the operating system. It is called automatically at every top-level query, except the stacks are not trimmed then.


Node:Meta Logic, Next:, Previous:State Info, Up:Built Intro

Meta-Logic

The predicates in this section are meta-logical and perform operations that require reasoning about the current instantiation of terms or decomposing terms into their constituents. Such operations cannot be expressed using predicate definitions with a finite number of clauses.

var(?X) [ISO]

Tests whether X is currently uninstantiated (var is short for variable). An uninstantiated variable is one which has not been bound to anything, except possibly another uninstantiated variable. Note that a compound term with some components which are uninstantiated is not itself considered to be uninstantiated. Thus the query

| ?- var(foo(X, Y)).

always fails, despite the fact that X and Y are uninstantiated.

nonvar(?X) [ISO]

Tests whether X is currently instantiated. This is the opposite of var/1.

ground(?X)

Tests whether X is completely instantiated, i.e. free of unbound variables. In this context, mutable terms are treated as nonground, so as to make ground/1 a monotone predicate.

atom(?X) [ISO]

Checks that X is currently instantiated to an atom (i.e. a non-variable term of arity 0, other than a number).

float(?X) [ISO]

Checks that X is currently instantiated to a float.

integer(?X) [ISO]

Checks that X is currently instantiated to an integer.

number(?X) [ISO]

Checks that X is currently instantiated to a number.

atomic(?X) [ISO]

Checks that X is currently instantiated to an atom or number.

simple(?X)

Checks that X is currently uninstantiated or instantiated to an atom or number.

compound(?X) [ISO]

Checks that X is currently instantiated to a compound term.

callable(?X)

Checks that X is currently instantiated to a term valid as a goal i.e. a compound term or an atom.

is_mutable(?X)

Checks that X is currently instantiated to a mutable term (see Modify Term).

functor(+Term,?Name,?Arity) [ISO]
functor(?Term,+Name,+Arity) [ISO]

The principal functor of term Term has name Name and arity Arity, where Name is either an atom or, provided Arity is 0, a number. Initially, either Term must be instantiated, or Name and Arity must be instantiated to, respectively, either an atom and an integer in [0,255] or an atomic term and 0. In the case where Term is initially uninstantiated, the result of the call is to instantiate Term to the most general term having the principal functor indicated.

arg(+ArgNo,+Term,?Arg) [ISO]

Arg is the argument ArgNo of the compound term Term. The arguments are numbered from 1 upwards, ArgNo must be instantiated to a positive integer and Term to a compound term.

+Term =.. ?List [ISO]
?Term =.. +List [ISO]

List is a list whose head is the atom corresponding to the principal functor of Term, and whose tail is a list of the arguments of Term. e.g.

| ?- product(0, n, n-1) =.. L.

L = [product,0,n,n-1]

| ?- n-1 =.. L.

L = [-,n,1]

| ?- product =.. L.

L = [product]

If Term is uninstantiated, then List must be instantiated either to a list of determinate length whose head is an atom, or to a list of length 1 whose head is a number. Note that this predicate is not strictly necessary, since its functionality can be provided by arg/3 and functor/3, and using the latter two is usually more efficient.

name(+Const,?CharList) [Obsolescent]
name(?Const,+CharList) [Obsolescent]

If Const is an atom or number, CharList is a list of the character codes of the characters comprising the name of Const. e.g.

| ?- name(product, L).

L = [112,114,111,100,117,99,116]

| ?- name(product, "product").

| ?- name(1976, L).

L = [49,57,55,54]

| ?- name('1976', L).

L = [49,57,55,54]

| ?- name((:-), L).

L = [58,45]

If Const is uninstantiated, CharList must be instantiated to a list of character codes. If CharList can be interpreted as a number, Const is unified with that number; otherwise, with the atom whose name is CharList. E.g.

| ?- name(X, [58,45]).

X = :-

| ?- name(X, ":-").

X = :-

| ?- name(X, [49,50,51]).

X = 123

Note that there atoms are for which name(Const,CharList) is true, but which will not be constructed if name/2 is called with Const uninstantiated. One such atom is the atom '1976'. It is recommended that new programs use atom_codes/2 or number_codes/2, as these predicates do not have this inconsistency.

atom_codes(+Const,?CodeList) [ISO]
atom_codes(?Const,+CodeList) [ISO]

The same as name(Const,CodeList), but Const is constrained to be an atom.

number_codes(+Const,?CodeList) [ISO]
number_codes(?Const,+CodeList) [ISO]

The same as name(Const,CodeList), but Const is constrained to be a number.

atom_chars(+Const,?CharList) [ISO only]
atom_chars(?Const,+CharList) [ISO only]

Analogous to atom_codes/2, but CharList is a list of one-char atoms, rather than of character codes.

atom_chars(+Const,?CodeList) [SICStus only]
atom_chars(?Const,+CodeList) [SICStus only]

The same as atom_codes(Const,CharList).

number_chars(+Const,?CharList) [ISO only]
number_chars(?Const,+CharList) [ISO only]

Analogous to number_codes/2, but CharList is a list of one-char atoms, rather than of character codes.

number_chars(+Const,?CodeList) [SICStus only]
number_chars(?Const,+CodeList) [SICStus only]

The same as number_codes(Const,CharList).

char_code(+Char,?Code) [ISO]
char_code(?Char,+Code) [ISO]

Code is the character code of the one-char atom Char.

atom_length(+Atom,?Length) [ISO]

Length is the number of characters of the atom Atom.

atom_concat(+Atom1,+Atom2,?Atom12) [ISO]
atom_concat(?Atom1,?Atom2,+Atom12) [ISO]

The characters of the atom Atom1 concatenated with those of Atom2 are the same as the characters of atom Atom12. If the last argument is instantiated, nondeterministically enumerates all possible atom-pairs that concatenate to the given atom, e.g.

| ?- atom_concat(A, B, 'ab').

A = '',
B = ab ? ;

A = a,
B = b ? ;

A = ab,
B = '' ? ;

no

sub_atom(+Atom,?Before,?Length,?After,?SubAtom) [ISO]

The characters of SubAtom form a sublist of the characters of Atom, such that the number of characters preceding SubAtom is Before, the number of characters after SubAtom is After, and the length of SubAtom is Length. Capable of nondeterministically enumerating all sub-atoms and their all possible placements, e.g.

| ?- sub_atom(abrakadabra, Before, _, After, ab).

After = 9,
Before = 0 ? ;

After = 2,
Before = 7 ? ;

no

copy_term(?Term,?CopyOfTerm) [ISO]

CopyOfTerm is a renaming of Term, such that brand new variables have been substituted for all variables in Term. If any of the variables of Term have goals blocked on them, the copied variables will have copies of the goals blocked on them as well. Similarly, independent copies are substituted for any mutable terms in term. It behaves as if defined by:

copy_term(X, Y) :-
        assert('copy of'(X)),
        retract('copy of'(Y)).

The implementation of copy_term/2 conserves space by not copying ground subterms.


Node:Modify Term, Next:, Previous:Meta Logic, Up:Built Intro

Modification of Terms

One of the tenets of logic programming is that terms are immutable objects of the Herbrand universe, and the only sense in which they can be modified is by means of instantiating non-ground parts. There are, however, algorithms where destructive assignment is essential for performance. Although alien to the ideals of logic programming, this feature can be defended on practical grounds.

SICStus Prolog provides an abstract datatype and three operations for efficient backtrackable destructive assignment. In other words, any destructive assignments are transparently undone on backtracking. Modifications that are intended to survive backtracking must be done by asserting or retracting dynamic program clauses instead. Unlike previous releases of SICStus Prolog, destructive assignment of arbitrary terms is not allowed.

A mutable term is represented as a compound terms with a reserved functor: '$mutable'(Value,Timestamp) where Value is the current value and Timestamp is reserved for bookkeeping purposes [Aggoun & Beldiceanu 90].

Any copy of a mutable term created by copy_term/2, assert, retract, an internal database predicate, or an all solutions predicate, is an independent copy of the original mutable term. Any destructive assignment done to one of the copies will not affect the other copy.

The following operations are provided:

create_mutable(+Datum,-Mutable)

Mutable is a new mutable term with initial value Datum. Datum must not be an unbound variable.

get_mutable(?Datum,+Mutable)

Datum is the current value of the mutable term Mutable.

update_mutable(+Datum,+Mutable)

Updates the current value of the mutable term Mutable to become Datum. Datum must not be an unbound variable.

is_mutable(?Mutable)

Checks that Mutable is currently instantiated to a mutable term.

NOTE: the effect of unifying two mutables is undefined.


Node:Modify Prog, Next:, Previous:Modify Term, Up:Built Intro

Modification of the Program

The predicates defined in this section allow modification of dynamic predicates. Dynamic clauses can be added (asserted) or removed from the program (retracted).

For these predicates, the argument Head must be instantiated to an atom or a compound term, with an optional module prefix. The argument Clause must be instantiated either to a term Head :- Body or, if the body part is empty, to Head, with an optional module prefix. An empty body part is represented as true.

Note that a term Head :- Body must be enclosed in parentheses when it occurs as an argument of a compound term, as :- is a standard infix operator with precedence greater than 1000 (see Operators), e.g.:

| ?- assert((Head :- Body)).

Like recorded terms (see Database), the clauses of dynamic predicates have a unique implementation-defined identifier. Some of the predicates below have an additional argument which is this identifier. This identifier makes it possible to access clauses directly instead of requiring a normal database (hash-table) lookup.


assert(:Clause)
assert(:Clause,-Ref)

The current instance of Clause is interpreted as a clause and is added to the current interpreted program. The predicate concerned must currently be dynamic or undefined and the position of the new clause within it is implementation-defined. Ref is a database reference to the asserted clause. Any uninstantiated variables in the Clause will be replaced by new private variables, along with copies of any subgoals blocked on these variables (see Procedural).

asserta(:Clause) [ISO]
asserta(:Clause,-Ref)

Like assert/2, except that the new clause becomes the first clause for the predicate concerned.

assertz(:Clause) [ISO]
assertz(:Clause,-Ref)

Like assert/2, except that the new clause becomes the last clause for the predicate concerned.

clause(:Head,?Body) [ISO]
clause(:Head,?Body,?Ref)
clause(?Head,?Body,+Ref)

The clause (Head :- Body) exists in the current interpreted program, and its database reference is Ref. The predicate concerned must currently be dynamic. At the time of call, either Ref must be instantiated, or Head must be instantiated to an atom or a compound term. Thus clause/3 can have two different modes of use.

retract(:Clause) [ISO]

The first clause in the current interpreted program that matches Clause is erased. The predicate concerned must currently be dynamic. retract/1 may be used in a nondeterminate fashion, i.e. it will successively retract clauses matching the argument through backtracking. If reactivated by backtracking, invocations of the predicate whose clauses are being retracted will proceed unaffected by the retracts. This is also true for invocations of clause/[2,3] for the same predicate. The space occupied by a retracted clause will be recovered when instances of the clause are no longer in use.

retractall(:Head)

Erases all clauses whose head matches Head, where Head must be instantiated to an atom or a compound term. The predicate concerned must currently be dynamic. The predicate definition is retained.

NOTE: all predicates mentioned above first look for a predicate that is visible in the module in which the call textually appears. If no predicate is found, a new dynamic predicate (with no clauses) is created automatically. It is recommended to declare as dynamic predicates for which clauses will be asserted.

abolish(:Spec) [ISO]
abolish(:Name,+Arity)

Abolishes the procedures specified by the generalized predicate spec Spec or Name/Arity. Name may be prefixed by a module name (see Module Spec). In iso execution mode only dynamic predicates can be abolished. In sicstus execution mode only built-in predicates cannot be abolished, the user-defined ones always can be, even when static.

erase(+Ref)

The dynamic clause or recorded term (see Database) whose database reference is Ref is effectively erased from the internal database or interpreted program.

instance(+Ref,?Term)

A (most general) instance of the dynamic clause or recorded term whose database reference is Ref is unified with Term.


Node:Database, Next:, Previous:Modify Prog, Up:Built Intro

Internal Database

The predicates described in this section were introduced in early implementations of Prolog to provide efficient means of performing operations on large quantities of data. The introduction of indexed dynamic predicates have rendered these predicates obsolete, and the sole purpose of providing them is to support existing code. There is no reason whatsoever to use them in new code.

These predicates store arbitrary terms in the database without interfering with the clauses which make up the program. The terms which are stored in this way can subsequently be retrieved via the key on which they were stored. Many terms may be stored on the same key, and they can be individually accessed by pattern matching. Alternatively, access can be achieved via a special identifier which uniquely identifies each recorded term and which is returned when the term is stored.


recorded(?Key,?Term,?Ref) [Obsolescent]

The internal database is searched for terms recorded under the key Key. These terms are successively unified with Term in the order they occur in the database. At the same time, Ref is unified with the database reference to the recorded item. If the key is instantiated to a compound term, only its principal functor is significant. If the key is uninstantiated, all terms in the database are successively unified with Term in the order they occur.

recorda(+Key,?Term,-Ref) [Obsolescent]

The term Term is recorded in the internal database as the first item for the key Key, where Ref is its database reference. The key must be given, and only its principal functor is significant. Any uninstantiated variables in the Term will be replaced by new private variables, along with copies of any subgoals blocked on these variables (see Procedural).

recordz(+Key,?Term,-Ref) [Obsolescent]

Like recorda/3, except that the new term becomes the last item for the key Key.

current_key(?KeyName,?KeyTerm) [Obsolescent]

KeyTerm is the most general form of the key for a currently recorded term, and KeyName is the name of that key. This predicate can be used to enumerate in undefined order all keys for currently recorded terms through backtracking.


Node:Blackboard Primitives, Next:, Previous:Database, Up:Built Intro

Blackboard Primitives

The predicates described in this section store arbitrary terms in a per-module repository known as the "blackboard". The main purpose of the blackboard was initially to provide a means for communication between branches executing in parallel, but the blackboard works equally well during sequential execution. The blackboard implements a mapping from keys to values. Keys are restricted to being atoms or small integers, whereas values are arbitrary terms. In contrast to the predicates described in the previous sections, a given key can map to at most a single term.

Each Prolog module maintains its own blackboard, so as to avoid name clashes if different modules happen to use the same keys. The "key" arguments of these predicates are subject to module name expansion, so the module name does not have to be explicitly given unless multiple Prolog modules are supposed to share a single blackboard.

The predicates below implement atomic blackboard actions.

bb_put(:Key, +Term)

A copy of Term is stored under Key. Any previous term stored under the same Key is simply deleted.

bb_get(:Key, ?Term)

If a term is currently stored under Key, a copy of it is unified with Term. Otherwise, bb_get/2 silently fails.

bb_delete(:Key, ?Term)

If a term is currently stored under Key, the term is deleted, and a copy of it is unified with Term. Otherwise, bb_delete/2 silently fails.

bb_update(:Key, ?OldTerm, ?NewTerm)

If a term is currently stored under Key and unifies with OldTerm, the term is replaced by a copy of NewTerm. Otherwise, bb_update/3 silently fails. This predicate provides an atomic swap operation.

The following example illustrates how these primitives may be used to implement a "maxof" predicate that finds the maximum value computed by some nondeterminate goal, which may execute in parallel. We use a single key max. Note the technique of using bb_update/3 in a repeat-fail loop, since other execution branches may be competing for updating the value, and we only want to store a new value if it is greater than the old value.

We assume that Goal does not produce any "false" solutions that would be eliminated by cuts in a sequential execution. Thus, Goal may need to include redundant checks to ensure that its solutions are valid, as discussed above.

maxof(Value, Goal, _) :-
        bb_put(max, -1),                % initialize max-so-far
        call(Goal),
        update_max(Value),
        fail.
maxof(_, _, Max) :-
        bb_delete(max, Max),
        Max > 1.

update_max(New):-
        repeat,
          bb_get(max, Old),
          compare(C, Old, New),
          update_max(C, Old, New), !.

update_max(<, Old, New) :- bb_update(max, Old, New).
update_max(=, _, _).
update_max(>, _, _).


Node:All Solutions, Next:, Previous:Blackboard Primitives, Up:Built Intro

All Solutions

When there are many solutions to a problem, and when all those solutions are required to be collected together, this can be achieved by repeatedly backtracking and gradually building up a list of the solutions. The following built-in predicates are provided to automate this process.

Note that the Goal argument to the predicates listed below is called as if by call/1 at runtime. Thus if Goal is complex and if performance is an issue, define an auxiliary predicate which can then be compiled, and let Goal call it.

setof(?Template,:Goal,?Set) [ISO]

Read this as "Set is the set of all instances of Template such that Goal is satisfied, where that set is non-empty". The term Goal specifies a goal or goals as in call(Goal) (see Control). Set is a set of terms represented as a list of those terms, without duplicates, in the standard order for terms (see Term Compare). If there are no instances of Template such that Goal is satisfied then the predicate fails.

The variables appearing in the term Template should not appear anywhere else in the clause except within the term Goal. Obviously, the set to be enumerated should be finite, and should be enumerable by Prolog in finite time. It is possible for the provable instances to contain variables, but in this case the list Set will only provide an imperfect representation of what is in reality an infinite set.

If there are uninstantiated variables in Goal which do not also appear in Template, then a call to this built-in predicate may backtrack, generating alternative values for Set corresponding to different instantiations of the free variables of Goal. (It is to cater for such usage that the set Set is constrained to be non-empty.) Two instantiations are different iff no renaming of variables can make them literally identical. For example, given the clauses:

likes(bill, cider).
likes(dick, beer).
likes(harry, beer).
likes(jan, cider).
likes(tom, beer).
likes(tom, cider).

the query

| ?- setof(X, likes(X,Y), S).

might produce two alternative solutions via backtracking:

S = [dick,harry,tom],
Y = beer ? ;

S = [bill,jan,tom],
Y = cider ? ;

The query:

| ?- setof((Y,S), setof(X, likes(X,Y), S), SS).

would then produce:

SS = [(beer,[dick,harry,tom]),(cider,[bill,jan,tom])]

Variables occurring in Goal will not be treated as free if they are explicitly bound within Goal by an existential quantifier. An existential quantification is written:

Y^Q

meaning "there exists a Y such that Q is true", where Y is some Prolog variable.

For example:

| ?- setof(X, Y^(likes(X,Y)), S).

would produce the single result:

S = [bill,dick,harry,jan,tom]

in contrast to the earlier example.

Note that in iso execution mode, only outermost existential quantification is accepted, i.e. if the Goal argument is of form V1 ^ ... ^ N ^ SubGoal. In sicstus execution mode existential quantification is handled also deeper inside Goal.

bagof(?Template,:Goal,?Bag) [ISO]

This is exactly the same as setof/3 except that the list (or alternative lists) returned will not be ordered, and may contain duplicates. The effect of this relaxation is to save a call to sort/2, which is invoked by setof/3 to return an ordered list.

?X^:P

The all solution predicates recognize this as meaning "there exists an X such that P is true", and treats it as equivalent to P (see Control). The use of this explicit existential quantifier outside the setof/3 and bagof/3 constructs is superfluous and discouraged.

findall(?Template,:Goal,?Bag) [ISO]

Bag is a list of instances of Template in all proofs of Goal found by Prolog. The order of the list corresponds to the order in which the proofs are found. The list may be empty and all variables are taken as being existentially quantified. This means that each invocation of findall/3 succeeds exactly once, and that no variables in Goal get bound. Avoiding the management of universally quantified variables can save considerable time and space.

findall(?Template,:Goal,?Bag,?Remainder)

Same as findall/3, except Bag is the list of solution instances appended with Remainder, which is typically unbound.


Node:Messages and Queries, Next:, Previous:All Solutions, Up:Built Intro

Messages and Queries

This section describes the two main aspects of user interaction, displaying messages and querying the user. We will deal with these two issues in turn.


Node:Message Processing, Next:, Previous:Messages and Queries, Up:Messages and Queries

Message Processing

Every message issued by the Prolog system is displayed using a single predicate:

print_message(+Severity, +Message)

Message is a term that encodes the message to be printed. The format of message terms is subject to change, but can be inspected in the file library('SU_messages') of the SICStus Prolog distribution.

The atom Severity specifies the type (or importance) of the message. The following table lists the severities known to the SICStus Prolog system, together with the line prefixes used in displaying messages of the given severity:

error '! ' for error messages
warning '* ' for warning messages
informational '% ' for informational messages
help '' for help messages
query '' for query texts (see Query Processing)
silent '' a special kind of message which normally does not produce any outpu, but can be intercepted by hooks

print_message/2 is a built-in predicate, so that users can invoke it to have their own messages processed in the same way as the system messages.

The processing and printing of the messages is highly customizable. For example, this allows the user to change the language of the messages, or to make them appear in dialog windows rather than on the terminal.

Phases of Message Processing

Messages are processed in two major phases. The user can influence the behavior of each phase using appropriate hooks, described later.

The first phase is called the message generation phase: it determines the text of the message from the input (the abstract message term). No printing is done here. In this phase the user can change the phrasing or the language of the messages.

The result of the first phase is created in the form of a format-command list. This is a list whose elements are format-commands, or the atom nl denoting the end of a line. A format-command describes a piece of text not extending over a line boundary and it can be one of the following:

FormatString-Args
format(FormatString, Args)
This indicates that the message text should appear as if printed by
format(FormatString, Args).

write_term(Term, Options)
This indicates that the message text should appear as if printed by
write_term(Term, Options).

write_term(Term)
Equivalent to write_term(Term, Options) where Options is the actual value of the prolog flag toplevel_print_options.

As an example, let us see what happens in case of the toplevel call _ =:= 3. An instantiation error is raised by the Prolog system, which is caught, and the abstract message term instantiation_error(_=:=3,1) is generated (assuming sicstus execution mode)--the first argument is the goal, and the second argument is the position of the uninstantiated variable within the goal. In the first phase of message processing this is converted to the following format-command list:

['Instantiation error'-[],' in argument ~d of ~q'-[1,=:= /2],nl,
 'goal:  '-[],write_term(_=:=3),nl]

A minor transformation, so-called line splitting is performed on the message text before it is handed over to the second phase. The format-command list is broken up along the nl atoms into a list of lines, where each line is a list of format-commands. We will use the term format-command lines to refer to the result of this transformation.

In the example above, the result of this conversion is the following:

[['Instantiation error'-[],' in argument ~d of ~q'-[1,=:= /2]],
 ['goal:  '-[],write_term(_=:=3)]]
The above format-command lines term is the input of the second phase of message processing.

The second phase is called the message printing phase, this is where the message is actually displayed. The severity of the message is used here to prefix each line of the message with some characters indicating the type of the message, as listed above.

The user can change the exact method of printing (e.g. redirection of messages to a stream, a window, or using different prefixes, etc.) through appropriate hooks.

In our example the following lines are printed by the second phase of processing:

! Instantiation error in argument 1 of =:= /2
! goal:  _=:=3

The user can override the default message processing mechanism in the following two ways:

Message Generation Phase

The default message generation predicates are located in the library('SU_messages') file, in the 'SU_messages' module, together with other message and query related predicates. This is advantageous when these predicates have to be changed as a whole (for example when translating all messages to another language), because this can be done simply by replacing the file library('SU_messages') by a new one.

In the message generation phase three alternative methods are tried:

The hook predicate generate_message_hook/3 can be used to override the default behavior, or to handle new messages defined by the programmer, which do not fit the default message generation schemes. The latter can also be achieved by adding new clauses to the extendible 'SU_messages':generate_message/3 predicate.

If both the hook and the default method refuses to handle the message, then the following simple format-command list is generated from the abstract message term Message:

['~q'-[Message],nl]
This will result in displaying the abstract message term itself, as if printed by writeq/1.

For messages of the severity silent the message generation phase is skipped, and the [] format-command list is returned as the output.

Message Printing Phase

By default this phase is handled by the built-in predicate print_message_lines/3. Each line of the message is prefixed with a string depending on the severity, and is printed to user_error. The query severity is special--no newline is printed after the last line of the message.

This behavior can be overridden by defining the hook predicate message_hook/3, which is called with the severity of the message, the abstract message term and its translation to format-command lines. It can be used to make smaller changes, for example by calling print_message_lines/3 with a stream argument other than user_error, or to implement a totally different display method such as using dialog windows for messages.

For messages of the severity silent the message printing phase consists of calling the hook predicate message_hook/3 only. Even if the hook fails, no printing is done.


Node:Message Handling Predicates, Next:, Previous:Message Processing, Up:Messages and Queries

Message Handling Predicates

print_message(+Severity, +Message) [Hookable]

Prints a Message of a given Severity. The behavior can be customized using the hooks user:portray_message/2, user:generate_message_hook/3 and user:message_hook/3.

All messages from the system are printed by calling this predicate.

First print_message/2 calls user:portray_message/2 with the same arguments. If this does not succeed, the message is processed in the following phases:


portray_message(+Severity, +Message) [Hook]
user:portray_message(+Severity, +Message)

Called by print_message/2 before processing the message. If this succeeds, it is assumed that the message has been processed and nothing further is done.

generate_message_hook(+Message, -L0, -L) [Hook]
user:generate_message_hook(+Message, -L0, -L)

A way for the user to override the call to 'SU_messages':generate_message/3 in the message generation phase in print_message/2.

'SU_messages':generate_message(+Message, -L0, -L) [multifile,extendible]

Defines how to transform a message term Message to a format-command list. For a given Message, generates a format-command list in the form of the difference list L0-L; this means, that L0 is the generated list with L appended to it. This list will be translated into format-command lines which will be passed to the message printing phase.

message_hook(+Severity, +Message, +Lines) [Hook]
user:message_hook(+Severity, +Message, +Lines)

Overrides the call to print_message_lines/3 in the message printing phase of print_message/2. A way for the user to intercept the abstract message term Message of type Severity, whose translation into format-command lines is Lines, before it is actually printed.

print_message_lines(+Stream, +Severity, +Lines)

Print the Lines to Stream, preceding each line with a prefix defined by Severity. Lines must be a valid format-command lines, Severity can be an arbitrary atom. If it is one of the predefined severities, the corresponding prefix is used in printing the message lines. Otherwise the Severity itself is interpreted as the prefix (this is for Quintus Prolog compatibility, where print_message_lines/3 takes the prefix as its second argument). In case of the query severity no newline is written after the last line.

goal_source_info(+AGoal, ?Goal, ?SourceInfo)

Decompose the AGoal annotated goal into a Goal proper and the SourceInfo descriptor term, indicating the source position of the goal.

Annotated goals occur in most of error message terms, and carry information on the Goal causing the error and its source position. The SourceInfo term, retrieved by goal_source_info/3 will be one of the following:

[]
The goal has no source information associated with it.
fileref(File,Line)
The goal occurs in file File, line Line.
clauseref(File,MFunc,ClauseNo,CallNo,Line)
The goal occurs in file File, within predicate MFunc, clause number ClauseNo, call number CallNo and virtual line number Line. Here, MFunc is of form Module:Name/Arity, calls are numbered textually and the virtual line number shows the position of the goal within the listing of the predicate MFunc, as produced by listing/1. Such a term is returned for goals occurring in interpreted predicates which do not have "real" line number information, e.g. because they were entered from the terminal, or created dynamically.


Node:Query Processing, Next:, Previous:Message Handling Predicates, Up:Messages and Queries

Query Processing

All user input in the Prolog system is handled by a single predicate:

ask_query(+QueryClass, +Query, +Help, -Answer)

QueryClass, described below, specifies the form of the query interaction. Query is an abstract message term specifying the query text, Help is an abstract message term used as a help message in certain cases, and Answer is the (abstract) result of the query.

ask_query/4 is a built-in predicate, so that users can invoke it to have their own queries processed in the same way as the system queries.

The processing of queries is highly customizable. For example, this allows changing the language of the input expected from the user, or to make queries appear in dialog windows rather than on the terminal.

Query Classes

Queries posed by the system can be classified according to the kind of input they expect, the way the input is processed, etc. Queries of the same kind form a query class.

For example, queries requiring a yes/no answer form a query class with the following characteristics:

There are built-in query classes for reading in yes/no answers, toplevel queries, debugger commands, etc.

A query class is characterized by a ground Prolog term, which is supplied as the first argument to the query processing predicate ask_query/4. The characteristics of a query class are normally described by the extendible predicate

'SU_messages':query_class(+QueryClass, -Prompt, -InputMethod,
                          -MapMethod, -FailureMode).

The arguments of the query_class predicate have the following meaning:

Phases of Query Processing

Query processing is done in several phases, described below. We will illustrate what is done in each phase through a simple example: the question put to the user when the solution to the toplevel query X is 1+1 is displayed, requesting a decision whether to find alternative answers or not:

| ?- X is 1+1.

X = 2 ?  no
Please enter ";" for more choices; otherwise, <return>
 ? ;

We focus on the query X = 2 ? in the above script.

The example query belongs to the class next_solution, its text is described by the message term solutions([binding("X",2)]), and its help text by the message term bindings_help. Accordingly, such a query is executed by calling:

ask_query(next_solution,               /* QueryClass */
          solutions([binding("X",2)]), /* Query */
          bindings_help,               /* Help */
          Answer)

In general, execution of ask_query(+QueryClass, +Query, +Help, -Answer) consists of the following phases:

Hooks in Query Processing

As explained above, the major parts of query processing are implemented in the 'SU_messages' module in the file library('SU_messages') through the following extendible predicates:

This is to enable the user to change the language used, the processing done, etc., simply by changing or replacing the library('SU_messages') file.

To give more control to the user and to make the system more robust (for example if the 'SU_messages' module is corrupt) the so-called four step procedure is used in the above three cases--obtaining the query class parameters, performing the query input and performing the mapping. The four steps of this procedure, described below, are tried in the given order until the first one that succeeds. Note that if an exception is raised within the first three steps, then a warning is printed and the step is considered to have failed.

Default Input Methods

The following InputMethod types are implemented by the default 'SU_messages':query_input(+InputMethod, +Prompt, -RawInput) (and these are the input methods known to the third, fall-back step):

line
The Prompt is printed, a line of input is read using read_line/2 and the list of character codes is returned as RawInput.
term(Options)
Prompt is set to be the prompt (cf. prompt/2), and a Prolog term is read by read_term/2 using the given Options, and is returned as RawInput.
FinalTerm^term(Term,Options)
A Prolog term is read as above, and is unified with Term. FinalTerm is returned as RawInput. For example, the T-Vs^term(T,[variable_names(Vs)]) input method will return the term read, paired with the list of variable names.

Default Map Methods

The following MapMethod types are known to 'SU_messages':query_map(+MapMethod, +RawInput, -Result, -Answer) and to the built-in fall-back mapping:

char(Pairs)
In this map method RawInput is assumed to be a string (a list of character codes).

Pairs is a list of Name-Abbreviations pairs, where Name is a ground term, and Abbreviations is a list of character codes. The first non-layout character of RawInput is used for finding the corresponding name as the answer, by looking it up in the abbreviation lists. If the character is found, then Result is success, and Answer is set to the Name found; otherwise, Result is failure.

=
No conversion is done, Answer is equal to RawInput and Result is success.
debugger
This map method is used when reading a single line debugger command. It parses the debugger command and returns the corresponding abstract command term. If the parse is unsuccessful, the answer unknown(Line,Warning) is returned. This is to allow the user to extend the debugger command language via debugger_command_hook/2, see Debug Commands.

The details of this mapping can be obtained from the library('SU_messages') file.

Note that the fall-back version of this mapping is simplified, it only accepts parameterless debugger commands.

Default Query Classes

Most of the default query classes are designed to support some specific interaction with the user within the Prolog development environment. The full list of query classes can be inspected in the file library('SU_messages'). Here, we only describe the two classes defined by 'SU_messages':query_class/5 that may be of general use:

QueryClass yes_or_no yes_no_proceed
Prompt ' (y or n) ' ' (y, n, p, s, a, or ?) '
InputMethod line line
MapMethod char([yes-"yY", no-"nN"]) char([yes-"yY", no-"nN", proceed-"pP", suppress-"sS", abort-"aA"])
FailureMode help_query help_query


Node:Query Handling Predicates, Previous:Query Processing, Up:Messages and Queries

Query Handling Predicates

ask_query(+QueryClass, +Query, +Help, -Answer) [Hookable]

Prints the question Query, then reads and processes user input according to QueryClass, and returns the result of the processing, the abstract answer term Answer. The Help message may be printed in case of invalid input.

All queries made by the system are handled by calling this predicate.

First ask_query/4 calls query_hook/6 with the same arguments plus the Query and Help arguments converted to format-command lines. If this call succeeds, then it overrides all further processing done by ask_query/4. Otherwise, the query is processed in the following way:


query_hook(+QueryClass, +Query, +QueryLines, +Help, +HelpLines, -Answer) [Hook]
user:query_hook(+QueryClass, +Query, +QueryLines, +Help, +HelpLines, -Answer)

Called by ask_query/4 before processing the query. If this predicate succeeds, it is assumed that the query has been processed and nothing further is done.

query_class_hook(+QueryClass, -Prompt, -InputMethod, -MapMethod, -FailureMode) [Hook]
user:query_class_hook(+QueryClass, -Prompt, -InputMethod, -MapMethod, -FailureMode)

Provides the user with a method of overriding the call to 'SU_messages':query_class/5 in the preparation phase of query processing. This way the default query class characteristics can be changed.

'SU_messages':query_class(+QueryClass, -Prompt, -InputMethod, -MapMethod, -FailureMode) [multifile,extendible]

Returns the parameters of the given QueryClass:

For the list of default input- and map methods, see the "Default Input Methods" and "Default Map Methods" subsections in Query Processing.

'SU_messages':query_abbreviation(+QueryClass, -Prompt, -Pairs) [multifile,extendible]

This extendible predicate provides a shortcut for defining query classes with some fixed characteristics, where

This defines a query class with the given prompt, the line input method, the char(Pairs) map method and help_query failure mode. The predicate is actually implemented by the first clause of 'SU_messages':query_class/5:

query_class(QueryClass, Prompt, line,
            char(Pairs), help_query) :-
        query_abbreviation(QueryClass, Prompt, Pairs), !.

query_input_hook(+InputMethod, +Prompt, -RawInput) [Hook]
user:query_input_hook(+InputMethod, +Prompt, -RawInput)

Provides the user with a method of overriding the call to 'SU_messages':query_input/3 in the input phase of query processing. This way the implementation of the default input methods can be changed.

'SU_messages':query_input(+InputMethod, +Prompt, -RawInput) [multifile,extendible]

Implements the input phase of query processing. The user is prompted with Prompt, input is read according to InputMethod, and the result is returned in RawInput.

See Query Processing, for details.

query_map_hook(+MapMethod, +RawInput, -Result, -Answer) [Hook]
user:query_map_hook(+MapMethod, +RawInput, -Result, -Answer)

Provides the user with a method of overriding the call to 'SU_messages':query_map/4 in the mapping phase of query processing. This way the implementation of the default map methods can be changed.

'SU_messages':query_map(+MapMethod, +RawInput, -Result, -Answer) [multifile,extendible]

Implements the mapping phase of query processing. The RawInput, received from query_input/3, is mapped to the abstract answer term Answer. The mapping is defined by the MapMethod parameter, and one of the terms success, failure and failure(Warning), describing the result of the conversion is returned in Result.

See Query Processing, for details.


Node:Coroutining, Next:, Previous:Messages and Queries, Up:Built Intro

Coroutining

The coroutining facility can be accessed by a number of built-in predicates. This makes it possible to use coroutines in a dynamic way, without having to rely on block declarations:

when(+Condition,:Goal)

Blocks Goal until the Condition is true, where Condition is a Prolog goal with the restricted syntax:

nonvar(X)
ground(X)
?=(X,Y)
Condition,Condition
Condition;Condition

For example:

| ?- when(((nonvar(X);?=(X,Y)),ground(T)), process(X,Y,T)).

freeze(?X,:Goal)

Blocks Goal until nonvar(X) (see Meta Logic) holds. This is defined as if by:

freeze(X, Goal) :- when(nonvar(X), Goal).

or

:- block freeze(-, ?).
freeze(_, Goal) :- Goal.

frozen(-Var,?Goal)

If some goal is blocked on the variable Var, or Var has attributes that can be interpreted as a goal (see Attributes), then that goal is unified with Goal. If no goals are blocked, Goal is unified with the atom true. If more than one goal is blocked, a conjunction is unified with Goal.

dif(?X,?Y)

Constrains X and Y to represent different terms i.e. to be non-unifiable. Calls to dif/2 either succeed, fail, or are blocked depending on whether X and Y are sufficiently instantiated. It is defined as if by:

dif(X, Y) :- when(?=(X,Y), X\==Y).

call_residue(:Goal,?Residue)

The Goal is executed as if by call/1. If during the execution some attributes or blocked goals were attached to some variables, then Residue is unified with a list of VariableSet-Goal pairs, and those variables no longer have attributes or blocked goals attached to them. Otherwise, Residue is unified with the empty list [].

VariableSet is a set of variables such that when any of the variables is bound, Goal gets unblocked. Usually, a goal is blocked on a single variable, in which case VariableSet is a singleton.

Goal is an ordinary goal, sometimes module prefixed. For example:

| ?- call_residue((dif(X,f(Y)), X=f(Z)), Res).

X = f(Z),
Res = [[Y,Z]-(prolog:dif(f(Z),f(Y)))]


Node:Debug Pred, Next:, Previous:Coroutining, Up:Built Intro

Debugging

Debugging predicates are not available in runtime systems.

unknown(?OldState,?NewState)

OldState is the current state of the "Action on unknown predicates" flag, and sets the flag to NewState. This flag determines whether or not the system is to catch calls to undefined predicates (see Undefined Predicates), when user:unknown_predicate_handler/3 cannot handle the goal. The possible states of the flag are:

trace
Causes calls to undefined predicates to be reported and the debugger to be entered at the earliest opportunity. Not available in runtime systems.
fail
Causes calls to such predicates to fail.
warning
Causes calls to such predicates to display a warning message and then fail.
error
Causes calls to such predicates to raise an exception (the default). See Exception.

debug

The debugger is switched on in leap mode. See Basic Debug.

trace

The debugger is switched on in creep mode. See Basic Debug.

zip

The debugger is switched on in zip mode. See Basic Debug.

nodebug
notrace
nozip

The debugger is switched off. See Basic Debug.

leash(+Mode)

Leashing Mode is set to Mode. See Basic Debug.

spy :Spec

Plain spypoints are placed on all the predicates given by Spec. See Plain Spypoint.

spy(:Spec, :Conditions)

Spypoints with condition Conditions are placed on all the predicates given by Spec. See Breakpoint Predicates.

nospy :Spec

All spypoints (plain and conditional) are removed from all the predicates given by Spec. See Plain Spypoint.

nospyall

Removes all the spypoints (including the generic ones) that have been set.

debugging

Displays information about the debugger. See Basic Debug.

add_breakpoint(:Conditions, ?BID)

Creates a breakpoint with Conditions and with identifier BID. See Breakpoint Predicates.

current_breakpoint(:Conditions, ?BID, ?Status, ?Kind)

There is a breakpoint with conditions Conditions, identifier BID, enabledness Status, and kind Kind. See Breakpoint Predicates.

remove_breakpoints(+BIDs)
disable_breakpoints(+BIDs)
enable_breakpoints(+BIDs)

Removes, disables or enables the breakpoints specified by BIDs. See Breakpoint Predicates.

execution_state(:Tests)

Tests are satisfied in the current state of the execution.

execution_state(+FocusConditions, :Tests)

Tests are satisfied in the state of the execution pointed to by FocusConditions.

debugger_command_hook(+DCommand,?Actions) [Hook]
user:debugger_command_hook(+DCommand,?Actions)

Allows the interactive debugger to be extended with user-defined commands. See Debug Commands.

error_exception(+Exception) [Hook]
user:error_exception(+Exception)

Tells the debugger to enter trace mode on certain exceptions. See Advanced Debugging.


Node:Profiling, Next:, Previous:Debug Pred, Up:Built Intro

Execution Profiling

Execution profiling is a common aid for improving software performance. The SICStus Prolog compiler has the capability of instrumenting compiled code with counters which are initially zero and incremented whenever the flow of control passes a given point in the compiled code. This way the number of calls, backtracks, choicepoints created, etc., can be counted for the instrumented predicates, and an estimate of the time spent in individual clauses and disjuncts can be calculated.

Gauge is a graphical user interface for inspecting execution profiles. It is available as a library module (see Gauge).

The original version of the profiling package was written by M.M. Gorlick and C.F. Kesselman at the Aerospace Corporation [Gorlick & Kesselman 87].

Only compiled code can be instrumented. To get an execution profile of a program, the compiler must first be told to produce instrumented code. This is done by issuing the query:

| ?- prolog_flag(compiling,_,profiledcode).

after which the program to be analyzed can be compiled as usual. Any new compiled code will be instrumented while the compilation mode flag has the value profiledcode.

The profiling data is generated by simply running the program. The predicate profile_data/4 (see below) makes available a selection of the data as a Prolog term. The predicate profile_reset/1 zeroes the profiling counters for a selection of the currently instrumented predicates.

profile_data(:Spec,?Selection,?Resolution,-Data)

Data is profiling data collected from the predicates covered by the generalized predicate spec Spec.

The Selection argument determines the kind of profiling data to be collected. If uninstantiated, the predicate will backtrack over its possible values, which are:

calls
All instances of entering a clause by a procedure call are counted. This is equivalent to counting all procedure calls that have not been determined to fail by indexing on the first argument.
backtracks
All instances of entering a clause by backtracking are counted.
choice_points
All instances of creating a choicepoint are counted. This occurs, roughly, when the implementation determines that there are more than one possibly matching clauses for a procedure call, and when a disjunction is entered.
shallow_fails
Failures in the "if" part of if-then-else statements, and in the "guard" part of guarded clauses, are counted as shallow failures. See Conditionals and Disjunction.
deep_fails
Any failures that do not classify as shallow as above are counted as deep failures. The reason for distinguishing shallow and deep failures is that the former are considerably cheaper to execute than the latter.
execution_time
The execution time for the selected predicates, clauses, or disjuncts is estimated in artificial units.

The Resolution argument determines the level of resolution of the profiling data to be collected. If uninstantiated, the predicate will backtrack over its possible values, which are:

predicate
Data is a list of Module:PredName-Count, where Count is a sum of the corresponding counts per clause.
clause
Data is a list of Module:ClauseName-Count, where Count includes counts for any disjunctions occurring inside that clause. Note, however, that the selections calls and backtracks do not include counts for disjunctions.
all
Data is a list of Module:InternalName-Count. This is the finest resolution level, counting individual clauses and disjuncts.

Above, PredName is a predicate spec, ClauseName is a compound term PredName/ClauseNumber, and InternalName is either
ClauseName--corresponding to a clause, or
(ClauseName-DisjNo)/Arity/AltNo--corresponding to a disjunct.

profile_reset(:Spec)

Zeroes all counters for predicates covered by the generalized predicate spec Spec.


Node:Misc Pred, Previous:Profiling, Up:Built Intro

Miscellaneous

?X = ?Y [ISO]

Defined as if by the clause Z=Z.; i.e. X and Y are unified.

?X \= ?Y [ISO]

The same as \+ X = Y; i.e. X and Y are not unifiable.

unify_with_occurs_check(?X, ?Y) [ISO]

True if X and Y unify to a finite (acyclic) term. Runs in almost linear time.

length(?List,?Length)

If List is instantiated to a list of determinate length, then Length will be unified with this length.

If List is of indeterminate length and Length is instantiated to an integer, then List will be unified with a list of length Length. The list elements are unique variables.

If Length is unbound then Length will be unified with all possible lengths of List.

numbervars(?Term,+N,?M)

Unifies each of the variables in term Term with a special term, so that write(Term) (or writeq(Term)) (see Term I/O) prints those variables as (A + (i mod 26))(i/26) where i ranges from N to M-1. N must be instantiated to an integer. If it is 0 you get the variable names A, B, ..., Z, A1, B1, etc. This predicate is used by listing/[0,1] (see State Info).

undo(:Goal)

The goal Goal is executed on backtracking. This predicate is useful if Goal performs some side-effect which must be done on backtracking to undo another side-effect.

Note that this operation is immune to cuts. That is, undo/1 does not behave as if it were defined by:

weak_undo(_).
weak_undo(Goal) :- Goal, fail.

since defining it that way would not guarantee that Goal be executed on backtracking.

Note also that the Prolog top-level operates as a read-call-fail loop, and backtracks implicitly for each new query. Raised exceptions and the predicates halt/0 and abort/0 cause implicit backtracking as well.

halt [ISO]

Causes Prolog to exit back to the shell. (In recursive calls to Prolog from C, this predicate will return back to C instead.)

halt(+Code) [ISO]

Causes the Prolog process to immediately exit back to the shell with the integer return code Code, even if it occurs in a recursive call from C.

op(+Precedence,+Type,+Name) [ISO]

Declares the atom Name to be an operator of the stated Type and Precedence (see Operators). Name may also be a list of atoms in which case all of them are declared to be operators. If Precedence is 0 then the operator properties of Name (if any) are cancelled.

current_op(?Precedence,?Type,?Op) [ISO]

The atom Op is currently an operator of type Type and precedence Precedence. Neither Op nor the other arguments need be instantiated at the time of the call; i.e. this predicate can be used to generate as well as to test.

break

Invokes a recursive top-level. See Nested. (This predicate is not available in runtime systems.)

abort

Aborts the current execution. See Nested. (In recursive calls to Prolog from C, this predicate will return back to C instead.)

save_files(+SourceFiles, +File)

Any module declarations, predicates, multifile clauses, or directives encountered in SourceFiles are saved in object format into the file File. Source file information as provided by source_file/[1,2] for the relevant predicates and modules is also saved.

If File does not have an explicit suffix, the suffix .po will be appended to it. SourceFiles should denote a single file or a list of files. File can later be loaded by load_files/[1,2], at which time any saved directives will be re-executed. If any of the SourceFiles declares a module, File too will behave as a module-file and export the predicates listed in the first module declaration encountered in SourceFiles. See Saving.

save_modules(+Modules, +File)

The module declarations, predicates, multifile clauses and initializations belonging to Modules are saved in object format into the file File. Source file information and embedded directives (except initializations) are not saved.

If File does not have an explicit suffix, the suffix .po will be appended to it. Modules should denote a single module or a list of modules. File can later be loaded by load_files/[1,2] and will behave as a module-file and export any predicates exported by the first module in Modules. See Saving.

save_predicates(:Spec, +File)

The predicates specified by the generalized predicate spec Spec are saved in object format into the file File. Source file information and embedded directives are not saved. Thus, this predicate is intended for saving data represented as tables of dynamic facts, not for saving static code.

If File does not have an explicit suffix, the suffix .po will be appended to it. File can later be loaded by load_files/[1,2]. See Saving.

save_program(+File)
save_program(+File, :Goal)

The system saves the program state into file File. When the program state is restored, Goal is executed. Goal defaults to true. See Saving.

restore(+File)

The system is returned to the program state previously saved to file File with start-up goal Goal. restore/1 may succeed, fail or raise an exception depending on Goal. See Saving.

garbage_collect

Performs a garbage collection of the global stack immediately.

garbage_collect_atoms

Performs a garbage collection of the atoms immediately.

gc

Enables garbage collection of the global stack (the default).

nogc

Disables garbage collection of the global stack.

prompt(?Old,?New)

The sequence of characters (prompt) which indicates that the system is waiting for user input is represented as an atom, and unified with Old; the atom bound to New specifies the new prompt. In particular, the goal prompt(X, X) unifies the current prompt with X, without changing it. Note that this predicate only affects the prompt given when a user's program is trying to read from the standard input stream (e.g. by calling read/1). Note also that the prompt is reset to the default |: on return to top-level.

version

Displays the introductory messages for all the component parts of the current system.

Prolog will display its own introductory message when initially run and on reinitialization by calling version/0. If this message is required at some other time it can be obtained using this predicate which displays a list of introductory messages; initially this list comprises only one message (Prolog's), but you can add more messages using version/1. (This predicate is not available in runtime systems.)

version(+Message)

Appends Message to the end of the message list which is output by version/0. Message must be an atom. (This predicate is not available in runtime systems.)

The idea of this message list is that, as systems are constructed on top of other systems, each can add its own identification to the message list. Thus version/0 should always indicate which modules make up a particular package. It is not possible to remove messages from the list.

help [Hookable]

Displays basic information, or a user defined help message. It first calls user:user_help/0, and only if that call fails is a default help message printed on the current output stream. (This predicate is not available in runtime systems.)

user_help [Hook]
user:user_help

This may be defined by the user to print a help message on the current output stream.


Node:Mixing C and Prolog, Next:, Previous:Built Intro, Up:Top

Mixing C and Prolog

SICStus Prolog provides a bi-directional, procedural interface for program parts written in C and Prolog. The C side of the interface defines a number of functions and macros for various operations. On the Prolog side, you have to supply declarations specifying the names and argument/value types of C functions being called as Prolog predicates. These declarations are used by the predicate load_foreign_resource/1, which performs the actual binding of C functions to Prolog predicates.

In most cases, the argument/value type declaration suffice for making the necessary conversions of data automatically as they are passed between C and Prolog. However, it is possible to declare the type of an argument to be a Prolog term, in which case the receiving function will see it as a "handle" object, called an SP_term_ref, for which access functions are provided.

The C support routines are available in a development system as well as in runtime systems. The support routines include:


Node:Notes, Next:, Previous:Mixing C and Prolog, Up:Mixing C and Prolog

Notes


ANSI Conformance
Only C compilers that support ANSI C (or similar) are supported.
The SP_PATH variable
It is normally not necessary to set this environment variable, but its value will be used, as a fall-back, at runtime if no explicit boot path is given when initializing a runtime or development system. In this chapter, the environment variable SP_PATH is used as a shorthand for the SICStus Prolog installation directory, whose default location for SICStus 3.9.0 is /usr/local/lib/sicstus-3.9.0) for UNIX and C:\Program Files\SICStus Prolog 3.9.0 for Windows. See Environment Variables.
Definitions and declarations
Type definitions and function declarations for the interface are found in the header file <sicstus/sicstus.h>.
Error Codes

The value of many support functions is a return code which is one of SP_SUCCESS for success, SP_FAILURE for failure, SP_ERROR if an error condition occurred, or if an uncaught exception was raised during a call from C to Prolog. If the value is SP_ERROR, the macro SP_errno will return a value describing the error condition:

int SP_errno

The function SP_error_message returns a pointer to the diagnostic message corresponding to a specified error number:

char *SP_error_message(int errno)

Wide Characters
The foreign interface supports wide characters. Whenever a sequence of possibly wide character codes is to be passed to or from a C function it is encoded as a sequence of bytes, using the so called internal encoding of SICStus Prolog, the UTF-8 encoding; see WCX Concepts. Unless noted otherwise the encoded form is terminated by a NUL byte. This sequence of bytes will be called an encoded string, representing the given sequence of character codes. Note that it is a property of the UTF-8 encoding that it does not change ASCII character code sequences.

If a foreign function is specified to return an encoded string, an exception will be raised if, on return to Prolog, the actual string is malformed (is not a valid sequence of UTF-8 encoded characters). The exception raised is representation_error(...,...,mis_encoded_string).


Node:Calling C, Next:, Previous:Notes, Up:Mixing C and Prolog

Calling C from Prolog

Functions written in the C language may be called from Prolog using an interface in which automatic type conversions between Prolog terms and common C types are declared as Prolog facts. Calling without type conversion can also be specified, in which case the arguments and values are passed as SP_term_refs. This interface is partly modeled after Quintus Prolog.

The functions installed using this foreign language interface may invoke Prolog code and use the support functions described in the other sections of this chapter.

Functions, or their equivalent, in any other language having C compatible calling conventions may also be interfaced using this interface. When referring to C functions in the following, we also include such other language functions. Note however that a C compiler is needed since a small amount of glue code (in C) must be generated for interfacing purposes.


Node:Foreign Resources, Next:, Previous:Calling C, Up:Calling C

Foreign Resources

A foreign resource is a set of C functions, defined in one or more files, installed as an atomic operation. The name of a foreign resource, the resource name, is an atom, which should uniquely identify the resource. Thus, two foreign resources with the same name cannot be installed at the same time.

It is recommended that a resource name be all lowercase, starting with a to z followed by a sequence consisting of a to z, underscore (_), and digits. The resource name is used to construct the file name containing the foreign resource.

For each foreign resource, a foreign_resource/2 fact is used to declare the interfaced functions. For each of these functions, a foreign/[2,3] fact is used to specify conversions between predicate arguments and C-types. These conversion declarations are used for creating the necessary interface between Prolog and C.

The functions making up the foreign resource, the automatically generated glue code, and any libraries, are compiled and linked, using the program splfr (see The Foreign Resource Linker), to form a linked foreign resource. A linked foreign resource exists in two different flavors, static and dynamic. A static resource is simply a relocatable object file containing the foreign code. A dynamic resource is a shared library (.so under most UNIX dialects, .dll under Windows) which is loaded into the Prolog executable at runtime.

Foreign resources can be linked into the Prolog executable either when the executable is built (pre-linked), or at runtime. Pre-linking can be done using static or dynamic resources. Runtime-linking can only be done using dynamic resources. Dynamic resources can also be unlinked.

In all cases, the declared predicates are installed by the built-in predicate load_foreign_resource/1. The resource name of a linked foreign resource is derived from its filename by deleting any leading path and the suffix. If the resource was pre-linked, only the predicate names are bound; otherwise, runtime-linking is attempted (using dlopen(), LoadLibrary(), or similar).

See Top, for more information.


Node:Conversion Declarations, Next:, Previous:Foreign Resources, Up:Calling C

Conversion Declarations

Conversion declaration predicates:

foreign_resource(+ResourceName,+Functions) [Hook]

Specifies that a set of foreign functions, to be called from Prolog, are to be found in the resource named by ResourceName. Functions is a list of functions exported by the resource. Only functions that are to be called from Prolog and optionally one init function and one deinit function should be listed. The init and deinit functions are specified as init(Function) and deinit(Function) respectively (see Init and Deinit Functions). This predicate should be defined entirely in terms of facts (unit clauses) and will be called in the relevant module, i.e. not necessarily in the user module. For example:

foreign_resource('terminal', [scroll,pos_cursor,ask]).

specifies that functions scroll(), pos_cursor() and ask() are to be found in the resource terminal.

foreign(+CFunctionName, +Predicate) [Hook]
foreign(+CFunctionName, +Language, +Predicate) [Hook]

Specify the Prolog interface to a C function. Language is at present constrained to the atom c, so there is no advantage in using foreign/3 over foreign/2. CFunctionName is the name of a C function. Predicate specifies the name of the Prolog predicate that will be used to call CFunction(). Predicate also specifies how the predicate arguments are to be translated to and from the corresponding C arguments. These predicates should be defined entirely in terms of facts (unit clauses) and will be called in the relevant module, i.e. not necessarily in the user module. For example:

foreign(pos_cursor, c, move_cursor(+integer, +integer)).

The above example says that the C function pos_cursor() has two integer value arguments and that we will use the predicate move_cursor/2 to call this function. A goal move_cursor(5, 23) would translate into the C call pos_cursor(5,23);.

The third argument of the predicate foreign/3 specifies how to translate between Prolog arguments and C arguments. A call to a foreign predicate will raise an exception if an input arguments is uninstantiated (instantiation_error/2) or has the wrong type (type_error/4) or domain (domain_error/4). The call will fail upon return from the function if the output arguments do not unify with the actual arguments.

The available conversions are listed in the next subsection.


Node:Conversions, Next:, Previous:Conversion Declarations, Up:Calling C

Conversions between Prolog Arguments and C Types

The following table lists the possible values for the arguments in the predicate specification of foreign/[2,3]. The value declares which conversion between corresponding Prolog argument and C type will take place. Note that the term chars below refers to a list of character codes, rather than to one-char atoms.

Prolog: +integer
C: long
The argument should be a number. It is converted to a C long and passed to the C function.
Prolog: +float
C: double
The argument should be a number. It is converted to a C double and passed to the C function.
Prolog: +atom
C: SP_atom
The argument should be an atom. Its canonical representation is passed to the C function.
Prolog: +chars
C: char *
The argument should be a list of character codes. The C function will be passed the address of an array with the encoded string representation of these characters. The array is subject to reuse by other support functions, so if the value is going to be used on a more than temporary basis, it must be moved elsewhere.
Prolog: +string
C: char *
The argument should be an atom. The C function will be passed the address of an encoded string representing the characters of the atom. The C function should not overwrite the string.
Prolog: +string(N)
C: char *
The argument should be an atom. The encoded string representing the atom will be copied into a newly allocated buffer. The string will be truncated (at a wide character boundary) if it is longer than N bytes. The string will be blank padded on the right if it is shorter than N bytes. The C function will be passed the address of the buffer. The C function may overwrite the buffer, but should not assume that it remains valid after returning.
Prolog: +address
C: void *
The argument should be an aligned pointer. The value passed will be a void * pointer.
Prolog: +address(TypeName)
C: TypeName *
The argument should be an aligned pointer. The value passed will be a TypeName * pointer.
Prolog: +term
C: SP_term_ref
The argument could be any term. The value passed will be the internal representation of the term.
Prolog: -integer
C: long *
The C function is passed a reference to an uninitialized long. The value returned will be converted to a Prolog integer.
Prolog: -float
C: double *
The C function is passed a reference to an uninitialized double. The value returned will be converted to a Prolog float.
Prolog: -atom
C: SP_atom *
The C function is passed a reference to an uninitialized SP_atom. The value returned should be the canonical representation of a Prolog atom.
Prolog: -chars
C: char **
The C function is passed the address of an uninitialized char *. The returned encoded string will be converted to a Prolog list of character codes.
Prolog: -string
C: char **
The C function is passed the address of an uninitialized char *. The returned encoded string will be converted to a Prolog atom. Prolog will copy the string to a safe place, so the memory occupied by the returned string may be reused during subsequent calls to foreign code.
Prolog: -string(N)
C: char *
The C function is passed a reference to a character buffer large enough to store N bytes. The C function is expected to fill the buffer with an encoded string of N bytes (not NULL-terminated). This encoded string will be stripped of trailing blanks and converted to a Prolog atom.
Prolog: -address
C: void **
The C function is passed the address of an uninitialized void *. The returned value should be an aligned pointer.
Prolog: -address(TypeName)
C: TypeName **
The C function is passed the address of an uninitialized TypeName *. The returned value should be an aligned pointer.
Prolog: -term
C: SP_term_ref
The C function is passed a new SP_term_ref, and is expected to set its value to a suitable Prolog term. Prolog will try to unify the value with the actual argument.
Prolog: [-integer]
C: long F()
The C function should return a long. The value returned will be converted to a Prolog integer.
Prolog: [-float]
C: double F()
The C function should return a double. The value returned will be converted to a Prolog float.
Prolog: [-atom]
C: SP_atom F()
The C function should return an SP_atom. The value returned must be the canonical representation of a Prolog atom.
Prolog: [-chars]
C: char *F()
The C function should return a char *. The returned encoded string will be converted to a Prolog list of character codes.
Prolog: [-string]
C: char *F()
The C function should return a char *. The returned encoded string will be converted to a Prolog atom. Prolog will copy the string to a safe place, so the memory occupied by the returned string may be reused during subsequent calls to foreign code.
Prolog: [-string(N)]
C: char *F()
The C function should return a char *. The first N bytes of the encoded string (not necessarily NULL-terminated) will be copied and the copied string will be stripped of trailing blanks. The stripped string will be converted to a Prolog atom. C may reuse or destroy the string buffer during later calls.
Prolog: [-address]
C: void *F()
The C function should return a void *. The returned value should be an aligned pointer. (see Creating Prolog Terms), will be converted to a Prolog integer.
Prolog: [-address(TypeName)]
C: TypeName *F()
The C function should return a TypeName *. The returned value should be an aligned pointer.
Prolog: [-term]
C: SP_term_ref F()
The C function should return a SP_term_ref. Prolog will try to unify its value with the actual argument.


Node:Interface Predicates, Next:, Previous:Conversions, Up:Calling C

Interface Predicates


load_foreign_resource(:Resource)

Unless a foreign resource with the same name as Resource has been statically linked, the linked foreign resource specified by Resource is linked into the Prolog load image. In both cases, the predicates defined by Resource are installed, and any init function is called. Dynamic linking is not possible if the foreign resource was linked using the static option.

If a resource with the same name has been previously loaded, it will be unloaded, as if unload_foreign_resource(Resource) were called, before Resource is loaded.

unload_foreign_resource(:Resource)

Any deinit function associated with Resource is called, and the predicates defined by Resource are uninstalled. If Resource has been dynamically linked, it is unlinked from the Prolog load image.

NOTE: all foreign resources are unloaded before Prolog exits. This implies that the C library function atexit(func) cannot be used if func is defined in a dynamically linked foreign resource.

The following predicates are provided for backwards compatibility and should be avoided in new code:

foreign_file(+File,+Functions) [Hook,Obsolescent]

Specifies that a set of foreign functions, to be called from Prolog, are to be found in File. This predicate is only called from load_foreign_files/2.

load_foreign_files(:ObjectFiles,+Libraries) [Hookable,Obsolescent]

A resource name is derived from the first file name in ObjectFiles by stripping off the suffix. If this resource has been statically linked, the predicates defined by it are installed; otherwise, a linked foreign resource containing the declared functions is created and loaded. Not available in runtime systems.


Node:The Foreign Resource Linker, Next:, Previous:Interface Predicates, Up:Calling C

The Foreign Resource Linker

The foreign resource linker, splfr, is used for creating foreign resources (see Foreign Resources). splfr reads terms from a Prolog file, applying op declarations and extracting any foreign_resource/2 fact with first argument matching the resource name and all foreign/[2,3] facts. Based on this information, it generates the necessary glue code, and combines it with any additional C or object files provided by the user into a linked foreign resource. The output filename will be the resource name with a suitable extension. splfr is invoked as

% splfr [ Option | InputFile ] ...

The input to splfr can be divided into Options and InputFiles and they can be arbitrarily mixed on the command line. Anything not interpreted as an option will be interpreted as an input file. Exactly one of the input files should be a Prolog file. The following options are available:

--help
-v
--verbose
--version
--config=ConfigFile
--cflag=CFlag
-LD
--sicstus=Executable
--with_jdk=DIR
--with_tcltk=DIR
--with_tcl=DIR
--with_tk=DIR
--with_bdb=DIR
--keep
These are treated the same as for the spld tool. See The Application Builder, for details.
--resource=ResourceName
Specify the resource's name. This defaults to the basename of the Prolog source file found on the command line.
-o, --output=OutputFileName
Specify output file-name. This defaults to the name of the resource, suffixed with the platform's standard shared object suffix (i.e. .so on most UNIX dialects, .dll under Windows). The use of this option is discouraged, except to change the output directory.
--manual
Do not generate any glue code. This option can only be used when the interface code is generated manually as described in Runtime Utilities. You should probably not use this option.
-S
--static
Create a statically linked foreign resource instead of a dynamically linked shared object (which is the default). A statically linked foreign resource is a single object file which can be pre-linked into a Prolog system. See also the spld tool, The Application Builder.
--no-rpath
On UNIX, the default is to embed into the shared object all linker library directories for use by the dynamic linker. For most UNIX linkers this corresponds to adding a -Rpath for each -Lpath. The --no-rpath option inihibits this.
--namebase=namebase
namebase will be used as part of the name of generated files. The default name base is the resource name (e.g. as specified with --resource). If --static is specified, the default namebase is the resource name followed by _s.
--header=headername
Specify the name of the generated header file. The default if is namebase_glue.h. All C files that define foreign functions or that call SICStus API functions should include this file. Among other things the generated header file includes prototypes corresponding to the foreign/3 declarations in the prolog code.
--nocompile
Do not compile, just generate code. This may be useful in Makefiles, for example to generate the header file in a separate step.
--multi-sp-aware
--exclusive-access
--context-hook=name
--no-context-hook
Specifies various degrees of support for more than one SICStus in the same process. See Foreign Resources and Multiple SICStus Run-Times, for details.

The key input to splfr is the SourceFile. The contents of this file determines how the foreign resource's interface will look like. When the source-file is read in, foreign_resource/2 facts with first argument matching the name of this resource (i.e. ResourceName) is extracted together with all foreign/[2,3] facts.


Node:Init and Deinit Functions, Next:, Previous:The Foreign Resource Linker, Up:Calling C

Init and Deinit Functions

An init function and/or a deinit function can be declared by foreign_resource/2. If this is the case, these functions should have the prototype:

void FunctionName (int when)

The init function is called by load_foreign_resource/1 after the resource has been loaded and the interfaced predicates have been installed.

The deinit function is called by unload_foreign_resource/1 before the interfaced predicates have been uninstalled and the resource has been unloaded.

The init and deinit functions may use the C-interface to call Prolog etc.

Foreign resources are unloaded before saving states, and reloaded afterwards or when the saved state is restored; see Saving. Foreign resources are also unloaded when exiting Prolog execution. The parameter when reflects the context of the (un)load_foreign_resource/1 and is set as follows for init functions:

SP_WHEN_EXPLICIT
Explicit call to load_foreign_resource/1.
SP_WHEN_RESTORE
Resource is reloaded after save or restore.

For deinit functions:

SP_WHEN_EXPLICIT
Explicit call to unload_foreign_resource/1.
SP_WHEN_SAVE
Resource is unloaded before save.
SP_WHEN_EXIT
Resource is unloaded before exiting Prolog.


Node:Creating the Linked Foreign Resource, Next:, Previous:Init and Deinit Functions, Up:Calling C

Creating the Linked Foreign Resource

Suppose we have a Prolog source file ex.pl containing:

foreign(f1, p1(+integer,[-integer])).
foreign(f2, p2(+integer,[-integer])).
foreign_resource(ex, [f1,f2]).
:- load_foreign_resource(ex).

and a C source file ex.c with definitions of the functions f1 and f2, both returning long and having a long as only parameter. The conversion declarations in ex.pl state that these functions form the foreign resource ex.

To create the linked foreign resource, simply type (to the Shell):

% splfr ex.pl ex.c

The linked foreign resource ex.so (file suffix .so is system dependent) has been created. It will be dynamically linked by the directive :- load_foreign_resource(ex). when the file ex.pl is loaded. Linked foreign resources can also be created manually (see Runtime Utilities).

Dynamic linking of foreign resources can also be used by Runtime Systems. On some platforms, however, the executable must not be stripped for dynamic linking to work, i.e. its symbol table must remain.


Node:A Simpler Way to Call C, Previous:Creating the Linked Foreign Resource, Up:Calling C

A Simpler Way to Define C Predicates

SP_define_c_predicate defines a Prolog predicate such that when the Prolog predicate is called it will call a C function with a term corresponding to the Prolog goal. The arguments to the predicate can then be examined using the usual term access functions, e.g. SP_get_arg (see Accessing Prolog Terms).

typedef int SP_CPredFun(SP_term_ref goal, void *stash);
int SP_define_c_predicate(char *name, int arity, char *module,
                          SP_CPredFun *proc, void *stash)

The Prolog predicate module:name/arity will be defined (the module module must already exist). The stash argument can be anything and is simply passed as the second argument to the C function proc.

The C function should return SP_SUCCESS for success and SP_FAILURE for failure. The C function may also use SP_fail or SP_raise_exception in which case the return value will be ignored.

static int square_it(SP_term_ref goal, void *stash)
{
        long arg1;
        SP_term_ref tmp = SP_new_term_ref();
        SP_term_ref square_term = SP_new_term_ref();
        long the_square;

        /* goal will be a term like square(42,X) */
        if (!SP_get_arg(1,goal,tmp)) /* extract first arg */
           return SP_FAILURE;   /* should not happen */
        if (!SP_get_integer(tmp,&arg1))
           return SP_FAILURE;   /* arg 1 not an integer */

        SP_put_integer(square_term, arg1*arg1);
        SP_get_arg(2,goal,tmp); /* extract second arg */

        /* Unify output argument.
           SP_put_integer(tmp,...) would *not* work!
         */
        if (SP_unify(tmp, square_term))
           return SP_SUCCESS;
        else
           return SP_FAILURE;
}


...
/* Install square_it as user:square/2 */
SP_define_c_predicate("square", 2, "user", square_it, NULL /* unused */);
...


Node:Support, Next:, Previous:Calling C, Up:Mixing C and Prolog

Support Functions

The support functions include functions to manipulate SP_term_refs, functions to convert data between the basic C types and Prolog terms, functions to test whether a term can be converted to a specific C type, and functions to unify or compare two terms.


Node:Creating and Manipulating SP_term_refs, Next:, Previous:Support, Up:Support

Creating and Manipulating SP_term_refs

Normally, C functions only have indirect access to Prolog terms via SP_term_refs. C functions may receive arguments as unconverted Prolog terms, in which case the actual arguments received will have the type SP_term_ref. Also, a C function may return an unconverted Prolog term, in which case it must create an SP_term_ref. Finally, any temporary Prolog terms created by C code must be handled as SP_term_refs.

SP_term_refs are motivated by the fact that SICStus Prolog's memory manager must have a means of reaching all live Prolog terms for memory management purposes, including such terms that are being manipulated by the user's C code. Previous releases of SICStus Prolog provided direct access to Prolog terms and the ability to tell the memory manager that a given memory address points to a Prolog term, but this approach was too low level and highly error-prone. The current design is modeled after and largely compatible with Quintus Prolog release 3.

SP_term_refs are created dynamically. At any given time, an SP_term_ref has a value (a Prolog term, initially []). This value can be examined, accessed, and updated by the support functions described in this section.

It is important to understand the rules governing the scope of SP_term_refs in conjunction with calls from Prolog to C and vice versa:

See SPTerm and Memory, for a discussion (in the context of the Java interface) of the lifetime of term references.

A new SP_term_ref is created by calling:

SP_term_ref SP_new_term_ref(void)

The value of the SP_term_ref to is set to the value of the SP_term_ref from by calling SP_put_term(to,from). The previous value of to is lost:

void SP_put_term(SP_term_ref to, SP_term_ref from)
Each Prolog atom is represented internally by a unique integer, represented in C as an SP_atom. This mapping between atoms and integers depends on the execution history. Certain functions require this representation as opposed to an SP_term_ref. It can be obtained by a special argument type declaration when calling C from Prolog, by calling SP_get_atom(), or by looking up an encoded string s in the Prolog symbol table by calling SP_atom_from_string(s).
SP_atom SP_atom_from_string(char *s)

which returns the atom, or zero if the given string is malformed (is not a valid sequence of UTF-8 encoded characters).

The encoded string containing the characters of a Prolog atom a can be obtained by calling:

char *SP_string_from_atom(SP_atom a)

The length of the encoded string representing a Prolog atom a can be obtained by calling:

int SP_atom_length(SP_atom a)

Same as strlen(SP_string_from_atom(a), but runs in O(1) time.

Prolog atoms, and the space occupied by their print names, are subject to garbage collection when the number of atoms has reached a certain threshold, under the control of the agc_margin Prolog flag (see State Info), or when the atom garbage collector is called explicitly. The atom garbage collector will find all references to atoms from the Prolog specific memory areas, including SP_term_refs and arguments passed from Prolog to foreign language functions. However, atoms created by SP_atom_from_string and merely stored in a local variable are endangered by garbage collection. The following functions make it possible to protect an atom while it is in use. The operations are implemented using reference counters to cater for multiple, independent use of the same atom in different foreign resources:

int SP_register_atom(SP_atom a)

Registers the atom a with the Prolog memory manager by incrementing its reference counter. Returns a nonzero value if the operation succeeds.

int SP_unregister_atom(SP_atom a)

Unregisters the atom a with the Prolog memory manager by decrementing its reference counter. Returns a nonzero value if the operation succeeds.


Node:Creating Prolog Terms, Next:, Previous:Creating and Manipulating SP_term_refs, Up:Support

Creating Prolog Terms

These functions create a term and store it as the value of an SP_term_ref, which must exist prior to the call. They return zero if the conversion fails (as far as failure can be detected), and a nonzero value otherwise, assigning to t the converted value. Note that here, the term chars refers to a list of character codes, rather than to one-char atoms:


int SP_read_from_string(SP_term_ref t, const char*string, SP_term_ref vals[])
Assigns to t the result of reading a term from the its textual representation string. Variables that occur in the term are bound to the corresponding term in val.

The SP_term_ref vector val is terminated by 0 (zero). val may be NULL, this is treated as an empty vector.

The variables in the term are ordered according to their first occurence during a depth first traversal in increasing argument order. That is, the same order as used by terms:term_variables_bag/2 (see Term Utilities). Variables that do not have a corresponding entry in vals are ignored. Entries in vals that do not correspond to a variable in the term are ignored.

The string should be encoded using the internal encoding of SICStus Prolog, the UTF-8 encoding (see WCX Concepts).

This example creates the term foo(X,42,42,X) (without error checking):

SP_term_ref x = SP_new_term_ref();
SP_term_ref y = SP_new_term_ref();
SP_term_ref term = SP_new_term_ref();
SP_term_ref vals[] = {x,y,x, 0/* zero termination */};

SP_put_variable(x);
SP_put_integer(y,42);

SP_read_from_string(term, "foo(A,B,B,C).", vals);
/* A corresponds to vals[0] (x), B to vals[1] (y), C to vals[2] (x).
   A and C therefore both are bound to the variable referred to by x.
   B is bound to the term referred to by y (42). So term refer to a
   term foo(X,42,42,X).
*/

See Calling Prolog, for an example of using SP_read_from_string to call an arbitrary Prolog goal.

int SP_put_variable(SP_term_ref t)
Assigns to t a new Prolog variable.
int SP_put_integer(SP_term_ref t, long l)
Assigns to t a Prolog integer from a C long integer.
int SP_put_float(SP_term_ref t, double d)
Assigns to t a Prolog float from a C double.
int SP_put_atom(SP_term_ref t, SP_atom a)
Assigns to t a Prolog atom from a, which must be the canonical representation of a Prolog atom. (see Calling C).
int SP_put_string(SP_term_ref t, char *name)
Assigns to t a Prolog atom from a encoded C string.
int SP_put_address(SP_term_ref t, void *pointer)
Assigns to t a Prolog integer representing an aligned pointer.
int SP_put_list_chars(SP_term_ref t, SP_term_ref tail, char *s)
Assigns to t a Prolog list of the character codes represented by the encoded string s, prepended to the value of tail.
int SP_put_list_n_chars(SP_term_ref t, SP_term_ref tail, long n, char *s)
Assigns to t a Prolog list of the character codes represented by the first n bytes in encoded string s, prepended in front of the value of tail.
int SP_put_number_chars(SP_term_ref t, char *s)
Assigns to t a Prolog number by parsing the string in s.
int SP_put_functor(SP_term_ref t, SP_atom name, int arity)
Assigns to t a Prolog compound term with all the arguments unbound variables. If arity is 0, assigns the Prolog atom whose canonical representation is name to t. This is similar to calling functor/3 with the first argument unbound and the second and third arguments bound to an atom and an integer, respectively.
int SP_put_list(SP_term_ref t)
Assigns to t a Prolog list whose head and tail are both unbound variables.
int SP_cons_functor(SP_term_ref t, SP_atom name, int arity, SP_term_ref arg, ...)
Assigns to t a Prolog compound term whose arguments are the values of arg... If arity is 0, assigns the Prolog atom whose canonical representation is name to t. This is similar to calling =../2 with the first argument unbound and the second argument bound.
int SP_cons_list(SP_term_ref t, SP_term_ref head, SP_term_ref tail)
Assigns to t a Prolog list whose head and tail are the values of head and tail.


Node:Accessing Prolog Terms, Next:, Previous:Creating Prolog Terms, Up:Support

Accessing Prolog Terms

These functions will take an SP_term_ref and convert it to C data. They return zero if the conversion fails, and a nonzero value otherwise, and (except the last two) store the C data in output arguments. Note that here, the term chars refers to a list of character codes, rather than to one-char atoms:

int SP_get_integer(SP_term_ref t, long *l)
Assigns to *l the C long corresponding to a Prolog number. The value must fit in *l for the operation to succeed. For numbers too large to fit in a long you can use SP_get_number_chars, below.
int SP_get_float(SP_term_ref t, double *d)
Assigns to *d the C double corresponding to a Prolog number.
int SP_get_atom(SP_term_ref t, SP_atom *a)
Assigns to *a the canonical representation of a Prolog atom.
int SP_get_string(SP_term_ref t, char **name)
Assigns to *name a pointer to the encoded string representing the name of a Prolog atom. This string must not be modified.
int SP_get_address(SP_term_ref t, void **pointer)
Assigns to *pointer a C pointer from a Prolog term, which must represent an aligned pointer.
int SP_get_list_chars(SP_term_ref t, char **s)
Assigns to *s a zero-terminated array containing an encoded string which corresponds to the given Prolog list of character codes. The array is subject to reuse by other support functions, so if the value is going to be used on a more than temporary basis, it must be moved elsewhere.
int SP_get_list_n_chars(SP_term_ref t, SP_term_ref tail, long n, long *w, char *s)
Copies into s the encoded string representing the character codes in the initial elements of list t, so that at most n bytes are used. The number of bytes actually written is assigned to *w. tail is set to the remainder of the list. The array s must have room for at least n bytes.
int SP_get_number_chars(SP_term_ref t, char **s)
Assigns to *s a zero-terminated array of characters corresponding to the printed representation of a Prolog number. The array is subject to reuse by other support functions, so if the value is going to be used on a more than temporary basis, it must be moved elsewhere.
int SP_get_functor(SP_term_ref t, SP_atom *name, int *arity)
Assigns to *name and *arity the canonical representation and arity of the principal functor of a Prolog compound term. If the value of t is an atom, then that atom is assigned to *name and 0 is assigned to *arity. This is similar to calling functor/3 with the first argument bound to a compound term or an atom and the second and third arguments unbound.
int SP_get_list(SP_term_ref t, SP_term_ref head, SP_term_ref tail)
Assigns to head and tail the head and tail of a Prolog list.
int SP_get_arg(int i, SP_term_ref t, SP_term_ref arg)
Assigns to arg the i:th argument of a Prolog compound term. This is similar to calling arg/3 with the third argument unbound.


Node:Testing Prolog Terms, Next:, Previous:Accessing Prolog Terms, Up:Support

Testing Prolog Terms

There is one general function for type testing of Prolog terms and a set of specialized, more efficient, functions, one for each term type:

int SP_term_type(SP_term_ref t)
Depending on the type of the term t, one of SP_TYPE_VARIABLE, SP_TYPE_INTEGER, SP_TYPE_FLOAT, SP_TYPE_ATOM, or SP_TYPE_COMPOUND is returned.
int SP_is_variable(SP_term_ref t)
Returns nonzero if the term is a Prolog variable, zero otherwise.
int SP_is_integer(SP_term_ref t)
Returns nonzero if the term is a Prolog integer, zero otherwise.
int SP_is_float(SP_term_ref t)
Returns nonzero if the term is a Prolog float, zero otherwise.
int SP_is_atom(SP_term_ref t)
Returns nonzero if the term is a Prolog atom, zero otherwise.
int SP_is_compound(SP_term_ref t)
Returns nonzero if the term is a Prolog compound term, zero otherwise.
int SP_is_list(SP_term_ref t)
Returns nonzero if the term is a Prolog list, zero otherwise. Note that only the principal functor matters: the function returns zero if the term is the empty list, and nonzero if it's a non-strict list.
int SP_is_atomic(SP_term_ref t)
Returns nonzero if the term is an atomic Prolog term, zero otherwise.
int SP_is_number(SP_term_ref t)
Returns nonzero if the term is a Prolog number, zero otherwise.


Node:Unifying and Comparing Terms, Next:, Previous:Testing Prolog Terms, Up:Support

Unifying and Comparing Terms

int SP_unify(SP_term_ref x, SP_term_ref y)
Unifies two terms, returning zero on failure and nonzero on success.
int SP_compare(SP_term_ref x, SP_term_ref y)
Returns -1 if x @< y, 0 if x == y and 1 if x @> y


Node:Operating System Services, Next:, Previous:Unifying and Comparing Terms, Up:Support

Operating System Services

Memory Allocation

The standard C library memory allocation functions (malloc, calloc, realloc, and free) are available in foreign code, but cannot reuse any free memory that SICStus Prolog's memory manager may have available, and so may contribute to memory fragmentation. Furthermore, the C library functions may return values that are not aligned pointers, something which many functions of the foreign language interface require.

The following functions provide the same services via SICStus Prolog's memory manager. All pointers returned are aligned.

void * SP_malloc(unsigned int size)
Returns a pointer to a block of at least size bytes.
void * SP_calloc(unsigned int nmemb, unsigned size)

Returns a pointer to a block of at least size * nemb. The first size * nmemb bytes are set to zero.

void * SP_realloc(void *ptr, unsigned int size)
Changes the size of the block referenced by ptr to size bytes and returns a pointer to the (possibly moved) block. The contents will be unchanged up to the lesser of the new and old sizes. The block referenced by ptr must have been obtained by a call to SP_malloc or SP_realloc, and must not have been released by a call to SP_free or SP_realloc.
void SP_free(void *ptr)
Releases the block referenced by ptr, which must have been obtained by a call to SP_malloc or SP_realloc, and must not have been released by a call to SP_free or SP_realloc.
char * SP_strdup(const char *str)

Returns a pointer to a new string which is a duplicate of the string pointer to by str. The memory for the new string is allocated using SP_malloc().

File System

SICStus Prolog caches the name of the current working directory. To take advantage of the cache and to keep it consistent, foreign code should call the following interface functions instead of calling chdir() and getcwd() directly:

int SP_chdir(const char *path)
Cause a directory pointed to by path to become the current working directory. Returns 0 upon successful completion. Otherwise, a value of -1 is returned and errno is set to indicate the error.
char *SP_getcwd(char *buf, unsigned int size);

Returns a pointer to the current directory pathname. If buf is not NULL, the pathname will be stored in the space pointed to by buf. If buf is a NULL pointer, size bytes of space will be obtained using SP_malloc(). In this case, the pointer returned may be used as the argument in a subsequent call to SP_free(). Returns NULL with errno set if size is not large enough to store the pathname.

Threads

When running more that one SICStus run-time in the same process it is often necessary to protect data with mutual exclusion locks. The following functions implement recursive mutual exclusion locks which only need static initialization.

Note that the SICStus run-time is not thread safe in general.

typedef ... SP_mutex;
#define SP_MUTEX_INITIALIZER ...

int SP_mutex_lock(SP_mutex *pmx);
int SP_mutex_unlock(SP_mutex *pmx);

A (recursive) mutual exclusion lock is declared as type SP_mutex. It should be initialized to (the static initializer) SP_MUTEX_INITIALIZER before use.

SP_mutex_lock locks the mutex. SP_mutex_lock returns zero on error, non-zero on success.

SP_mutex_unlock unlocks the mutex. It returns zero on error, non-zero on success. The number of unlocks must match the number of locks and only the thread that performed the lock can unlock the mutex. SP_mutex_unlock returns zero on error, non-zero on success.

...
static SP_mutex volatile my_mutex = SP_MUTEX_INITIALIZER;
/* only access this counter with my_mutex locked */
int volatile protected_counter = 0;

/* returns the new value of protected_counter */
int increment_the_counter(void)
{
  int new_value;

  if(SP_mutex_lock(&my_mutex) == 0) goto error_handling;
  /* No other thread can update protected_counter here */
  new_value = protected_counter+1;
  protected_counter = new_value;
  if (SP_mutex_unlock(&my_mutex) == 0) goto error_handling;
  return new_value;

error_handling:
  ...
}


Node:Miscellaneous C API Functions, Previous:Operating System Services, Up:Support

Miscellaneous

A dynamic foreign resource that is used by multiple SICStus run-times in the same process may need to maintain a global state that is kept separate for each SICStus run-time. Each SICStus run-time maintains a location (containing a void*) for each foreign resource. A foreign resource can then access this location to store any data that is specific to the calling SICStus run-time.

void **SP_foreign_stash(void)

You can use SP_foreign_stash() to get access to a location, initially set to NULL, where the foreign resource can store a void*. Typically this would be a pointer to a C struct that holds all information that need to be stored in global variables. This struct can be allocated and initialized by the foreign resource initialization function, it should be deallocated by the foreign resource deinitialization function.

SP_foreign_stash is only available for use in dynamic foreign resources. The value returned by SP_foreign_stash is only valid until the next SICStus API call. The correct way to initialize the location pointed at by SP_foreign_stash is therefore:

struct my_state {...};

init_my_foreign_resource(...)
{
   struct my_state *p = SP_malloc(sizeof(struct my_state));
   (*SP_foreign_stash()) = (void*)p;
}

The following example is incorrect; SP_malloc may be called between the time SP_foreign_stash is called and the time its return value is used:

/* WRONG */
(*SP_foreign_stash()) = SP_malloc(sizeof(struct my_state));

SP_foreign_stash is currently a C macro, not a function. You should not rely on this.


Node:Calling Prolog, Next:, Previous:Support, Up:Mixing C and Prolog

Calling Prolog from C

In development and runtime systems alike, Prolog and C code may call each other to arbitrary depths.

Before calling a predicate from C you must look up the predicate definition by module, name, and arity. The function SP_predicate() will return a pointer to this definition or return NULL if the predicate is not visible in the module. This definition could be used in more than one call to the same predicate. The module specification is optional. If NULL or "" (the empty string) is given, then the default type-in module (see Module Spec) is assumed:

SP_pred_ref SP_predicate(char *name_string,
                         long arity,
                         char *module_string)

Note that the first and third arguments point to encoded strings, representing the characters of the predicate and module name.

The function SP_pred() may be used as an alternative to the above. The only difference is that the name and module arguments are passed as Prolog atoms rather than strings, and the module argument is mandatory. This saves the cost of looking up the two arguments in the Prolog symbol table. This cost dominates the cost of SP_predicate():

SP_pred_ref SP_pred(SP_atom name_atom,
                    long arity,
                    SP_atom module_atom)


Node:Finding One Solution of a Call, Next:, Previous:Calling Prolog, Up:Calling Prolog

Finding One Solution of a Call

The easiest way to call a predicate if you are only interested in the first solution is to call the function SP_query(). It will create a goal from the predicate definition and the arguments, call it, and commit to the first solution found, if any.

Returns SP_SUCCESS if the goal succeeded, SP_FAILURE if it failed, and SP_ERROR if an error condition occurred. Only when the return value is SP_SUCCESS are the values in the query arguments valid, and will remain so until backtracking into any enclosing query:

int SP_query(SP_pred_ref predicate, SP_term_ref arg1, ...)

If you are only interested in the side effects of a predicate you can call SP_query_cut_fail(). It will try to prove the predicate, cut away the rest of the solutions, and finally fail. This will reclaim the storage used after the call, and throw away any solution found. The return values are the same as for SP_query.

int SP_query_cut_fail(SP_pred_ref predicate, SP_term_ref arg1, ...)


Node:Finding Multiple Solutions of a Call, Next:, Previous:Finding One Solution of a Call, Up:Calling Prolog

Finding Multiple Solutions of a Call

If you are interested in more than one solution a more complicated scheme is used. You find the predicate definition as abov, but you don't call the predicate directly.

  1. Set up a call with SP_open_query()
  2. Call SP_next_solution() to find a solution. Call this predicate again to find more solutions if there are any.
  3. Terminate the call with SP_close_query() or SP_cut_query()

The function SP_open_query() will return an identifier of type SP_qid that you use in successive calls, or 0, if given an invalid predicate reference. Note that if a new query is opened while another is already open, the new query must be terminated before exploring the solutions of the old one. That is, queries must be strictly nested:

SP_qid SP_open_query(SP_pred_ref predicate, SP_term_ref arg1, ...)

The function SP_next_solution() will cause the Prolog engine to backtrack over any current solution of an open query and look for a new one. The given argument must be the innermost query that is still open, i.e. it must not have been terminated explicitly by SP_close_query() or SP_cut_query() or implicitly by an unsuccessful call to SP_next_solution(). Returns SP_SUCCESS for success, SP_FAILURE for failure, SP_ERROR if an error condition occurred. Only when the return value is SP_SUCCESS are the values in the query arguments valid, and will remain so until backtracking into this query or an enclosing one:

int SP_next_solution(SP_qid query)

A query must be terminated in either of two ways. The function SP_cut_query() will discard the choices created since the corresponding SP_open_query(), like the goal !. The current solution is retained in the arguments until backtracking into any enclosing query. The given argument does not have to be the innermost open query; any open queries in its scope will also be cut. Returns SP_SUCCESS for success and SP_ERROR for invalid usage:

int SP_cut_query(SP_qid query)

Alternatively, the function SP_close_query() will discard the choices created since the corresponding SP_open_query(), and then backtrack into the query, throwing away any current solution, like the goal !, fail. The given argument does not have to be the innermost open query; any open queries in its scope will also be closed. Returns SP_SUCCESS for success and SP_ERROR for invalid usage:

int SP_close_query(SP_qid query)

A simple way to call arbitrary prolog code is to use SP_read_from_string (see Creating Prolog Terms) to create an argument to call/1. It is a good idea to always explicitly specify the module context when using call/1 or other meta predicates from C.

This example calls a compound goal (without error checking).

SP_pred_ref call_pred = SP_predicate("call", 1, "prolog");
SP_term_ref x = SP_new_term_ref();
SP_term_ref goal = SP_new_term_ref();
SP_term_ref vals[] = {x, 0 /* zero termination */};
long len;

SP_put_variable(x);
/* The X=_ is a trick to ensure that X is the first variable
   in the depth-first order and thus corresponds to vals[0] (x).
   There are no entries in vals for _,L1,L2.
*/
SP_read_from_string(goal,
   "user:(X=_, length([0,1,2],L1), length([3,4],L2), X is L1+L2).", vals);

SP_query(call_pred, goal);
SP_get_integer(x, &len);
/* here len is 5 */


Node:Calling Prolog Asynchronously, Next:, Previous:Finding Multiple Solutions of a Call, Up:Calling Prolog

Calling Prolog Asynchronously

If you wish to call Prolog back from a signal handler or a thread other than the thread that called SP_initialize, that is, the main thread, you cannot use SP_query() etc. directly. The call to Prolog has to be delayed until such time that the Prolog execution can accept an interrupt and the call has to be performed from the main thread (the Prolog execution thread). The function SP_event() serves this purpose, and installs the function func to be called from Prolog (in the main thread) when the execution can accept a callback. It returns non-zero if and only if installation succeeded. func is called with arg as first argument.

A queue of functions, with corresponding arguments, is maintained; that is, if several calls to SP_event() occur before Prolog can accept an interrupt, the functions are queued and executed in turn at the next possible opportunity. A func installed with SP_event() will not be called until SICStus is actually running. One way of ensuring that all pending functions installed with SP_event() are run is to call, from the main thread, some dummy goal, such as, SP_query_cut_fail(SP_predicate("true",0,"user")).

While SP_event() is safe to call from any thread, it is not safe to call from arbitrary signal handlers. If you want to call SP_event() when a signal is delivered, you need to install your signal handler with SP_signal() (see below).

Note that SP_event() is one of the very few functions in the SICStus API that can safely be called from another thread than the main thread.

Depending on the value returned from func, the interrupted Prolog execution will just continue (SP_SUCCESS) or backtrack (SP_FAILURE or SP_ERROR). An exception raised by func, using SP_raise_exception, will be processed in the interrupted Prolog execution. If func calls SP_fail or SP_raise_exception the return value from func is ignored and handled as if func returned SP_FAILURE or SP_ERROR, respectively. In case of failure or exception, the event queue is flushed.

It is generally not robust to let func raise an exception or fail. The reason is that not all Prolog code is written such that it gracefully handles being interrupted. If you want to interrupt some long-running Prolog code, it is better to let your code test a flag in some part of your code that is executed repeatedly.

int SP_event(int (*func)(void*), void *arg)


Node:Signal Handling, Previous:Calling Prolog Asynchronously, Up:Calling Prolog Asynchronously

Signal Handling

As noted above it is not possible to call, e.g., SP_query() or even SP_event() from an arbitrary signal handler. That is, from signal handlers installed with signal or sigaction. Instead you need to install the signal handler using SP_signal().

When the OS delivers a signal sig for which SP_signal(sig,func) has been called SICStus will not call func immediately. Instead the call to func will be delayed until it is safe for Prolog to do so, in much the same way that functions installed by SP_event are handled (this is an incompatible change from SICStus 3.8 and earlier).

Since the signal handling function func will not be called immediately upon delivery of the signal to the process it only makes sense to use SP_signal to handle certain asynchronous signals such as SIGINT, SIGUSR1, SIGUSR2. Other asynchronous signals handled specially by the OS, such as SIGCHLD are not suitable for handling via SP_signal. Note that the development system installs a handler for SIGINT, and, on Windows, SIGBREAK, to catch keyboard interrupts. On UNIX, library(timeout) currently uses SIGVTALRM.

When func is called it may only call other (non SICStus) C code and SP_event(). Note that func will be called in the main thread.

To install a function, func, as a handler for the signal sig, call:

typedef void SP_SigFun (int);
SP_SigFun SP_signal (int sig, SP_SigFun fun);

SP_signal returns SP_SIG_ERR on error. On success, SP_signal returns some unspecified value different from SP_SIG_ERR.

If fun is one of the special constants SP_SIG_IGN or SP_SIG_DFL, then one of two things happens. If a signal handler for sig has already been installed with SP_signal, then the SICStus OS-level signal handler is removed and replaced with, respectively, SIG_IGN or SIG_DFL. If a signal handler has not been installed with SP_signal, then SP_signal does nothing and returns SP_SIG_ERR.

A signal handler installed by a foreign resource should be uninstalled in the deinit function for the foreign resource. This is to prevent the handler in the foreign resource from being called after the code of the foreign resource has been unloaded (e.g. by unload_foreign_resource/1).

The following two functions were used prior to SICStus 3., but are obsolete now:

SP_SigFun SP_reinstall_signal (int sig, SP_SigFun)  [Obsolescent]
void SP_continue(void)  [Obsolescent]
they are no-ops.

The following piece of C code illustrates these facilities. The function signal_init() installs the function signal_handler() as the primary signal handler for the signals SIGUSR1 and SIGUSR2. That function invokes the predicate user:prolog_handler/1 as the actual signal handler, passing the signal number as an argument to the predicate.

SP_pred_ref event_pred;

static int signal_event(void *handle)
{
  int signal_no = (int) handle;
  SP_term_ref x=SP_new_term_ref();
  int rc;

  SP_put_integer(x, signal_no); /* Should not give an error */
  rc = SP_query(event_pred, x);
  if (rc == SP_ERROR && SP_exception_term(x))
    SP_raise_exception(x);        /* Propagate any raised exception */
  return rc;
}

static void signal_handler(int signal_no)
{
  SP_event(signal_event, (void *)signal_no);
  /* The two calls below are for SICStus 3.8 compatibility */
  SP_reinstall_signal(signal_no, signal_handler);
  SP_continue();
}

void signal_init(void)
{
  event_pred = SP_predicate("prolog_handler",1,"user");

  SP_signal(SIGUSR1, signal_handler);
  SP_signal(SIGUSR2, signal_handler);
}


Node:Exception Handling in C, Previous:Calling Prolog Asynchronously, Up:Calling Prolog

Exception Handling in C

When an exception has been raised, the functions SP_query(), SP_query_cut_fail() and SP_next_solution() return SP_ERROR. To access the exception term (the argument of the call to raise_exception/1), which is asserted when the exception is raised, the function SP_exception_term() is used. As a side effect, the exception term is retracted, so if your code wants to pass the exception term back to Prolog, it must use the SP_raise_exception() function below. If an exception term exists, SP_exception_term() retracts it and stores it as the value of an SP_term_ref which must exist prior to the call and returns nonzero. Otherwise, it returns zero:

int SP_exception_term(SP_term_ref t)

To raise an exception from a C function called from Prolog, just call SP_raise_exception(t) where t is the SP_term_ref whose value is the exception term. The glue code will detect that an exception has been raised, any value returned from the function will be ignored, and the exception will be passed back to Prolog:

void SP_raise_exception(SP_term_ref t)


Node:SICStus Streams, Next:, Previous:Calling Prolog, Up:Mixing C and Prolog

SICStus Streams

With the SICStus Prolog C interface, the user can define his/her own streams as well as from C read or write on the predefined streams. The stream interface is modeled after Quintus Prolog release 2. It provides:


Node:Prolog Streams, Next:, Previous:SICStus Streams, Up:SICStus Streams

Prolog Streams

From the Prolog level there is a unique number that identifies a stream. This identifier can be converted from/to a Prolog stream:

stream_code(+Stream,?StreamCode)
stream_code(?Stream,+StreamCode)

StreamCode is the C stream identifier (an integer) corresponding to the Prolog stream Stream. This predicate is only useful when streams are passed between Prolog and C. Note that StreamCode no longer has any relation to the file descriptor.

The StreamCode is a Prolog integer representing an aligned SP_stream * pointer.

To read or write on a Prolog stream from C, special versions of the most common standard C I/O functions are used:

int SP_getc(void)
int SP_fgetc(SP_stream *s)
void SP_putc(int c)
void SP_fputc(int c, SP_stream *s)

The above functions deliver or accept wide character codes.

void SP_puts(char *string)
void SP_fputs(char *string, SP_stream *s)
int SP_printf(char *format, ...)
int SP_fprintf(SP_stream *s, char *format, ...)
int SP_fflush(SP_stream *s)
int SP_fclose(SP_stream *s)

The above functions expect and deliver encoded strings in their char * and char ** arguments. Specifically, in the SP_printf() and SP_fprintf() functions, first the formatting operation will be performed. The resulting string will be assumed to be in internal encoding, and will then be output using the SP_puts() or SP_fputs() function (see below). This means, e.g. that the %c printf conversion specification can only be used for ASCII characters, and the strings included using a %s specification should also be ASCII strings, or already transformed to the encoded form.

The SP_puts() and SP_fputs() functions first convert their encoded string argument into a sequence of wide character codes, and then output these on the required stream according to the external encoding; see WCX Foreign Interface.

There following predefined streams are accessible from C:

SP_stdin
Standard input. Refers to the same stream as user_input in Prolog. Which stream is referenced by user_input is controlled by the flag user_input (see prolog_flag/3) .
SP_stdout
Standard output. Refers to the same stream as user_output in Prolog. Which stream is referenced by user_output is controlled by the flag user_output (see prolog_flag/3).
SP_stderr
Standard error. Refers to the same stream as user_error in Prolog. Which stream is referenced by user_error is controlled by the flag user_error (see prolog_flag/3).
SP_curin
Current input. It is initially set equal to SP_stdin. It can be changed with the predicates see/1 and set_input/1.
SP_curout
Current output. It is initially set equal to SP_stdout. It can be changed with the predicates tell/1 and set_output/1.

Note that these variables are read only. They are set but never read by the stream handling.


Node:Defining a New Stream, Next:, Previous:Prolog Streams, Up:SICStus Streams

Defining a New Stream

The following steps are required to define a new stream in C:


Node:Low Level I/O Functions, Next:, Previous:Defining a New Stream, Up:Defining a New Stream

Low Level I/O Functions

For each new stream the appropriate low level I/O functions have to be defined. Error handling, prompt handling and character counting is handled in a layer above these functions. They all operate on a user defined private data structure pointed out by user_handle in SP_stream.

User defined low level I/O functions may invoke Prolog code and use the support functions described in the other sections of this chapter.

int my_fgetc(void *handle)
Should return the character read or -1 on end of file.
int my_fputc(char c, void *handle)
Should write the character c and return the character written.
int my_flush(void *handle)
Should flush the (output) stream and return 0 on success, -1 on error.
int my_eof(void *handle)
Should return 1 on end of file, else 0.
void my_clrerr(void *handle)
Should reset the stream's error and EOF indicators.
int my_close(void *handle)
Should close the stream and return zero.


Node:Installing a New Stream, Next:, Previous:Low Level I/O Functions, Up:Defining a New Stream

Installing a New Stream

A new stream is made accessible to Prolog using one of the functions:

int SP_make_stream(
        void *handle,
        int (*sgetc)(),
        int (*sputc)(),
        int (*sflush)(),
        int (*seof)(),
        void (*sclrerr)(),
        int (*sclose)(),
        SP_stream **stream)

int SP_make_stream_context(
        void *handle,
        int (*sgetc)(),
        int (*sputc)(),
        int (*sflush)(),
        int (*seof)(),
        void (*sclrerr)(),
        int (*sclose)(),
        SP_stream **stream,
        SP_atom option,
        int context)

The functions return SP_SUCCESS on success and SP_ERROR for invalid usage, and will:

The handle pointer will be supplied as the handle argument in the calls to the low level functions.

A stream without a close function will be treated as not closable i.e. close/1 will not have any effect on it.

The SP_make_stream_context function has two additional arguments supplying information related to the handling of wide characters; see WCX Foreign Interface.


Node:The Internal Representation of a Prolog Stream, Previous:Installing a New Stream, Up:Defining a New Stream

Internal Representation

For most streams you don't have to know anything about the internal representatio, but there may be occasions when you have to set some fields manually or do some processing on all streams of a particular type. SICStus Prolog maintains a circular list of stream objects of type SP_stream.

SP_stream *backward;
SP_stream *forward;
Used for linking streams together. The insertion is done by SP_make_stream() and the deletion is done from the Prolog predicate close/1.
char *filename;
This field is set to the empty string, "", by SP_make_stream(). May be set to a suitable encoded string, provided the string will not be overwritten until the stream is closed.
unsigned long mode;
A bit vector that contains information about the access modes supported, if the stream is a TTY stream etc. It is not available to the user but the TTY property can be set by the function:
void SP_set_tty(SP_stream *s)

int fd;
The file descriptor if the stream is associated with a file, socket etc. Otherwise a negative integer.
void *user_handle;
This is the pointer to the user supplied private data for the stream. For example, in the case of SICStus Prolog predefined file streams the user_handle could be a pointer to the standard I/O FILE.

There is no standard way to tell if a stream is user defined. You have to save pointers to the streams created or check if one of the stream functions installed is user defined, i.e:

int is_my_stream(SP_stream *s)
{
  return (s->sclose == my_close);
}


Node:Hookable Standard Streams, Previous:Defining a New Stream, Up:SICStus Streams

Hookable Standard Streams

As of release 3.7, the standard I/O streams (input, output, and error) are hookable, i.e. the streams can be redefined by the user.

SP_UserStreamHook *SP_set_user_stream_hook(SP_UserStreamHook *hook)
Sets the user-stream hook to hook.
SP_UserStreamPostHook *SP_set_user_stream_post_hook(SP_UserStreamPostHook *hook)
Sets the user-stream post-hook to hook.

These hook functions must be called before SP_initialize() (see Initializing the Prolog Engine). In custom built development systems, they may be called in the hook function SU_initialize(). See The Application Builder.


Node:Writing User-stream Hooks, Next:, Previous:Hookable Standard Streams, Up:Hookable Standard Streams

Writing User-stream Hooks

The user-stream hook is, if defined, called during SP_initialize(). It has the following prototype:

SP_stream *user_stream_hook(int which)

If the hook is not defined, SICStus will attempt to open the standard TTY/console versions of these streams. If they are unavailable (such as for windowed executables under Windows), the result is undefined.

It is called three times, one for each stream. The which argument indicates which stream it is called for. The value of which is one of:

SP_STREAMHOOK_STDIN
Create stream for standard input.
SP_STREAMHOOK_STDOUT
Create stream for standard output.
SP_STREAMHOOK_STDERR
Create stream for standard error.

The hook should return a standard SICStus I/O stream, as described in Defining a New Stream.


Node:Writing User-stream Post-hooks, Next:, Previous:Writing User-stream Hooks, Up:Hookable Standard Streams

Writing User-stream Post-hooks

The user-stream post-hook is, if defined, called after all the streams have been defined, once for each of the three standard streams. It has a slightly different prototype:

void user_stream_post_hook(int which, SP_stream *str)

where str is a pointer to the corresponding SP_stream structure. There are no requirements as to what this hook must do; the default behavior is to do nothing at all.

The post-hook is intended to be used to do things which may require that all streams have been created.


Node:User-stream Hook Example, Previous:Writing User-stream Post-hooks, Up:Hookable Standard Streams

User-stream Hook Example

This section contains an example of how to create and install a set of user-streams.

The hook is set by calling SP_set_user_stream_hook() in the main program like this:

SP_set_user_stream_hook(user_strhook);

Remember: SP_set_user_stream_hook() and SP_set_user_stream_post_hook() must be called before SP_initialize().

The hook user_strhook() is defined like this:

SP_stream *user_strhook(int which)
{
  SP_stream *s;

  SP_make_stream(NULL, my_getc, my_putc, my_flush, my_eof, my_clrerr, NULL, &s);

  return s;
}

See Installing a New Stream for a description on the parameters to SP_make_stream().


Node:Hooks, Next:, Previous:SICStus Streams, Up:Mixing C and Prolog

Hooks

The user may define functions to be called at certain occasions by the Prolog system. This is accomplished by passing the functions as arguments to the following set-hook-functions. The functions can be removed by passing a NULL.

typedef int (SP_ReadHookProc) (int fd)
SP_ReadHookProc SP_set_read_hook (SP_ReadHookProc *) [Obsolescent]
The installed function is called before reading a character from fd provided it is associated with a terminal device. This function shall return nonzero when there is input available at fd. It is called repeatedly until it returns nonzero.

You should avoid the use of a read hook if possible. It is not possible to write a reliable read hook. The reason is that SICStus streams are typically based on C stdio streams (FILE*). Such streams can contain buffered data that is not accessible from the file descriptor. Using, e.g., select() can therefore block even though fgetc on the underlying FILE* would not block.

typedef void (SP_VoidFun) (void)
SP_VoidFun * SP_set_reinit_hook (SP_VoidFun *)
The installed function is called by the development system upon reinitialization. The call is made after SICStus Prolog's signal handler installation but before any initializations are run and the version banners are displayed. Calling Prolog from functions invoked through this hook is not supported. In recursive calls to Prolog from C, which includes all run-time systems, this hook is not used.
typedef void (SP_VoidFun) (void);
SP_VoidFun * SP_set_interrupt_hook (SP_VoidFun *)
The installed function is called on occasions like expansion of stacks, garbage collection and printouts, in order to yield control to special consoles etc., for interrupt checking. Calling Prolog from functions invoked through this hook is not supported.


Node:Stand-alone Executables, Next:, Previous:Hooks, Up:Mixing C and Prolog

Stand-alone Executables

So far we have only discussed foreign code as pieces of code loaded into a Prolog executable. This is often not the desired situation. Instead, people often want to create stand-alone executables, i.e. an application where Prolog is used as a component, accessed through the API described in the previous sections.


Node:Runtime Systems, Next:, Previous:Stand-alone Executables, Up:Stand-alone Executables

Runtime Systems

Stand-alone applications containing debugged Prolog code and destined for end-users are typically packaged as runtime systems. No SICStus license is needed by a runtime system. A runtime system has the following limitations:


Node:Runtime Systems on Target Machines, Next:, Previous:Runtime Systems, Up:Stand-alone Executables

Runtime Systems on Target Machines

When a runtime system is delivered to the end user, chances are that the user does not have an existing SICStus installation. To deliver such an executable, you need:

the executable
This is your executable program, usually created by spld (see The Application Builder).
the runtime kernel
This is a shared object or a DLL, usually $SP_PATH/../libsprt39.so under UNIX, or %SP_PATH%\..\sprt39.dll under Windows.
the runtime library
The saved state $SP_PATH/bin/sprt.sav contains the built-in predicates written in Prolog. It is restored into the program at runtime by the function SP_initialize().
your Prolog code
As a saved state, .po files, .ql, or source code (.pl files). They must be explicitly loaded by the program at runtime (see Loading Prolog Code).
your linked foreign resources
Any dynamically linked foreign resources, including any linked foreign resources for library modules which are located in $SP_PATH/library.

See Launching Runtime Systems on Target Machines, for more information about runtime systems on Target Machines.

It is also possible to package all the above components into a single executable file, an all-in-one executable. See All-in-one Executables.


Node:The Application Builder, Next:, Previous:Runtime Systems on Target Machines, Up:Stand-alone Executables

The Application Builder

The application builder, spld, is used for creating stand-alone executables. This tool replaces the scripts spmkrs and spmkds in previous versions of SICStus. It is invoked as:

% spld [ Option | InputFile ] ...

spld takes the files specified on the command line and combines them into an executable file, much like the UNIX ld or the Windows link commands.

The input to spld can be divided into Options and Files which can be arbitrarily mixed on the command line. Anything not interpreted as an option will be interpreted as an input file. Do not use spaces in any file or option passed to spld. On Windows you can use the short filename for files with space in their name. The following options are available:

--help
Prints out a summary of all options.
-v
--verbose
Print detailed information about each step in the compilation/linking sequence.
-vv
Be very verbose. Prints everything printed by --verbose, and switches on verbose flags (if possible) to the compiler and linker.
--version
Prints out the version number of spld and exits successfully.
-o
--output=filename
Specify output filename. The default depends on the linker (e.g. a.out on UNIX systems).
-D
--development
Create a development system (with top-level, debugger, compiler, etc.). The default is to create a runtime system. Implies --main=prolog.
--main=type
runtime_entry(+Message) [Hook]
user:runtime_entry(+Message)
Specify what the executable should do upon startup. The possible values are prolog, user, restore and load.

prolog
Implies -D. The executable will start the Prolog top-level. This is the default if -D is specified and no .sav, .pl, .po, or .ql files are specified.
user
The user supplies his/her own main-program by including C-code (object file or source) which defines a function user_main(). This option is not compatible with -D. See User-defined Main Programs.
restore
The executable will restore a saved-state created by save_program/[1,2]. This is the default if a .sav file is found among Files. It is only meaningful to specify one .sav file. If it was created by save_program/2, the given startup goal is run. Then the executable will any Prolog code specified on the command line. Finally, the goal user:runtime_entry(start) is run. The executable exits with 0 upon normal temination and with 1 on failure or exception. Not compatible with -D.
load
The executable will load any Prolog code specified on the command line, i.e. files with extension .pl, .po or .ql. This is the default if there are .pl, .po or .ql but no .sav files among Files. Finally, the goal user:runtime_entry(start) is run. The executable exits with 0 upon normal temination and with 1 on failure or exception. Not compatible with -D. Note that this is almost like --main==restore except that no saved state will be restored before loading the other files.
none
No main function is generated. The main function must be supplied in one of the user supplied files. Not compatible with -D.

--window
Win32 only. Create a windowed executable. A console window will be opened and connected to the Prolog standard streams. If --main=user is specified, user_main() should not set the user-stream hooks. C/C++ source code files specified on the command-line will be compiled with -DSP_WIN=1 if this option is given.
--moveable

Under UNIX, paths are normally hardcoded into executables in order for them to find the SICStus libraries and bootfiles. Two paths are normally hardcoded; the value of SP_PATH and, where possible, the runtime library search path using the -R linker option (or equivalent). If the linker does not support the -R flag (or an equivalent), a wrapper script is generated instead which sets LD_LIBRARY_PATH (or equivalent).

The --moveable option turns off this behavior, so the executable is not dependent on SICStus being installed in a specific place. On some platforms the executable can figure out where it is located and so can locate any files it need, e.g. using SP_APP_DIR and SP_RT_DIR. On some UNIX platforms, however, this is not possible. In these cases, if this flag is given, the executable will rely on environment variables (SP_PATH (see Environment Variables) and LD_LIBRARY_PATH, etc.) to find all relevant files.

Under Windows, this option is always on, since Windows applications do no need to hardcode paths in order for them to find out where they're installed. See Launching Runtime Systems on Target Machines, for more information on how SICStus locates its libraries and bootfiles.

-S
--static
Prefer static linking over dynamic. When --static is specified, spld will try to use static (not shared) versions of libraries and object-files. This option can be used to minimize runtime dependencies on shared libraries/object-files. In particular, a static version of the SICStus run-time will be used and any SICStus foreign resources specified with --resources will be statically linked with the executable. In addition, --static implies --embed-rt-sav.

Under UNIX, even if there is a static version of a library (such as for example Tcl/Tk (libtcl8.0.a), spld may still use the dynamic version (libtcl8.0.so). This is because there is no portable way of telling the linker to prefer static libraries over shared, it is usually only possible to link statically or dynamically; the modes are usually exclusive. In this case, spld will go with the linker's default, which is usually dynamic. If you are in a situation where you would want spld to use a static library instead of a dynamic one, you will have to hack into spld's configuration file spconfig-version (normally located in <installdir>/bin). We recommend that you make a copy of the configuration file and specify the new configuration file using --config=<file>. A typical modification of the configuration file for this purpose may look like:

[...]
TCLLIB=-Bstatic -L/usr/local/lib -ltk8.0 -ltcl8.0 -Bdynamic
[...]
Use the new configuration file by typing
% spld [...] -S --config=/home/joe/hacked_spldconfig [...]

--shared
Create a shared library runtime system instead of an ordinary executable. Not compatible with --static. Implies --main=none.

Not supported on all platforms.

--resources=ResourceList
ResourceList is a comma-separated list of resource names, describing which resources should be pre-linked with the executable. Names can be either simple resource names, for example tcltk, or they can be complete paths to a foreign resource (with or without extensions). Example
% spld [...] --resources=tcltk,clpfd,/home/joe/foobar.so
This will cause library(tcltk), library(clpfd), and /home/joe/foobar.so to be pre-linked with the executable. See also the option --respath below.

It is also possible to embed a data resource, that is, the contents of an arbitrary data file that can be accessed at run-time.

It is possible to embed any kind of dat, but, currently, only restore/1 knows about data resources. For this reason it only makes sense to embed .sav files.

The primary reason to embed files within the executable is to create an all-in-one executable, that is, an executable file that does not depend on any other files and that therefore is easy to run on machines without SICStus installed. See All-in-one Executables, for more information.

--respath=Path
Specify additional paths used for searching for resources. Path is a list of search-paths, colon separated on Unix, semicolon separated on Windows. spld will always search the default library directory as a last resort, so if this option is not specified, only the default resources will be found. See also the --resources option above.
--config=ConfigFile
Specify another configuration file. This option is not intended for normal use. The filename may not contain spaces.
--cflag=CFlag
CFlag is a comma-separated list of options to send to the C-compiler. Any commas in the list will be replaced by spaces. This option can occur multiple times.
-LD
Do not process the rest of the command-line, but send it directly to the compiler/linker. Syntactic sugar for --cflag.
--sicstus=Executable
spld relies on using SICStus during some stages of its execution. The default is the SICStus-executable installed with the distribution. Executable can be used to override this, in case the user wants to use another SICStus executable.
--interactive
-i
Only applicable with --main=load or --main=restore. Calls SP_force_interactive() (see Initializing the Prolog Engine) before initializing SICStus.
--memhook=hook
Corresponds to SP_set_memalloc_hooks(MM_USE_hook,...). hook can be one of default, sbrk, malloc or sparse, corresponding respectively to MM_USE_DEFAULT, MM_USE_SBRK, MM_USE_MALLOC and MM_USE_SPARSE. This option can only be used with --main=load and --main=restore.
--lang=Dialect
Corresponds to prolog_flag(language,_,Dialect). Dialect can be one of iso or sicstus. The language mode is set before restoring or loading any argument files. This option can only be used with --main=load and --main=restore.
--userhook
This option enables you to define your own version of the SU_initialize() function. SU_initialize() is called by the main program before SP_initialize(). Its purpose is to call interface functions which must be called before SP_initialize(), such as SP_set_memalloc_hooks(). It is not meaningful to specify this option if --main=user or --main=none is given.

SU_initialize() should be defined as:

int SU_initialize(int argc, char *argv[])
The contents of argv should not be modified. SU_initialize() should return 0 for success and non-zero for failure. If a non-zero value is returned, the development system exits with the return value as error code.
--with_jdk=DIR
--with_tcltk=DIR
--with_tcl=DIR
--with_tk=DIR
--with_bdb=DIR
Specify the installation path for external (third-party) software. This is mostly useful on Windows. Under UNIX, the installation script manages this automatically.
--keep
Keep temporary files and interface code and rename them to human-readable names. Not intended for the casual user, but useful if you want to know exactly what code is generated.
--namebase=namebase
Use namebase to construct the name of generated files. This defaults to spldgen_ or, if --static is specified, spldgen_s_.
--embed-rt-sav
--no-embed-rt-sav
--embed-rt-sav will embed the SICStus run-time .sav file into the executable. This is off by default unless --static is specified. It can be forced on (off) by specifying --embed-rt-sav (--no-embed-rt-sav).
--multi-sp-aware
Compile the application with support for using more than one SICStus run-time in the same process. Not compatible with --static or pre-liked foreign resources. See Multiple SICStus Run-Times in C, for details.

Arguments to spld which are not recognized as options are assumed to be input-files and are handled as follows:

*.pl
*.po
*.ql
These are interpreted as names of files containing Prolog code and will be passed to SP_load() at run-time (if --main is load or restore. If the intention is to make an executable that works independently of the run-time working directory, avoid relative filenames. Instead use absolute filenames, SP_APP_DIR or embed a .sav file as a data resource, using --resource.
*.sav
These are interpreted as names of files containing saved states and will be passed to SP_restore() at run-time if --main=restore is specified, subject to the above caveat about relative filenames.

It is not meaningful to give more than one .sav argument.

*.so
*.sl
*.s.o
*.o
*.obj
*.dll
*.lib
*.dylib
These files are assumed to be input-files to the linker and will be passed on unmodified.
*.c
*.cc
*.C
*.cpp
*.c++
These files are assumed to be C/C++ source code and will be compiled by the C/C++-compiler before being passed to the linker.

If an argument is still not recognized, it will be passed unmodified to the linker.


Node:All-in-one Executables, Next:, Previous:The Application Builder, Up:The Application Builder

All-in-one Executables

It is possible to embed saved states into an executable. Together with static linking, this gives a all-in-one executbale, an executable that does not depend on external SICStus files.

The keys to this feature are:

Data resources are added by specifying their internal name and their location as part of the comma separated list of resources passed with the spld option --resources. Each data resource is specified as file=name where file is the name of the file containing the data (it must exist during the call to spld) and name is the name used to access the content of file during run-time. name should begin with a slash (/) and look like an ordinary lowercase file path made up of /-separated names consisting of a to z, underscore (_, period (.), and digits.

Typically, you would use spld --main=restore which will automatically restore the first .sav argument. To manually restore an embedded saved state you should use the syntax URL:x-sicstus-resource:name, e.g., SP_restore("URL:x-sicstus-resource:name").

An example will make this clearer. Suppose we create a run-time system that consists of a single file main.pl that looks like:

:- use_module(library(system)).
:- use_module(library(clpfd)).

% This will be called when the application starts:
runtime_entry(start) :-
   %% You may consider putting some other code here...
   write('hello world'),nl,
   write('Getting host name:'),nl,
   host_name(HostName),             % from system
   write(HostName),nl,
   ( all_different([3,9]) ->        % from clpfd
       write('3 != 9'),nl
   ; otherwise ->
       write('3 = 9!?'),nl
   ).

Then create the saved state main.sav which will contain the compiled code of main.pl as well as the Prolog code of library(system) and library(clpfd) and other Prolog libraries needed by library(clpfd).

sicstus -i -f

SICStus 3.9 ...
Licensed to SICS
| ?- compile(main).
% compiling .../main.pl...
% ... loading several library modules
| ?- save_program('main.sav').
% .../main.sav created in 201 msec
yes
| ?- halt.

Finally, tell spld to build an executable statically linked with the SICStus run-time and the foreign resources needed by library(system) and library(clpfd). Also, embed the Prolog run-time saved state and the application specific saved state just created.

(The example is using Cygwin bash (<http://www.cygwin.com>) on Windows but would look much the same on other platforms. The command should be given on a single line; it is broken up here for better layout.)

spld --static
  --main=restore
  --resources=main.sav=/mystuff/main.sav,clpfd,system
  --output=main.exe

The arguments are as follows:

--static
Link statically with the SICStus run-time and foreign resources (system and clpfd in this case). This option also adds --embed-rt-sav ensuring that the SICStus run-time .sav file is embedded.
--main=restore
Start the application by restoring the saved state and calling runtime_entry(start). This is not strictly needed in the above example since it is the default if any file with extension .sav or a data resource with a name with extension .sav is specified.
--resources=...
This is followed by three comma separated resource specifications:

main.sav=/mystuff/main.sav
This tells spld to make the content (at the time spld is invoked) of main.sav available at run-time in a data resource named /mystuff/main.sav. That is, the data resource name corresponding to "URL:x-sicstus-resource:/mystuff/main.sav".
clpfd
system
These tell spld to link with the foreign resources (that is, C-code) associated with library(system) and library(clpfd). Since --static was specified the static versions of these foreign resources will be used.

--output=main.exe
This tells spld where to put the resulting executable.

Finally, we may run this executable on any machine, even if SICStus is not installed:

bash-2.04$ ./main.exe
hello world
Getting host name:
EOWYN
3 != 9
bash-2.04$

Note that no pathnames passed to spld should contain spaces. On MS Windows, this can be avoided by using the short version of pathnames as necessary.


Node:spld examples, Previous:All-in-one Executables, Up:The Application Builder

Examples

  1. The character-based SICStus development system executable (sicstus) can be created using
    % spld --main=prolog -o sicstus
    

    This will create a development system which is dynamically linked and has no pre-linked foreign resources.

  2. % spld --static -D --resources=random -o main -ltk8.0 -ltcl8.0
    

    This will create a statically linked executable called main which has the resource random pre-linked (statically). The linker will receive -ltk8.0 -ltcl8.0 which will work under UNIX (if Tcl/Tk is installed correctly) but will probably fail under Windows.

  3. The following is a little more advanced example demonstrating two things. One is how to use the --userhook option to perform initializations in development systems before SP_initialize() is called. It also demonstrates how to use this mechanism to redefine the memory manager bottom layer.
    /* --------------------------------------------------------------
     * userhook.c - an example of how to use SU_initialize() to
     *              define your own memory manager bottom layer.
     *
     * The following commands create a sicstus-executable 'msicstus'
     * which uses malloc() as its own memory manager bottom layer.
     * This is more or less equivalent to specifying "-m" to the
     * regular 'sicstus' executable, except that these memory hooks
     * print out messages when they are called.
     * --------------------------------------------------------------
     */
    #include <stdio.h>
    #include <stdlib.h>
    #include <sicstus/sicstus.h>
    
    /* for mallopt() */
    #ifdef linux
    #include <malloc.h>
    #endif
    
    void *
    my_alloc_hook (unsigned int size,
                   unsigned int align,
                   unsigned int *actual_size)
    {
      void *mem;
    
      printf ("Inside my_alloc_hook(%d,%d,%p) -> ",
              size, align, actual_size);
    
      if (align > sizeof (double))
          size += align;
    
      mem = malloc (size);
      *actual_size = size;
      if (mem)
        printf ("%p\n", mem);
      else
        printf ("NULL (malloc failed to allocate memory)\n");
    
      return mem;
    }
    
    void *
    my_init_alloc_hook (unsigned int size,
                        unsigned int align,
                        unsigned int *actual_size)
    {
      printf ("Inside my_init_alloc_hook(%d,%d,%p)\n",
              size, align, actual_size);
    
      /* Do not use MMAP on Linux. */
    #ifdef linux
      mallopt (M_MMAP_MAX, 0);
    #endif
    
      return my_alloc_hook (size, align, actual_size);
    }
    
    void *
    my_realloc_hook (void *ptr,
                     unsigned int oldsize,
                     unsigned int newsize,
                     unsigned int align,
                     unsigned int *actual_size)
    {
      void *mem;
    
      printf ("Inside my_realloc_hook(%p,%d,%d,%d,%p) -> ",
              ptr, oldsize, newsize, align, actual_size);
    
      if (align > sizeof (double))
          newsize += align;
    
      mem = realloc (ptr, newsize);
      *actual_size = newsize;
      if (mem)
        printf ("%p\n", mem);
      else
        printf ("NULL (realloc() failed to re-allocate memory)\n");
    
      return mem;
    }
    
    int
    my_free_hook (void *ptr, unsigned int size)
    {
      printf ("Inside my_free_hook(%p,%d)\n", ptr, size);
    
      free (ptr);
      return 1;
    }
    
    /* Entry point for initializations to be done before SP_initialize() */
    int
    SU_initialize (int argc, char **argv)
    {
      SP_set_memalloc_hooks (MM_USE_OTHER,
                             my_init_alloc_hook,
                             my_alloc_hook,
                             my_realloc_hook,
                             my_free_hook);
      return 0;
    }
    

    Compile userhook.c like this:

    % spld -D --userhook userhook.c -o ./msicstus
    Created "./msicstus"
    % ./msicstus
    Inside my_init_alloc_hook(524304,8,0xbfffc318)
    Inside my_alloc_hook(524304,8,0xbfffc318) -> 0x804b920
    Inside my_alloc_hook(65536,8,0xbfff019c) -> 0x80cba38
    Inside my_alloc_hook(65536,8,0xbfff019c) -> 0x80dba40
    Inside my_alloc_hook(65536,8,0xbfff00d0) -> 0x80eba48
    Inside my_alloc_hook(65544,8,0xbfff0110) -> 0x80fba50
    Inside my_alloc_hook(65536,8,0xbfff019c) -> 0x810ba60
    Inside my_alloc_hook(65536,8,0xbfff00f4) -> 0x811ba68
    Inside my_alloc_hook(65536,8,0xbfff019c) -> 0x812ba70
    Inside my_alloc_hook(65536,8,0xbfff019c) -> 0x813ba78
    Inside my_alloc_hook(65536,8,0xbfff019c) -> 0x814ba80
    Inside my_alloc_hook(65536,8,0xbfff019c) -> 0x815ba88
    Inside my_alloc_hook(65536,8,0xbfff019c) -> 0x816ba90
    SICStus 3.8b1 (x86-linux-glibc2.1): Fri Oct 29 11:24:24 CEST 1999
    Licensed to SICS
    Inside my_free_hook(0x80fba50,65544)
    | ?-
    


Node:User-defined Main Programs, Previous:The Application Builder, Up:Stand-alone Executables

User-defined Main Programs

Runtime systems may or may not have an automatically generated main program. This is controlled by the --main option to spld. If --main=user is given, a function user_main() must be supplied:

int user_main(int argc, char *argv[])

user_main() is responsible for initializing the Prolog engine, loading code, and issuing any Prolog queries. And alternative is to use --main=none and write your own main() function.


Node:Initializing the Prolog Engine, Next:, Previous:User-defined Main Programs, Up:User-defined Main Programs

Initializing the Prolog Engine

The Prolog Engine is initialized by calling SP_initialize(). This must be done before any interface functions are called, except SP_force_interactive, SP_set_memalloc_hooks, SP_set_wcx_hooks, SP_set_user_stream_post_hook and SP_set_user_stream_hook. The function will allocate data areas used by Prolog, initialize command line arguments so that they can be accessed by the argv Prolog flag, and load the Runtime Library. It is called like this:

int SP_initialize(int argc, char **argv, char *boot_path)

boot_path should be the name of a directory, equivalent to $SP_PATH/bin. If boot_path is NULL, SP_initialize() will look up the value of the environment variable SP_PATH and look for the file $SP_PATH/bin/sprt.sav which contains the Runtime Library.

It returns SP_SUCCESS if initialization was successful, and SP_ERROR otherwise. If initialization was successful, further calls to SP_initialize() will be no-ops (and return SP_SUCCESS).

To unload the SICStus emulator, SP_deinitalize() can be called.

void SP_deinitialize(void)

SP_deinitialize() will make a best effort to restore the system to the state it was in at the time of calling SP_initialize(). This involves unloading foreign resources, shutting down the emulator by calling halt/0, and deallocate memory used by Prolog. SP_deinitialize() is idempotent as well, i.e. it is a no-op unless SICStus has actually been initialized.

You may also call SP_force_interactive() before calling SP_initialize(). This will force the I/O built-in predicates to treat the standard input stream as a terminal, even if it does not appear to be a terminal. Same as the -i option in development systems. (see Start).

void SP_force_interactive(void)

You may also call SP_set_memalloc_hooks() before calling SP_initialize(). This will define the bottom layer of Prolog's memory manager, in case your application has special requirements.

typedef void *(SP_AllocHook)(unsigned int size,
                             unsigned int align,
                             unsigned int *actual_sizep);
typedef void *(SP_ReAllocHook)(void *ptr,
                               unsigned int oldsize,
                               unsigned int newsize,
                               unsigned int align,
                               unsigned int *actual_sizep);
typedef int (SP_FreeHook)(void *ptr,
                          unsigned int size);

void SP_set_memalloc_hooks(int usage,
                           SP_AllocHook *init_alloc_hook,
                           SP_AllocHook *alloc_hook,
                           SP_ReAllocHook *realloc_hook,
                           SP_FreeHook *free_hook)

The effect of SP_set_memalloc_hooks is controlled by the value of usage, which should be one of:

MM_USE_MALLOC
The bottom layer will be based on malloc()/free(). The other arguments are ignored. Same as the -m option in development systems. (see Start).
MM_USE_SBRK
The bottom layer will be based on sbrk(). The default for UNIX development systems; not available for Windows. The other arguments are ignored.

This option seems to work well in practice but standard UNIX documents sbrk() as incompatible with malloc() etc and it is not safe to use if more than one thread allocates memory. These concerns are the reason this option is no longer the default for run-time systems.

MM_USE_SPARSE
The bottom layer will be based on VirtualAlloc()/VirtualFree(). The default for Windows; not available for UNIX. The other arguments are ignored.
MM_USE_DEFAULT
The bottom layer will use on some safe default. Currently MM_USE_MALLOC on UNIX and MM_USE_SPARSE on Windows. The default for run-time systems.
MM_USE_OTHER
The bottom layer will be based on the other arguments. Their meaning is explained below. See The Application Builder, for an example.

In the latter case, the other arguments should be functions as specified below. Pointer arguments and values should be aligned pointers.

alloc_hook
must allocate and return a pointer to a piece of memory that has at least size bytes aligned at align in it. align is guaranteed to be a power of 2. The actual size of the piece of memory should be returned in *actual_sizep. Should return NULL if it cannot allocate any more memory.
init_alloc_hook
is a special case of alloc_hook. It will be called initially whereas alloc_hook will be called subsequently. It can do whatever initialization that this layer of memory management wants to do.
realloc_hook
is called with a piece of memory to be resized and possibly moved. ptr is the pointer, oldsize its current size. The function must allocate and return a pointer to a piece of memory that has at least newsize bytes aligned at align in it, and that has the same contents as the old block up to the lesser of oldsize and newsize. align is guaranteed to be a power of 2. The actual size of the piece of memory should be returned in *actual_sizep. Should return NULL if it cannot allocate any more memory, or if it cannot reclaim the old block in a meaningful way. In that case, Prolog will use the other functions.
free_hook
is called with a pointer to the piece of memory to be freed and its size. Should return non-zero iff the function was able to free this piece of memory. Otherwise, Prolog will keep using the memory as if it were not freed.

The default bottom layers look at the environment variables PROLOGINITSIZE, PROLOGINCSIZE, PROLOGKEEPSIZE and PROLOGMAXSIZE. They are useful to customize the default memory manager. If users redefine the bottom layer, they can choose to ignore these environment variables. See Environment Variables.


Node:Loading Prolog Code, Previous:Initializing the Prolog Engine, Up:User-defined Main Programs

Loading Prolog Code

You can load your Prolog code with the call SP_load(). This is the C equivalent of the Prolog predicate load_files/1:

int SP_load(char *filename)

Alternatively, you can restore a saved state with the call SP_restore(), which is the C equivalent of the Prolog predicate restore/1:

int SP_restore(char *filename)

SP_load() and SP_restore() return SP_SUCCESS for success or SP_ERROR if an error condition occurred. The filename arguments in both functions are encoded strings.

Prolog error handling is mostly done by raising and catching exceptions. However, some faults are of a nature such that when they occur, the internal program state may be corrupted, and it is not safe to merely raise an exception. In runtime systems, the following C macro provides an environment for handling faults:

int SP_on_fault(Stmt, Message, Cleanup)

which should occur in the scope of a char *Message declaration. Stmt is run, and if a fault occurs, Stmt is aborted, Message gets assigned a value explaining the fault, all queries and SP_term_refs become invalid, SICStus Prolog is reinitialized, and Cleanup run. If Stmt terminates normally, Message is left unchanged. For example, a "fault-proof" runtime system could have the structure:

int main(int argc, char **argv)
{
  char *message;

  SP_initialize(argc, argv, "/usr/local/lib/sicstus3.9.0/bin");
loop:
  SP_on_fault(main_loop(), message,
              {printf("ERROR: %s\n",message); goto loop;});
  exit(0);
}

main_loop()
{...}

Faults that occur outside the scope of SP_on_fault() cause the runtime system to halt with an error message.

The following function can be used to raise a fault. For example, it can be used in a signal handler for SIGSEGV to prevent the program from dumping core in the event of a segmentation violation (runtime systems have no predefined signal handling):

void SP_raise_fault(char *message)

As for most SICStus API functions, calling SP_raise_fault from a thread other than the main thread will lead to unpredictable results. For this reason, it is probably not a good idea to use SP_raise_fault in a signal handler unless the process is single threaded. Also note that SP_signal is not suitable for installing signal handlers for synchronous signals like SIGSEGV.


Node:Mixing Examples, Previous:Stand-alone Executables, Up:Mixing C and Prolog

Examples


Node:Train, Next:, Previous:Mixing Examples, Up:Mixing Examples

Train Example (connections)

This is an example of how to create a runtime system. The Prolog program train.pl will display a route from one train station to another. The C program train.c calls the Prolog code and writes out all the routes found between two stations:

% train.pl

connected(From, From, [From], _):- !.
connected(From, To, [From| Way], Been):-
        (   no_stop(From, Through)
        ;
            no_stop(Through, From)
        ),
        not_been_before(Been, Through),
        connected(Through, To, Way, Been).

no_stop('Stockholm', 'Katrineholm').
no_stop('Stockholm', 'Vasteras').
no_stop('Katrineholm', 'Hallsberg').
no_stop('Katrineholm', 'Linkoping').
no_stop('Hallsberg', 'Kumla').
no_stop('Hallsberg', 'Goteborg').
no_stop('Orebro', 'Vasteras').
no_stop('Orebro', 'Kumla').

not_been_before(Way, _) :- var(Way),!.
not_been_before([Been| Way], Am) :-
        Been \== Am,
        not_been_before(Way, Am).
/* train.c */

#include <stdio.h>
#include <sicstus/sicstus.h>

void write_path(SP_term_ref path)
{
  char *text = NULL;
  SP_term_ref
    tail = SP_new_term_ref(),
    via = SP_new_term_ref();

  SP_put_term(tail,path);

  while (SP_get_list(tail,via,tail))
  {
    if (text)
      printf(" -> ");

    SP_get_string(via, &text);
    printf("%s",text);
  }
  printf("\n");
}

int user_main(int argc, char **argv)
{
  int rval;
  SP_pred_ref pred;
  SP_qid goal;
  SP_term_ref from, to, path;

  /* Initialize Prolog engine. This call looks up SP_PATH in order to
   * find the Runtime Library.  */
  if (SP_FAILURE == SP_initialize(argc, argv, NULL))
    {
      fprintf(stderr, "SP_initialize failed: %s\n", SP_error_message(SP_errno));
      exit(1);
    }

  rval = SP_restore("train.sav");

  if (rval == SP_ERROR || rval == SP_FAILURE)
    {
      fprintf(stderr, "Could not restore \"train.sav\".\n");
      exit(1);
    }

  /* Look up connected/4. */
  if (!(pred = SP_predicate("connected",4,"user")))
    {
      fprintf(stderr, "Could not find connected/4.\n");
      exit(1);
    }

  /* Create the three arguments to connected/4. */
  SP_put_string(from = SP_new_term_ref(), "Stockholm");
  SP_put_string(to = SP_new_term_ref(), "Orebro");
  SP_put_variable(path = SP_new_term_ref());

  /* Open the query. In a development system, the query would look like:
   *
   * | ?- connected('Stockholm','Orebro',X).
   */
  if (!(goal = SP_open_query(pred,from,to,path,path)))
    {
      fprintf(stderr, "Failed to open query.\n");
      exit(1);
    }

  /*
   * Loop through all the solutions.
   */
  while (SP_next_solution(goal)==SP_SUCCESS)
    {
      printf("Path: ");
      write_path(path);
    }

  SP_close_query(goal);

  exit(0);
}

Create the saved-state containing the Prolog code:

% sicstus
SICStus 3.9 (sparc-solaris-5.7): Thu Sep 30 15:20:42 MET DST 1999
Licensed to SICS
| ?- compile(train),save_program('train.sav').
% compiling [...]/train.pl...
% compiled [...]/train.pl in module user, 10 msec 2848 bytes
% [...]/train.sav created in 0 msec

yes
| ?- halt.

Create the executable using the application builder:

% spld --main=user train.c -o train.exe

And finally, run the executable:

% ./train
Path: Stockholm -> Katrineholm -> Hallsberg -> Kumla -> Orebro
Path: Stockholm -> Vasteras -> Orebro


Node:I/O on Lists of Character Codes, Next:, Previous:Train, Up:Mixing Examples

I/O on Lists of Character Codes

This example is taken from the SICStus Prolog library (simplified, but operational). A stream for writing is opened where the written characters are placed in a buffer. When the stream is closed a list of character codes is made from the contents of the buffer. The example illustrates the use of user definable streams.

The open_buf_stream() function opens a stream where the characters are put in a buffer. The stream is closed by stream_to_chars() which returns the list constructed on the heap.

The Prolog code (simplified):

foreign(open_buf_stream, '$open_buf_stream'(-address('SP_stream'))).
foreign(stream_to_chars, '$stream_to_chars'(+address('SP_stream'),
                                            -term)).

foreign_resource(example, [open_buf_stream,stream_to_chars]).

:- load_foreign_resource(example).

%% with_output_to_chars(+Goal, -Chars)
%% runs Goal with current_output set to a list of characters

with_output_to_chars(Goal, Chars) :-
        '$open_buf_stream'(StreamCode),
        stream_code(Stream, StreamCode),
        current_output(CurrOut),
        set_output(Stream),
        call_and_reset(Goal, Stream, CurrOut, StreamCode, Chars).

call_and_reset(Goal, Stream, CurrOut, StreamCode, Chars) :-
        call(Goal), !,
        put(0),
        '$stream_to_chars'(StreamCode, Chars),
        reset_stream(Stream, CurrOut).
call_and_reset(_, Stream, CurrOut, _, _) :-
        reset_stream(Stream, CurrOut).

reset_stream(Stream, CurrOut) :-
        set_output(CurrOut),
        close(Stream).

The C code:

#include <sicstus/sicstus.h>

struct open_chars {
  char *chars;       /* character buffer */
  int index;         /* current insertion point */
  int size;
};

#define INIT_BUFSIZE 512

static int lputc(c, buf)
     int c;
     struct open_chars *buf;
{
  if (buf->index == buf->size)  /* grow buffer if necessary */
    {
      buf->size *= 2;
      buf->chars = (char *)realloc(buf->chars, buf->size);
    }
  return (buf->chars[buf->index++] = c);
}

static int lwclose(buf)
     struct open_chars *buf;
{
  free(buf->chars);
  free(buf);
  return 0;
}

void open_buf_stream(streamp)
     SP_stream **streamp;
{
  struct open_chars *buf;

  /* Allocate buffer, create stream & return stream code */

  buf = (struct open_chars *)malloc(sizeof(struct open_chars));
  SP_make_stream(buf, NULL, lputc, NULL, NULL, NULL, lwclose,
                 streamp);

  buf->chars = (char *)malloc(INIT_BUFSIZE);
  buf->size = INIT_BUFSIZE;
  buf->index = 0;
}

void stream_to_chars(streamp, head)
     SP_stream *streamp;
     SP_term_ref head;
{
  SP_term_ref tail = SP_new_term_ref();
  struct open_chars *buf = (struct open_chars *)streamp->user_handle;

  /* Make a list of character codes out of the buffer */

  SP_put_string(tail, "[]");
  SP_put_list_chars(head, tail, buf->chars);
}


Node:Exceptions from C, Next:, Previous:I/O on Lists of Character Codes, Up:Mixing Examples

Exceptions from C

Consider, for example, a function which returns the square root of its argument after checking that the argument is valid. If the argument is invalid, the function should raise an exception instead.

/* math.c */

#include <math.h>
#include <stdio.h>
#include <sicstus/sicstus.h>

extern double sqrt_check(double d);
double sqrt_check(double d)
{
  if (d < 0.0)
    {    /* build a domain_error/4 exception term */
      SP_term_ref culprit=SP_new_term_ref();
      SP_term_ref argno=SP_new_term_ref();
      SP_term_ref expdomain=SP_new_term_ref();
      SP_term_ref t1=SP_new_term_ref();

      SP_put_float(culprit, d);
      SP_put_integer(argno, 1);
      SP_put_string(expdomain, ">=0.0");
      SP_cons_functor(t1, SP_atom_from_string("sqrt"), 1, culprit);
      SP_cons_functor(t1, SP_atom_from_string("domain_error"), 4,
                      t1, argno, expdomain, culprit);
      SP_raise_exception(t1);    /* raise the exception */
      return 0.0;
    }
  return sqrt(d);
}

The Prolog interface to this function is defined in a file math.pl. The function uses the sqrt() library function, and so the math library -lm has to be included:

/* math.pl */

foreign_resource(math, [sqrt_check]).

foreign(sqrt_check, c, sqrt(+float, [-float])).

:- load_foreign_resource(math).

A linked foreign resource is created:

% splfr math.pl math.c -lm

A simple session using this function could be:

% sicstus
SICStus 3.9 (sparc-solaris-5.7): Thu Aug 19 16:25:28 MET DST 1999
Licensed to SICS
| ?- [math].
% consulting /home/san/pl/math.pl...
% /home/san/pl/math.pl consulted, 10 msec 816 bytes

yes
| ?- sqrt(5.0,X).

X = 2.23606797749979 ?

yes
| ?- sqrt(a,X).
! Type error in argument 1 of user:sqrt/2
! number expected, but a found
! goal:  sqrt(a,_143)

| ?- sqrt(-5,X).
! Domain error in argument 1 of user:sqrt/1
! expected '>=0.0', found -5.0
! goal:  sqrt(-5.0)

The above example used the foreign language interface with dynamic linking. To statically link math.s.o with the Prolog emulator, the following steps would have been taken:

% splfr -S math.pl math.c -lm
SICStus 3.9 (sparc-solaris-5.7): Thu Aug 19 16:25:28 MET DST 1999
Licensed to SICS
% spXxQwsr.c generated, 0 msec

yes
% spld -D -o mathsp --resources=./math.s.o
SICStus 3.9 (sparc-solaris-5.7): Thu Aug 19 16:25:28 MET DST 1999
Licensed to SICS
% spYdLTgi1.c generated, 0 msec

yes
Created "mathsp"
% ./mathsp
SICStus 3.9 (sparc-solaris-5.7): Thu Aug 19 16:25:28 MET DST 1999
Licensed to SICS
| ?- [math].
% consulting /a/filur/export/labs/isl/sicstus/jojo/sicstus38p/math.pl...
% consulted /a/filur/export/labs/isl/sicstus/jojo/sicstus38p/math.pl in module user, 0 msec 960 bytes

yes
| ?- sqrt(5.0,X).

X = 2.23606797749979 ?

yes


Node:Stream Example, Previous:Exceptions from C, Up:Mixing Examples

Stream Example

This is a small example how to initialize a bidirectional socket stream (error handling omitted):

typedef struct {
  int fd;                       /* socket number */
  FILE *r_stream;               /* For reading */
  FILE *w_stream;               /* For writing */
} SocketData;

int socket_sgetc(SocketData *socket)
{
  return fgetc(socket->r_stream);
}

int socket_sputc(char c, SocketData *socket)
{
  return fputc(c, socket->w_stream);
}

int socket_sflush(SocketData *socket)
{
  return fflush(socket->w_stream);
}

int socket_seof(SocketData *socket)
{
  return feof(socket->r_stream);
}

void socket_sclrerr(SocketData *socket)
{
  clearerr(socket->r_stream);
  clearerr(socket->w_stream);
}

int socket_sclose(SocketData *socket)
{
  fclose(socket->r_stream);
  fclose(socket->w_stream);
  close(socket->fd);
  free(socket);
  return 0;
}

SP_stream *new_socket_stream(int fd)
{
  SP_stream *stream;
  SocketData *socket;

/* Allocate and initialize data local to socket */

  socket = (SocketData *)malloc(sizeof(SocketData));
  socket->fd = fd;
  socket->r_stream = fdopen(fd,"r");
  socket->w_stream = fdopen(fd,"w");

/* Allocate and initialize Prolog stream */

  SP_make_stream(
                 socket,
                 socket_sgetc,
                 socket_sputc,
                 socket_sflush,
                 socket_seof,
                 socket_sclrerr,
                 socket_sclose,
                 &stream);

/* Allocate and copy string */

  stream->filename = "socket";
  stream->fd = fd;

  return stream;
}


Node:Mixing Java and Prolog, Next:, Previous:Mixing C and Prolog, Up:Top

Mixing Java and Prolog

Jasper is a bi-directional interface between Java and SICStus. The Java-side of the interface consists of a Java package (se.sics.jasper) containing classes representing the SICStus run-time system (SICStus, SPTerm, etc). The Prolog part is designed as a library module (library(jasper)).

The library module library(jasper) (see Jasper) provides functionality for controlling the loading and unloading the JVM (Java Virtual Machine), method call functionality (jasper_call/4), and predicates for managing object references.

Jasper can be used in two modes, depending on which system acts as Parent Application. If Java is the parent application, the SICStus runtime kernel will be loaded into the JVM using the System.loadLibrary() method (this is done indirectly when instantiating a SICStus object). In this mode, SICStus is loaded as a runtime system (see Runtime Systems).

As of SICStus 3.9, it is possible to use Jasper in multi threaded mode. This means that several Java threads can call SICStus runtime via a server thread. The communication between the client threads and the server thread is hidden from the programmer, and the API is based on Java Interfaces which are implemented both by the multi thread capable classes and the pre-3.9 classes which are restricted to single threaded mode. The decision whether to run in single thread mode or in multi threaded mode can thus be left until runtime.

If SICStus is the parent application, Java will be loaded as a foreign resource using the query use_module(library(jasper)). The Java engine is initialized using jasper_initialize/[1-2].


Node:Getting Started, Next:, Up:Mixing Java and Prolog

Getting Started

See Getting Started, for a detailed description of how to get started using the interface. It addresses issues such as finding SICStus from within Java and vice versa, setting the classpath correctly, etc. If you have trouble in getting started with Jasper, read that chapter before contacting SICStus Support.


Node:Calling Prolog from Java, Next:, Previous:Getting Started, Up:Mixing Java and Prolog

Calling Prolog from Java

Calling Prolog from Java is done by using the Java package se.sics.jasper. This package contains a set of Java classes which can be used to create and manipulate terms, ask queries and request one or more solutions. The functionality provided by this set of classes is basically the same as the functionality provided by the C-Prolog interface (see Mixing C and Prolog).

The usage is easiest described by some examples.


Node:Single threaded example, Next:, Up:Calling Prolog from Java

Single threaded example

The following is a Java version of the train example. See Train, for information about how the train.sav file is created.

This code demonstrates the use of Jasper in single threaded mode. In this mode only one thread can access the SICStus runtime via a SICStus object.

import se.sics.jasper.SICStus;
import se.sics.jasper.Query;
import java.util.HashMap;

public class Simple
{
    public static void main(String argv[]) {

        SICStus sp;
        Query query;
        HashMap WayMap = new HashMap();

        try {
            sp = new SICStus(argv,null);

	    sp.restore("train.sav");

            query = sp.openPrologQuery("connected('Orebro', 'Stockholm', Way, Way).",
                                 WayMap);

            try {
                while (query.nextSolution()) {
                    System.out.println(WayMap);
                }
            } finally {
                query.close();
            }
        }
        catch ( Exception e ) {
            e.printStackTrace();
        }
    }
}

It is assumed that the reader has read the section on Getting Started, which describes how to get the basics up and running.

This is how the example works:

  1. Before any predicates can be called, the SICStus run-time system must be initialized. This is done by instantiating the SICStus class. Each SICStus object correspond to one independent copy of the SICStus run-time system (a rather heavy-weight entity).

    In this example, we have specified null as the second argument to SICStus. This instructs SICStus to search for sprt.sav using its own internal methods, or using a path specified by passing -Dsicstus.path=[...] to the JVM.

  2. Queries are made through method query. The arguments to this method are a string specifying a Prolog goal, and a Map which will contain a mapping of variable names to bindings. This method is for finding a single solution. Note that the string is read by the Prolog reader, so it must conform to the syntax rules for Prolog, including the terminating period. There are two more methods for making queries: queryCutFail, for side-effects only, and openQuery to produce several solutions through backtracking.
  3. The next step is to load the Prolog code. This is done by the method restore. Corresponds to SP_restore() in the C-interface. See Loading Prolog Code. Note that this method must be called before any other SICStus method is called. See the HTML Jasper documentation for details.
  4. The openQuery method returns a reference to a query, an object implementing the Query interface. To obtain solutions, the method nextSolution is called with no arguments. nextSolution returns true as long as there are more solutions, and the example above will print the value of the Map WayMap until there are no more solutions. Note that the query must be closed, even if nextSolution has indicated that there are no more solutions.


Node:Multi threaded example, Next:, Previous:Single threaded example, Up:Calling Prolog from Java

Multi threaded example

Following is a Java version of the train example. See Train, for information about how the train.sav file is created.

This is a multi threaded version of the train example. In this mode several threads can access the SICStus runtime via a Prolog interface. The static method Jasper.newProlog() returns an object which implements a Prolog interface. A thread can make queries by calling the query-methods of the Prolog object. The calls will be sent to a separate server thread which does the actual call to SICStus runtime.

import se.sics.jasper.Jasper;
import se.sics.jasper.Query;
import se.sics.jasper.Prolog;
import java.util.HashMap;

public class MultiSimple
{
    class Client extends Thread
    {
        Prolog jp;
        String qs;

        Client(Prolog p,String queryString)
        {
            jp = p;
            qs = queryString;
        }
        public void run()
        {
            HashMap WayMap = new HashMap();
            try {
                synchronized(jp) {
                    Query query = jp.openPrologQuery(qs, WayMap);
                    try {
                        while (query.nextSolution()) {
                            System.out.println(WayMap);
                        }
                    } finally {
                        query.close();
                    }
                }
            } catch ( Exception e ) {
                e.printStackTrace();
            }
        }
    }

    MultiSimple(String argv[])
    {
        try {
            Prolog jp = Jasper.newProlog(argv,null,"train.sav");

            Client c1 =
                new Client(jp,"connected('Orebro', 'Hallsberg', Way1, Way1).");
            c1.start();
            // The prolog variable names are different from above so we can tell
            // which query gives what solution.
            Client c2 =
                new Client(jp,"connected('Stockholm', 'Hallsberg', Way2, Way2).");
            c2.start();
        }
        catch ( Exception e ) {
            e.printStackTrace();
        }
    }

    public static void main(String argv[])
    {
        new MultiSimple(argv);
    }
}

  1. The Prolog object jp is the interface to SICStus. It implements the methods of interface Prolog, making it possible to write quite similar code for single threaded and multi threaded usage of Jasper. The static method Jasper.newProlog() returns such an object.
  2. In this example, the Prolog code is loaded by the server thread just after creating the SICStus object (which is invisible to the user). The third argument to the method Jasper.newProlog is the .sav file to restore. Two threads are then started, which will make different queries with the connected predicate.
  3. If you are using more than one Java thread that may call Prolog, you should enclose the call to openQuery and the closing of the query in a single synchronized block, synchronizing on the Prolog object.


Node:Another multi threaded example (Prolog top level), Previous:Multi threaded example, Up:Calling Prolog from Java

Another multi threaded example (Prolog top level)

This is another multi threaded version of the train example. See Train, for information about how the train.sav file is created.

In this example prolog is the toplevel and Java is invoked via library(jasper).

MultiSimple2.java:

import se.sics.jasper.Jasper;
import se.sics.jasper.Query;
import se.sics.jasper.Prolog;
import se.sics.jasper.SICStus;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.ListIterator;

public class MultiSimple2
{
    class Client extends Thread
    {
        Prolog jp;
        SICStus sp;
        String qs;

        Client(Prolog p, SICStus s, String queryString)
        {
            jp = p;
            sp = s;
            qs = queryString;
        }
        public void run()
        {
            HashMap WayMap = new HashMap();
            try {
                synchronized(jp) {
                    Query query = jp.openPrologQuery(qs, WayMap);
                    try {
                        while (query.nextSolution()) {
                            System.out.println(WayMap);
                        }
                    } finally {
                        query.close();
                    }
                }
            } catch ( Exception e ) {
                e.printStackTrace();
            }
        }
    }

    class Watcher extends Thread
    {
        SICStus mySp;
        ArrayList threadList = new ArrayList(2);

        public boolean add(Client cl)
        {
            return threadList.add((Object)cl);
        }
        boolean at_least_one_is_alive(ArrayList tl)
        {
            ListIterator li = tl.listIterator();
            boolean f = false;
            while (li.hasNext()) {
                boolean alive = ((Client)(li.next())).isAlive();
                f = f || alive;
            }
            return f;
        }
        public void run()
        {
            while (at_least_one_is_alive(threadList)) {
                try {
                    this.sleep(1000);
                } catch (InterruptedException ie) {
                    System.err.println("Watcher interrupted.");
                }
            }
            mySp.stopServer();
        }
        Watcher(SICStus sp)
        {
            mySp = sp;
        }
    }

    public void CallBack()
    {
        try {
            SICStus sp = SICStus.getCaller(); // get the SICStus object
            sp.load("train.ql");
            Prolog jp = sp.newProlog(); // Create a new Prolog Interface
            Client c1 =
                new Client(jp, sp,
                           "connected('Orebro', 'Hallsberg', Way1, Way1).");
            c1.start();
            // The prolog variable names in the Map are different from above so
            // we can tell which query gives what solution.
            Client c2 =
                new Client(jp, sp,
                           "connected('Stockholm', 'Hallsberg', Way2, Way2).");
            c2.start();
            Watcher w = new Watcher(sp);
            w.add(c1);
            w.add(c2);
            w.start();
            sp.startServer();   // And finally start the server. This
                                //  method call does not return until
                                //  some other thread calls sp.stopServer().
        }
        catch ( Exception e ) {
            e.printStackTrace();
        }
    }

}

multisimple2.pl:

:- use_module(library(jasper)).

main:-
        jasper_initialize(JVM),
        jasper_new_object(JVM,
                          'MultiSimple2',
                          init,
                          init,
                          Obj),
        jasper_call(JVM,
                    method('', 'CallBack', [instance]),
                    'CallBack'(+object('')),
                    'CallBack'(Obj)).

  1. This example is similar to the previous multi threaded example See Multi threaded example, but in this case Prolog is the top level.
  2. Since a SICStus object already exists when the java method CallBack is called, we cannot use Jasper.newProlog to obtain a Prolog interface. Instead we can use the SICStus method getCaller to get a handle on the SICStus object.
  3. In this example we cannot use the restore method to load the prolog saved state, since it unloads all foreign resources. This includes library(jasper) from which the call to Java was made. Instead the method SICStus.load can be used to load a compiled prolog file. See the HTML Jasper documentation for details on this method.
  4. The rest of the example is similar to the previous multi threaded example with the addition of a watcher class, which is used to monitor the client threads. This is necessary if the method startServer is to return. See the HTML Jasper documentation on the methods SICStus.startServer and SICStus.stopServer.


Node:Jasper Package Class Reference, Next:, Previous:Calling Prolog from Java, Up:Mixing Java and Prolog

Jasper Package Class Reference

Detailed documentation of the classes in the jasper package can be found in the HTML documentation installed with SICStus and also at the SICStus documentation page (http://www.sics.se/sicstus/docs/).

Please note: None of the se.sics.jasper methods are thread safe, unless explicitly mentioned, they can only be called from the thread that created the SICStus object. (This is different from how se.sics.jasper worked in SICStus 3.8)

However, Jasper in SICStus 3.9 supports multi threaded mode. Several Java threads can access SICStus runtime through a server thread which does the actual calls.

The API is defined by three interfaces: Prolog, Query and Term. The methods of these interfaces are implemented by inner classes of the Jasper server. Instances of these inner classes are returned by methods of the class Jasper and can then be used from multiple threads by the Java programmer.

In multi threaded mode the Java programmer obtains an object implementing the interface Prolog. That interface has methods similar to the methods of the SICStus class described below. Interface Query and interface Term have the same relations to class SPQuery and class SPTerm, respectively. In addition the SICStus class, the SPQuery class and the SPTerm class all implement the above interfaces. The methods of the interfaces are preferred over the old methods.

See the HTML documentation for details on the methods of the interfaces.

See Jasper Notes, for limitations in multi threaded Jasper.

boolean query (String module, String name, SPTerm args[]) Method on SICStus
Call name with args (a vector of SPTerm objects). Like once(Module:Name(Args...)).

Returns true if the call succeeded, false if the call failed, i.e. there were no solutions.

Introduced in SICStus 3.8.5.

boolean query (String goal, Map varMap) Method on SICStus
Call a goal specified as a string.

goal
The textual representation of the goal to execute, with terminating period.
varMap
A map from variable names to SPTerm objects. Used both for passing variable bindings into the goal and to obtain the bindings produced by the goal. May be null.

On success, the values of variables with names that do not start with underscore (_) will be added to the map.

Returns true if the call succeeded, false if the call failed, i.e. there were no solutions.

HashMap varMap = new HashMap();

varMap.put("File", new SPTerm(sp, "datafile.txt"));

if (sp.query("see(File),do_something(Result),seen.", varMap)) {
   System.out.println("Result==" + ((SPTerm)varMap.get("Result")).toString());
} else {
   System.out.println("Failed);
}

Introduced in SICStus 3.8.5.

boolean query (SPPredicate pred, SPTerm args[]) Method on SICStus
Obsolescent version of SICStus::query() above.

boolean queryCutFail (String module, String name, SPTerm args[]) Method on SICStus
Call name with args for side effect only.

As SICStus.query() it only finds the first solution, and then it cuts away all other solutions and fails.

It corresponds roughly to the following Prolog code:

   ( \+ call(Module:Name(Args...)) -> fail; true )
Introduced in SICStus 3.8.5.

boolean queryCutFail (String goal, Map varMap) Method on SICStus
Call a goal specified as a string, for side effect only. The map is only used for passing variable bindings into the goal. See query for details

Introduced in SICStus 3.8.5.

boolean queryCutFail (SPPredicate pred, SPTerm args[]) Method on SICStus
Obsolescent version of queryCutFail above.

SPQuery openQuery (String module, String name, SPTerm args[]) Method on SICStus
Sets up a query (an object of class SPQuery) which can later be asked to produce solutions. You must close an opened query when no more solutions are required; see below.

It corresponds roughly to the following Prolog code:

   ( true     % just calling openQuery does not call the predicate

   ; % failing (nextSolution) will backtrack for more solutions
     call(Module:Name(Args...))
   )

Introduced in SICStus 3.8.5.

boolean openQuery (String goal, Map varMap) Method on SICStus
Sets up a query specified as a string. See openQuery and query for details.

Introduced in SICStus 3.8.5.

SPQuery openQuery (SPPredicate pred, SPTerm args[]) Method on SICStus
Obsolescent version of openQuery above.

The following methods are used to obtain solutions from an opened query and to tell the SICStus run-time system that no more answers are required.

boolean nextSolution () Method on SPQuery
Obtain the next solution. Returns true on success and false if there were no more solutions. When you are no longer interested in any more solutions, you should call SPQuery.close or SPQuery.cut to close the query.

Returns true if a new solution was produced, false if there were no more solutions. This corresponds roughly to fail/0. See SPTerm and Memory, for additional details.

close () Method on SPQuery
Cut and fail away any previous solution to the query. After closing a query object, you should not use it anymore. This corresponds roughly to !, fail. See SPTerm and Memory, for additional details.

cut () Method on SPQuery
Cut, but do not fail away, any previous solution. After closing a query object with cut, you should not use it anymore. This corresponds roughly to !. See SPTerm and Memory, for additional details.


Node:Java Exception Handling, Next:, Previous:Jasper Package Class Reference, Up:Mixing Java and Prolog

Java Exception Handling

Exceptions are handled seamlessly between Java and Prolog. This means that exceptions can be thrown in Prolog and caught in Java and the other way around. For example, if a predicate called from Java throws an exception with throw/1 and the predicate itself does not catch the exception, the Java-method which performed the query, queryCutFail() for example, will throw an exception (of class SPException) containing the exception term. Symmetrically, a Java-exception thrown (and not caught) in a method called from Prolog will cause the corresponding predicate (simple/2 in the example above) to throw an exception consisting of the exception object (in the internal Prolog representation of a Java object). See Handling Java Exceptions, for examples of catching Java exceptions in Prolog.


Node:SPTerm and Memory, Next:, Previous:Java Exception Handling, Up:Mixing Java and Prolog

SPTerm and Memory

Java and Prolog have quite different memory management policies. In Java, memory is reclaimed when the garbage collector can determine that no code will ever use the object occupying the memory. In Prolog, the garbage collector additionally reclaims memory upon failure (such as the failure implied in the use of SPQuery.close() and SPQuery::nextSolution()). This mismatch in the notion of memory lifetime can occasionally cause problems.


Node:Lifetime of SPTerms and Prolog Memory, Next:, Up:SPTerm and Memory

Lifetime of SPTerms and Prolog Memory

There are three separate memory areas involved when manipulating Prolog terms from Java using SPTerm objects. These areas have largely independent life times.

  1. The SPTerm object itself.
  2. Creating SPTerm object also tells Prolog to allocate an SP_term_ref. SP_term_refs have a life-time that is independent of the lifetime of the corresponding SPTerm object.
  3. Any Prolog terms allocated on the Prolog heap. An SPTerm refer to a Prolog term indirectly via a SP_term_ref.

A SP_term_ref ref (created as a side-effect of creating a SPTerm object) will be reclaimed if either:

An SPTerm object will be invalidated (and eventually reclaimed by the garbage collector) if the corresponding SP_term_ref is reclaimed as above. If passed an invalidated SP_term_ref, most methods will throw an IllegalTermException exception.

A Prolog term (allocated on the Prolog heap) will be deallocated when:

Plase note: it is possible to get a SPTerm object and its SP_term_ref to refer to deallocated Prolog terms, in effect creating "dangling" pointers in cases where the SPTerm would ordinarily still be valid. This will be detected and invalidate the SPTerm

{
  SPTerm old = new SPTerm(sp);
  SPQuery q;

  q = sp.openQuery(....);
  ...
  old.consFunctor(...);  // allocate a Prolog term newer than q
  ...
  q.nextSolution(); // or q.close()
  // error:
  // The SP_term_ref in q refers to an invalid part of the Prolog heap
  // the SPTerm old will be invalidated by q.nextSolution()
}


Node:Preventing SPTerm Memory Leaks, Previous:Lifetime of SPTerms and Prolog Memory, Up:SPTerm and Memory

Preventing SPTerm Memory Leaks

Some uses of SPTerm will leak memory on the Prolog side. This happens if a new SPTerm object is allocate, but Java neither returns to Prolog nor backtracks (using the method close, cut or nextSolution) into a query opened before the allocation of the SPTerm object.

As of SICStus 3.8.5, it is possible to explicitly delete a SPTerm object using the SPTerm.delete() method. The delete() method invalidates the SPTerm object and makes the associated SP_term_ref available for re-use.

Another way to ensure that all SP_term_refs are deallocated is to open a dummy query only for this purpose. The following code demonstrates this:

// Always synchronize over creation and closing of SPQuery objects
synchronized (sp) {
    // Create a dummy query that invokes true/0
    SPQuery context = sp.openQuery("user","true",new SPTerm[]{});
    // All SP_term_refs created after this point will be reclaimed by
    // Prolog when doing context.close() (or context.cut())

    try {           // ensure context is always closed
        SPTerm tmp = new SPTerm(sp); // created after context
        int i = 0;

        while (i++ < 5) {
            // re-used instead of doing tmp = new SPTerm(sp,"...");
            tmp.putString("Iteration #" + i + "\n");
            // e.g. user:write('Iteration #1\n')
            sp.queryCutFail("user", "write", new SPTerm[]{tmp});
        }
    }
    finally {
        // This will invalidate tmp and make Prolog
        // reclaim the corresponding SP_term_ref
        context.close(); // or context.cut() to retain variable bindings.
    }
}


Node:Java Threads, Previous:SPTerm and Memory, Up:Mixing Java and Prolog

Java Threads

None of the pre-3.9 methods in se.sics.jasper are thread safe. They can only be called from the thread that created the SICStus object. (This is different from how se.sics.jasper used to work in SICStus 3.8).

In 3.9 there are two ways to set up for calls to SICStus from multiple threads.

One way is to use the static method newProlog in the class Jasper:

Prolog newProlog (String argv[], String bootPath) Method on Jasper
Creates a Prolog interface object. Starts a server thread which will serve that Prolog. The server thread takes care of all interaction with the Prolog runtime, making sure that all calls to the Prolog runtime will be done from one and the same thread.

See the HTML documentation on the interface Prolog for details on what methods are available for a client thread.

Another way is to create a SICStus object and use the following methods:

Prolog newProlog () Method on SICStus
Returns the Prolog interface for this SICStus object. Creates a server and a client (Prolog) interface for this SICStus object. The server may be started by calling startServer()

startServer () Method on SICStus
Start serving requests from a Prolog client. This method does not return until another thread calls stopServer(). Before calling this method you should call newProlog() and hand the result over to another Thread.

stopServer () Method on SICStus
Stops the server. Calling this method causes the Thread running in the startServer() method to return.

As with the first method, the interface Prolog defines the methods available for the client threads.


Node:Multiple SICStus Run-Times, Next:, Previous:Mixing Java and Prolog, Up:Top

Multiple SICStus Run-Times in a Process

It is possible to have more than one SICStus run-time in a single process. These are completely independent (except that they dynamically load the same foreign resources; see Foreign Resources and Multiple SICStus Run-Times).

Even though the SICStus run-time can only be run in a single thread, it is now possible to start several SICStus run-times, optionally each in its own thread.

SICStus run-times are rather heavy weight and you should not expect to be able to run more than a handful.


Node:Memory Considerations, Next:, Previous:Multiple SICStus Run-Times, Up:Multiple SICStus Run-Times

Memory Considerations

The most pressing restriction when using more than one SICStus run-time in a process is that (on 32bit machines) all these run-times must compete for the lower 256MB of memory. This is worsened by the fact that each SICStus run-time will attempt to grow its memory area as needed, leading to fragmentation. A fix that removes the restriction on useable memory is planned for a later release.

One way to avoid the fragmentation issue to some extent is to make each SICStus run-time preallocate a large enough memory area so it will not have to grow during run-time. This can be effected by setting the environment variables GLOBALSTKSIZE and PROLOGINITSIZE.

bash> GLOBALSTKSIZE=10MB; export GLOBALSTKSIZE;
bash> PROLOGINITSIZE=20MB; export PROLOGINITSIZE;

You can use statistics/2 to try to determine suitable values for thes, but it is bound to be a trial-and-error process.


Node:Multiple SICStus Run-Times in Java, Next:, Previous:Memory Considerations, Up:Multiple SICStus Run-Times

Multiple SICStus Run-Times in Java

In Java, you can now create more than one se.sics.jasper.SICStus object. Each will correspond to a completely independent copy of the SICStus run-time. Note that a SICStus run-time is not deallocated when the corresponding SICStus object is no longer used. Thus, the best way to use multiple SICStus objects is to create them early and then re-use them as needed.

It is probably useful to create each in its own separate thread. One reason would be to gain speed on a multi-processor machine.


Node:Multiple SICStus Run-Times in C, Next:, Previous:Multiple SICStus Run-Times in Java, Up:Multiple SICStus Run-Times

Multiple SICStus Run-Times in C

Unless otherwise noted, this section documents the behavior when using dynamic linking to access a SICStus run-time.

The key implementation feature that makes it possible to use multiple run-times is that all calls from C to the SICStus API (SP_query, etc.) go through a dispatch vector. Two run-times can be loaded at the same time since their APIs are accessed through different dispatch vectors.

By default, there will be a single dispatch vector, referenced from a global variable (sp_GlobalSICStus). A SICStus API functions, such as SP_query, is then defined as a macro that expands to something similar to sp_GlobalSICStus->SP_query_pointer. The name of the global dispatch vector is subject to change without notice; it should not be referenced directly. If you need to access the dispatch vector, use the C macro SICStusDISPATCHVAR instead, see below.

Using a Single SICStus Run-Time

When building an application with spld, by default only one SICStus run-time can be loaded in the process. This is similar to the case in SICStus versions prior to 3.9. For most applications built with spld, the changes necessary to support multiple SICStus run-times should be invisible, and old code should only need to be rebuilt with spld.

In order to maintain backward compatibility, the global dispatch vector is automatically set up by SP_initialize. Other SICStus API functions will not set up the dispatch vector, and will therefore lead to memory access errors if called before SP_initialize. Currently, hook functions such as SP_set_memalloc_hooks also set up the dispatch vector to allow them to be called before SP_initialize. However, only SP_initialize is guaranteed to set up the dispatch vector. The hook installation functions may change to use a different mechanism in the future. The SICStus API functions that perform automatic setup of the dispatch vector are marked with SPEXPFLAG_PREINIT in sicstus.h.

Using More than One SICStus Run-Time

Using more than one SICStus run-time in a process is only supported when the dynamic library version of the sicstus run-time is used (e.g, sprt39.dll, libsprt39.so).

An application that wants to use more than one SICStus run-time needs to be built using the --multi-sp-aware argument to spld. C-code compiled by spld --multi-sp-aware will have the C preprocessor macro MULTI_SP_AWARE defined and non-zero.

Unlike the single run-time case described above, an application built with --multi-sp-aware will not have a global variable that holds the dispatch vector. Instead, your code will have to take steps to ensure that the appropriate dispatch vector is used when switching between SICStus run-times.

There are several steps needed to access a SICStus run-time from an application built with --multi-sp-aware.

  1. You must obtain the dispatch vector of the initial SICStus run-time using SP_get_dispatch(). Note that this function is special in that it is not accessed through the dispatch vector; instead, it is exported in the ordinary manner from the SICStus run-time dynamic library (sprt39.dll on Windows and, typically, libsprt39.so on UNIX).
  2. You must ensure that SICStusDISPATCHVAR expands to something that references the dispatch vector obtained in step 1.

    The C pre-processor macro SICStusDISPATCHVAR should expand to a SICSTUS_API_STRUCT_TYPE *, that is, a pointer to the dispatch vector that should be used. When --multi-sp-aware is not used SICStusDISPATCHVAR expands to sp_GlobalSICStus as described above. When using --multi-sp-aware it is probably best to let SICStusDISPATCHVAR expand to a local variable.

  3. Once you have access to the SICStus API of the initial SICStus run-time you can call the SICStus API function SP_load_sicstus_run_time to load additional run-times.
SICSTUS_API_STRUCT_TYPE *SP_get_dispatch(void *reserved);

SP_get_dispatch returns the dispatch vector of the SICStus run-time. The argument reserved should be NULL. This function can be called from any thread.

typedef SICSTUS_API_STRUCT_TYPE *SP_get_dispatch_type(void *);

int SP_load_sicstus_run_time(SP_get_dispatch_type **ppfunc, void **phandle);

SP_load_sicstus_run_time loads a new SICStus run-time. SP_load_sicstus_run_time returns zero if a new run-time could not be loaded. If a new run-time could be loaded a non-zero value is returned and the address of the SP_get_dispatch function of the newly loaded SICStus run-time is stored at the address ppfunc. The second argument, phandle, is reserved and should be NULL.

As a special case, if SP_load_sicstus_run_time is called from a SICStus run-time that has not been initialized (with SP_initialize) and that has not previously been loaded as the result of calling SP_load_sicstus_run_time, then no new run-time is loaded. Instead, the SP_get_dispatch of the run-time itself is returned. In particular, the first time SP_load_sicstus_run_time is called on the initial SICStus run-time, and if this happens before the initial SICStus run-time is initialized, then no new run-time is loaded.

Calling SP_load_sicstus_run_time from a particular run-time can be done from any thread.

An application that links statically with the SICStus run-time should not call SP_load_sicstus_run_time.

You should not use pre-linked foreign resources when using multiple SICStus run-times in the same process.

For an example of loading and using multiple SICStus run-times, see library/jasper/spnative.c that implements this functionality for the Java interface Jasper.


Node:Foreign Resources and Multiple SICStus Run-Times, Next:, Previous:Multiple SICStus Run-Times in C, Up:Multiple SICStus Run-Times

Foreign Resources and Multiple SICStus Run-Times

Foreign resources access the SICStus C API in the same way as an embedding application, that is, through a dispatch vector. As for applications, the default and backward compatible mode is to only support a single SICStus run-time. An alternative mode makes it possible for a foreign resource to be shared between several SICStus run-times in the same process.

Unless otherwise noted, this section documents the behavior when using dynamically linked foreign resources. That is, shared objects (.so-files) on UNIX, dynamic libraries (DLLs) on Windows.

Foreign Resources Supporting Only One SICStus Run-Time

A process will only contain one instance of the code and data of a (dynamic) foreign resource even if the foreign resource is loaded and used from more than one SICStus run-time.

This presents a problem in the likely event that the foreign resource maintains some state, e.g. global variables, between invocations of functions in the foreign resource. The global state will probably need to be separate between SICStus run-times. Requiring a foreign resource to maintain its global state on a per SICStus run-time basis would be an incompatible change. Instead, by default, only the first SICStus run-time that loads a foreign resource will be allowed to use it. If a subsequent SICStus run-time (in the same process) tries to load the foreign resource then an error will be reported to the second SICStus run-time.

When splfr builds a foreign resource, it will also generate glue code. When the foreign resource is loaded, the glue code will set up a global variable pointing to the dispatch vector used in the foreign resource to access the SICStus API. This is similar to how an embedding application accesses the SICStus API.

The glue code will also detect if a subsequent SICStus run-time in the same process tries to initialize the foreign resource. In this case, an error will be reported.

This means that pre 3.9 foreign code should only need to be rebuilt with splfr to work with the latest version of SICStus. However, a recommended change is that all C files of a foreign resource include the header file generated by splfr. Inclusion of this generated header file may become mandatory in a future release. See The Foreign Resource Linker.

Foreign Resources Supporting Multiple SICStus run-times

A foreign resource that wants to be shared between several SICStus run-times must somehow know which SICStus run-time is calling it so that it can make callbacks using the SICStus API into the right SICStus run-time. In addition, the foreign resource may have global variables that should have different values depending on which SICStus run-time is calling the foreign resource.

A header file is generated by splfr when it builds a foreign resource (before any C code is compiled). This header file provides prototypes for any foreign-declared function, but it also provides other things needed for multiple SICStus run-time support. This header file must be included by any C file that contains code that either calls any SICStus API function or that contains any of the functions called by SICStus. See The Foreign Resource Linker.

Simplified Support for Multiple SICStus Run-Times

To make it simpler to convert old foreign resources, there is an intermediate level of support for multiple SICStus run-times. This level of support makes it possible for several SICStus run-times to call the foreign resource, but a mutual exclusion lock ensures that only one SICStus run-time at a time can execute code in the foreign resource. That is, the mutex is locked upon entry to any function in the foreign resource and unlocked when the function returns. This makes it possible to use a global variable to hold the SICStus dispatch vector, in much the same way as is done when only a single SICStus run-time is supported. In addition, a special hook function in the foreign resource will be called every time the foreign resource is entered. This hook function can then make arrangements to ensure that any global variables are set up as appropriate.

To build a foreign resource in this way, use splfr --exclusive-access. In addition to including the generated header file, your code needs to define the context switch function. If the resource is named resname then the context switch hook should look like:

void sp_context_switch_hook_resname(int entering)

The context switch hook will be called with the SICStus API dispatch vector already set up, so calling any SICStus API function from the context switch hook will work as expected. The argument entering will be non-zero when a SICStus run-time is about to call a function in the foreign resource. The hook will be called with entering zero when the foreign function is about to return to SICStus.

It is possible to specify a name for the context switch hook with the splfr option --context-hook=name. If you do not require a context switch hook you can specify the splfr option --no-context-hook.

Due to the use of mutual exclusion lock to protect the foreign resource, there is a remote possibility of dead-lock. This would happen if the foreign resource calls back to SICStus and then passes control to a different SICStus run-time in the same thread which then calls the foreign resource. For this reason it is best to avoid --exclusive-access for foreign resources that makes call-backs into Prolog.

The new SICStus API function SP_foreign_stash() provides access to a location where the foreign resource can store anything that is specific to the calling SICStus run-time. The location is specific to each foreign resource and each SICStus run-time. See Miscellaneous C API Functions.

C code compiled by splfr --exclusive-access will have the C pre-processor macro SP_SINGLE_THREADED defined to a non-zero value.

Some of the foreign resources in the SICStus library use this technique; see for instance library(system).

Full Support for Multiple SICStus Run-Times

To fully support multiple SICStus run-times, a foreign resource should be built with splfr --multi-sp-aware.

C code compiled by splfr --multi-sp-aware will have the C pre-processor macro MULTI_SP_AWARE defined to a non-zero value.

Full support for multiple SICStus run-times means that more than one SICStus run-time can execute code in the foreign resource at the same time. This rules out the option to use any global variables for information that should be specific to each SICStus run-time. In particular, the SICStus dispatch vector cannot be stored in a global variable. Instead, the SICStus dispatch vector is passed as an extra first argument to each foreign function.

To ensure some degree of link time type checking, the name of each foreign function will be changed (using #define in the generated header file).

The extra argument is used in the same way as when using multiple SICStus run-times from an embedding application. It must be passed on to any function that needs access to the SICStus API.

To simplify the handling of this extra argument, several macros are defined so that the same foreign resource code can be compiled both with and without support for multiple SICStus run-times.

SPAPI_ARG0
SPAPI_ARG
SPAPI_ARG_PROTO_DECL0
SPAPI_ARG_PROTO_DECL

Their use is easiest to explain with an example. Suppose the original foreign code looked like:

static int f1(void)
{
        some SICStus API calls
}

static int f2(SP_term_ref t, int x)
{
        some SICStus API calls
}

/* :- foreign(foreign_fun, c, foreign_pred(+integer)). */
void foreign_fun(long x)
{
  ... some SICStus API calls ...
  f1();
  ...
  f2(SP_new_term_ref(), 42);
  ...
}

Assuming no global variables are used, the following change will ensure that the SICStus API dispatch vector is passed around to all functions:

static int f1(SPAPI_ARG_PROTO_DECL0) // _DECL<ZERO> for no-arg functions
{
        some SICStus API calls
}

static int f2(SPAPI_ARG_PROTO_DECL SP_term_ref t, int x) // Note: no comma
{
        some SICStus API calls
}

/* :- foreign(foreign_fun, c, foreign_pred([-integer])). */
void foreign_fun(SPAPI_ARG_PROTO_DECL long x) // Note: no comma
{
  ... some SICStus API calls ...
  f1(SPAPI_ARG0);               // ARG<ZERO> for no-arg functions
  ...
  f2(SPAPI_ARG SP_new_term_ref(), 42);       // Note: no comma
  ...
}

If MULTI_SP_AWARE is not defined, i.e. --multi-sp-aware is not specified to splfr, then all these macros expand to nothing, except SPAPI_ARG_PROTO_DECL0 which will expand to void.

You can use SP_foreign_stash() to get access to a location, initially set to NULL, where the foreign resource can store a void*. Typically this would be a pointer to a C struct that holds all information that need to be stored in global variables. This struct can be allocated and initialized by the foreign resource initialization function. It should be deallocated by the foreign resource deinit function. See Miscellaneous C API Functions, for details.

Simple stand-alone examples will be provided in the final version of 3.9. Until then, for an example of code that fully supports multiple SICStus run-times. see library/jasper/jasper.c. For an example which hides the passing of the extra argument by using the C pre-processor, see the files in library/clpfd/.


Node:Threads, Previous:Foreign Resources and Multiple SICStus Run-Times, Up:Multiple SICStus Run-Times

Multiple Run-Times and Threads

Perhaps the primary reason to use more than one SICStus run-time in a process is to have each run-time running in a separate thread. To this end, a few mutual exclusion primitives are available. See Operating System Services, for details on mutual exclusion locks.

Note that the SICStus run-time is not thread safe in general. See Calling Prolog Asynchronously, for ways to safely interact with a running SICStus from arbitrary threads.


Node:Handling Wide Characters, Next:, Previous:Multiple SICStus Run-Times, Up:Top

Handling Wide Characters

The chapter describes the SICStus Prolog features for handling wide characters. We will refer to these capabilities as Wide Character eXtensions, and will use the abbreviation WCX.


Node:WCX Introduction, Next:, Previous:Handling Wide Characters, Up:Handling Wide Characters

Introduction

SICStus Prolog supports character codes up to 31 bits wide. It has a set of hooks for specifying how the character codes should be read in and written out to streams, how they should be classified (as letters, symbol-chars, etc.), and how strings of wide characters should be exchanged with the operating system. There are three sets of predefined hook functions supporting ISO 8859/1, UNICODE/UTF-8 and EUC external encodings, selectable using an environment variable. Alternatively, users may plug in their own definition of hook functions and implement arbitrary encodings. WCX Concepts, introduces the basic WCX concepts and presents their implementation in SICStus Prolog. Prolog Level WCX Features, gives an overview of those Prolog language features which are affected by wide character handling. WCX Environment Variables, and WCX Hooks, describe the options for customization of SICStus Prolog WCX through environment variables and through the hook functions, respectively. WCX Foreign Interface, and WCX Features in Libraries, summarize the WCX extensions in the foreign language interface and in the libraries. WCX Utility Functions, describes the utility functions provided by SICStus Prolog to help in writing the WCX hook functions, while Representation of EUC Wide Characters, presents the custom-made internal code-set for the EUC encoding. Finally A Sample WCX Box, describes an example implementation of the WCX hook functions, which supports a composite character code set and four external encodings. The code for this example is included in the distribution as library(wcx_example).


Node:WCX Concepts, Next:, Previous:WCX Introduction, Up:Handling Wide Characters

Concepts

First let us introduce some notions concerning wide characters.

(Wide) character code
an integer, possibly outside the 0..255 range.

SICStus Prolog allows character codes in the range 0..2147483647 (= 2^31-1). Consequently, the built-in predicates for building and decomposing atoms from/into character codes (e.g. atom_codes/2, name/2, etc.) accept and produce lists of integers in the above range (excluding the 0 code).

Wide characters can be used in all contexts: in atoms (single quoted, or unquoted, depending on the character-type mapping), strings, character code notation (0'char), etc.

External (stream) encoding
a way of encoding sequences of wide characters as sequences of (8-bit) bytes, used in stream input and output.

SICStus Prolog has three different external stream encoding schemes built-in, selectable through an environment variable. Furthermore it provides hooks for users to plug in their own external stream encoding functions. The built-in predicates put_code/1, get_code/1, etc., accept and return wide character codes, converting the bytes written or read using the external encoding in force.

Note that an encoding need not be able to handle the whole range of character codes allowed by SICStus Prolog.

Character code set
a subset of the set {0, ..., 2^31-1} that can be handled by an external encoding. SICStus Prolog assumes that the character code set is an extension of the ASCII code set, i.e. it includes codes 0..127, and these codes are interpreted as ASCII characters. Note that ASCII characters can still have an arbitrary external encoding, cf. the usage flag WCX_CHANGES_ASCII; see WCX Hooks.
Character type mapping
a function mapping each element of the character code set to one of the character categories (layout, small-letter, symbol-char, etc.; see Token String). This is required for parsing tokens. The character-type mapping for non-ASCII characters is hookable in SICStus Prolog and has three built-in defaults, depending on the external encoding selected.
System encoding
a way of encoding wide character strings, used or required by the operating system environment in various contexts (e.g. file names in open/3, command line options, as returned by prolog_flag(argv, Flags), etc.). The system encoding is hookable in SICStus Prolog and has two built-in defaults.
Internal encoding
a way of encoding wide character strings internally within the SICStus Prolog system. This is of interest to the user only if the foreign language interface is used in the program, or a system encoding hook function needs to be written. SICStus Prolog has a fixed internal encoding, which is UTF-8.

As discussed above there are several points where the users can influence the behavior of SICStus Prolog. The user can decide on

Let us call WCX mode a particular setting of these parameters.

Note that the selection of the character code set is conceptual only and need not be communicated to SICStus Prolog, as the decision materializes in the functions for the mapping and encodings.


Node:Prolog Level WCX Features, Next:, Previous:WCX Concepts, Up:Handling Wide Characters

Summary of Prolog level WCX features

SICStus Prolog has a Prolog flag, called wcx, whose value can be an arbitrary atom, and which is initialized to []. This flag is used at opening a stream, its value is normally passed to a user-defined hook function. This can be used to pass some information from Prolog to the hook function. In the example of A Sample WCX Box, which supports the selection of external encodings on a stream-by-stream basis, the value of the wcx flag is used to specify the encoding to be used for the newly opened stream.

The value of the wcx flag can be overridden by supplying a wcx(Value) option to open/4 and load_files/2. If such an option is present, then the Value is passed on to the hook function.

The wcx flag has a reserved value. The value wci (wide character internal encoding) signifies that the stream should use the SICStus Prolog internal encoding (UTF-8), bypassing the hook functions supplied by the user. This is appropriate, e.g. if a file with wide characters is to be produced, which has to be readable irrespective of the (possibly user supplied) encoding scheme.

Wide characters generally require several bytes to be input or output. Therefore, for each stream, SICStus Prolog keeps track of the number of bytes input or output, in addition to the number of (wide) characters. Accordingly there is a built-in predicate byte_count(+Stream,?N) for accessing the number of bytes read/written on a stream.

Note that the predicate character_count/2 returns the number of characters read or written, which may be less than the number of bytes, if some of the characters are multibyte. (On output streams the byte_count/2 can also be less than the character_count/2, if some codes, not belonging to the code-set handled, are not written out.)

Note that if a stream is opened as a binary stream:

open(..., ..., ..., [type(binary)])

then no wide character handling will take place; every character output will produce a single byte on the stream, and every byte input will be considered a separate character.


Node:WCX Environment Variables, Next:, Previous:Prolog Level WCX Features, Up:Handling Wide Characters

Selecting the WCX mode using environment variables

When the SICStus Prolog system starts up, its WCX mode is selected according to the value of the SP_CTYPE environment variable. The supported values of the SP_CTYPE environment variable are the following:

iso_8859_1 (default)

character code set:
0..255
character-type mapping:
according to the ISO 8859/1 standard; see Token String.
external encoding:
each character code is mapped to a single byte on the stream with the same value (trivial encoding).

utf8

character code set:
0..2147483647 (= 2^31-1)
character-type mapping:
according to ISO 8859/1 for codes 0..255. All codes above 255 are considered small-letters.
external encoding:
UTF-8

This WCX mode is primarily intended to support the UNICODE character set, but it also allows the input and output of character codes above the 16-bit UNICODE character code range.

euc

character code set:
a subset of 0..8388607 The exact character code set is described in Representation of EUC Wide Characters, together with its mapping to the standard external encoding.
character-type mapping:
according to ISO 8859/1 for codes 0..127. All codes above 127 are considered small-letters.
external encoding:
EUC encoding with the lengths of the sub-code-sets dependent on the locale.

In all three cases the system encoding is implemented as truncation to 8-bits, i.e. any code output to the operating system is taken modulo 256, any byte coming from the operating system is mapped to the code with the same value.

The figure below shows an example interaction with SICStus Prolog in EUC mode. For the role of the SP_CSETLEN environment variable, see Representation of EUC Wide Characters.

images/kterm.png

SICStus Prolog in EUC mode


Node:WCX Hooks, Next:, Previous:WCX Environment Variables, Up:Handling Wide Characters

Selecting the WCX mode using hooks

Users can have complete control over the way wide characters are handled by SICStus Prolog if they supply their own definitions of appropriate hook functions. A set of such functions, implementing a specific environment for handling wide characters is called a WCX box. A sample WCX box is described below (see A Sample WCX Box).

Plugging-in of the WCX hook functions can be performed by calling

void SP_set_wcx_hooks ( int usage,
                        SP_WcxOpenHook *wcx_open,
                        SP_WcxCloseHook *wcx_close,
                        SP_WcxCharTypeHook *wcx_chartype,
                        SP_WcxConvHook *wcx_from_os,
                        SP_WcxConvHook *wcx_to_os);

The effect of SP_set_wcx_hooks() is controlled by the value of usage. The remaining arguments are pointers to appropriate hook functions or NULL values, the latter implying that the hook should take some default value.

There are three independent aspects to be controlled, and usage should be supplied as a bitwise OR of chosen constant names for each aspect. The defaults have value 0, so need not be included. The aspects are the following:

  1. decide on the default code-set

    This decides the default behavior of the wcx_open and wcx_chartype hook functions (if both are supplied by the user, the choice of the default is irrelevant). The possible values are:


    WCX_USE_LATIN1 (default)
    WCX_USE_UTF8
    WCX_USE_EUC
    Select the behavior described above under titles iso_8859_1, utf8, and euc, respectively; see WCX Environment Variables.

  2. decide on the default system encoding

    The flags below determine what function to use for conversion from/to the operating system encoding, if such functions are not supplied by the user through the wcx_from_os and wcx_to_os arguments (if both are supplied by the user, the choice of default is irrelevant).


    WCX_OS_8BIT (default)
    Select the "truncation to 8-bits" behavior.
    WCX_OS_UTF8
    Select the UTF-8 encoding to be used for all communication with the operating system.

  3. decide on the preservation of ASCII, i.e. the codes in 0..127

    This is important if some of the conversion functions (wcx_from_os, wcx_to_os, and wcx_getc, wcx_putc, see later) are user-defined. In such cases it may be beneficial for the user to inform SICStus Prolog whether the supplied encoding functions preserve ASCII characters. (The default encodings do preserve ASCII.)


    WCX_PRESERVES_ASCII (default)
    Declare that the encodings preserve all ASCII characters, i.e. getting or putting an ASCII character need not go through the conversion functions, and for strings containing ASCII characters only, the system encoding conversions need not be invoked.
    WCX_CHANGES_ASCII
    Force the system to use the conversion functions even for ASCII characters and strings.

We now describe the role of the arguments following usage in the argument list of SP_set_wcx_hooks().

SP_WcxOpenHook *wcx_open
where typedef void (SP_WcxOpenHook) (SP_stream *s, SP_atom option, int context);

This function is called by SICStus Prolog for each s stream opened, except when the encoding to be used for the stream is pre-specified (binary files, files opened using the wci option, and the C streams created with contexts SP_STREAMHOOK_WCI and SP_STREAMHOOK_BIN).

The main task of the wcx_open hook is to associate the two WCX-processing functions with the stream, by storing them in the appropriate fields of the SP_stream data structure:

SP_WcxGetcHook *wcx_getc;
SP_WcxPutcHook *wcx_putc;
    

These fields are pointers to the functions performing the external decoding and encoding as described below. They are initialized to functions that truncate to 8 bits on output and zero-extend to 31 bits on input.


SP_WcxGetcHook *wcx_getc
where typedef int (SP_WcxGetcHook) (int first_byte, SP_stream *s, long *pbyte_count);

This function is generally invoked whenever a character has to be read from a stream. Before invoking this function, however, a byte is read from the stream by SICStus Prolog itself. If the byte read is an ASCII character (its value is < 128), and WCX_PRESERVES_ASCII is in force, then the byte read is deemed to be the next character code, and wcx_getc is not invoked. Otherwise, wcx_getc is invoked with the byte and stream in question and is expected to return the next character code.

The wcx_getc function may need to read additional bytes from the stream, if first byte signifies the start of a multi-byte character. A byte may be read from the stream s in the following way:

byte = s->sgetc((long)s->user_handle);
        

The wcx_getc function is expected to increment its *pbyte_count argument by 1 for each such byte read.

The default wcx_open hook will install a wcx_getc function according to the usage argument. The three default external decoding functions are also available to users through the SP_wcx_getc() function (see WCX Utility Functions).

SP_WcxPutcHook *wcx_putc
where typedef int (SP_WcxPutcHook) (int char_code, SP_stream *s, long *pbyte_count);

This function is generally invoked whenever a character has to be written to a stream. However, if the character code to be written is an ASCII character (its value is < 128), and WCX_PRESERVES_ASCII is in force, then the code is written directly on the stream, and wcx_putc is not invoked. Otherwise, wcx_putc is invoked with the character code and stream in question and is expected to do whatever is needed to output the character code to the stream.

This will require outputting one or more bytes to the stream. A byte byte can be written to the stream s in the following way:

return_code = s->sputc(byte,(long)s->user_handle);
        

The wcx_putc function is expected to return the return value of the last invocation of s->sputc, or -1 as an error code, if incapable of outputting the character code. The latter may be the case, for example, if the code to be output does not belong to the character code set in force. It is also expected to increment its *pbyte_count argument by 1 for each byte written.

The default wcx_open hook function will install a wcx_putc function according to the usage argument. The three default external encoding functions are also available to users through the SP_wcx_putc() function (see WCX Utility Functions).

In making a decision regarding the selection of these WCX-processing functions, the context and option arguments of the wcx_open hook can be used. The option argument is an atom. The context argument encodes the context of invocation. It is one of the following values


SP_STREAMHOOK_STDIN
SP_STREAMHOOK_STDOUT
SP_STREAMHOOK_STDERR
for the three standard streams,
SP_STREAMHOOK_OPEN
for streams created by open
SP_STREAMHOOK_NULL
for streams created by open_null_stream
SP_STREAMHOOK_LIB
for streams created from the libraries
SP_STREAMHOOK_C, SP_STREAMHOOK_C+1, ...
for streams created from C code via SP_make_stream()

The option argument comes from the user and it can carry some WCX-related information to be associated with the stream opened. For example, this can be used to implement a scheme supporting multiple encodings, supplied on a stream-by-stream basis, as shown in the sample WCX-box (see A Sample WCX Box).

If the stream is opened from Prolog code, the option argument for this hook function is derived from the wcx(Option) option of open/4 and load_files/2. If this option is not present, or the stream is opened using some other built-in, then the value of the wcx prolog flag will be passed on to the open hook.

If the stream is opened from C, via SP_make_stream(), then the option argument will be the value of the prolog flag wcx.

There is also a variant of SP_make_stream(), called SP_make_stream_context() which takes two additional arguments, the option and the context, to be passed on to the wcx_open hook (see WCX Foreign Interface).

The wcx_open hook can associate the information derived from option with the stream in question using a new field in the SP_stream data structure: void *wcx_info, initialized to NULL. If there is more information than can be stored in this field, or if the encoding to be implemented requires keeping track of a state, then the wcx_open hook should allocate sufficient amount of memory for storing the information and/or the state, using SP_malloc(), and deposit a pointer to that piece of memory in wcx_info.

The default wcx_open hook function ignores its option and context arguments and sets the wcx_getc and wcx_putc stream fields to functions performing the external decoding and encoding according to the usage argument of SP_set_wcx_hooks().

SP_WcxCloseHook *wcx_close
where typedef void (SP_WcxCloseHook) (SP_stream *s);

This hook function is called whenever a stream is closed, for which the wcx_open hook was invoked at its creation. The argument s points to the stream being closed. It can be used to implement the closing activities related to external encoding, e.g. freeing any memory allocated in wcx_open hook.

The default wcx_close hook function does nothing.

SP_WcxCharTypeHook *wcx_chartype
where typedef int (SP_WcxCharTypeHook) (int char_code);

This function should be prepared to take any char_code >= 128 and return one of the following constants:


CHT_LAYOUT_CHAR
for additional characters in the syntactic category layout-char,
CHT_SMALL_LETTER
for additional characters in the syntactic category small-letter,
CHT_CAPITAL_LETTER
for additional characters in the syntactic category capital-letter,
CHT_SYMBOL_CHAR
for additional characters in the syntactic category symbol-char,
CHT_SOLO_CHAR
for additional characters in the syntactic category solo-char.

Regarding the meaning of these syntactic categories, see Token String.

The value returned by this function is not expected to change over time, therefore, for efficiency reasons, its behavior is cached. The cache is cleared by SP_set_wcx_hooks().

As a help in implementing this function, SICStus Prolog provides the function SP_latin1_chartype(), which returns the character type category for the codes 1..255 according to the ISO 8859/1 standard.

Note that if a character code >= 512 is categorized as a layout-char, and a character with this code occurs within an atom being written out in quoted form (e.g. using writeq) in native sicstus mode (as opposed to iso mode), then this code will be output as itself, rather than an octal escape sequence. This is because in sicstus mode escape sequences consist of at most 3 octal digits.

SP_WcxConvHook *wcx_to_os
where typedef char* (SP_WcxConvHook) (char *string, int context);

This function is normally called each time SICStus Prolog wishes to communicate a string of possibly wide characters to the operating system. However, if the string in question consists of ASCII characters only, and WCX_PRESERVES_ASCII is in force, then wcx_to_os may not be called, and the original string may be passed to the operating system.

The first argument of wcx_to_os is a zero terminated string, using the internal encoding of SICStus Prolog, namely UTF-8. The function is expected to convert the string to a form required by the operating system, in the context described by the second, context argument, and to return the converted string. If no conversion is needed, it should simply return its first argument. Otherwise, the conversion should be done in a memory area controlled by this function (preferably a static buffer, reused each time the function is called).

The second argument specifies the context of conversion. It can be one of the following integer values:


WCX_FILE
the string is a file-name,
WCX_OPTION
the string is a command, a command line argument or an environment variable,
WCX_WINDOW_TITLE
the string is a window title,
WCX_C_CODE
the string is a C identifier (used, e.g. in the glue code)

SICStus Prolog provides a utility function SP_wci_code(), see below, for obtaining a wide character code from a UTF-8 encoded string, which can be used to implement the wcx_to_os hook function.

The default of the wcx_to_os function depends on the usage argument of SP_set_wcx_hooks(). If the value of usage includes WCX_OS_UTF8, then the function does no conversion, as the operating system uses the same encoding as SICStus Prolog. If the value of usage includes WCX_OS_8BIT, then the function decodes the UTF-8 encoded string and converts this sequence of codes into a sequence of bytes by truncating each code to 8 bits.

Note that the default wcx_to_os functions ignore their context argument.

SP_WcxConvHook *wcx_from_os
where typedef char* (SP_WcxConvHook) (char *string, int context);

This function is called each time SICStus Prolog receives from the operating system a zero terminated sequence of bytes possibly encoding a wide character string. The function is expected to convert the byte sequence, if needed, to a string in the internal encoding of SICStus Prolog (UTF-8), and return the converted string. The conversion should be done in a memory area controlled by this function (preferably a static buffer, reused each time the function is called, but different from the buffer used in wcx_to_os).

The second argument specifies the context of conversion, as in the case of wcx_to_os.

SICStus Prolog provides a utility function SP_code_wci(), see below, for converting a character code (up to 31 bits) into UTF-8 encoding, which can be used to implement the wcx_from_os hook function.

The default of the wcx_from_os function depends on the usage argument of SP_set_wcx_hooks(). If the value of usage includes WCX_OS_UTF8, then the function does no conversion. If the value of usage includes WCX_OS_8BIT, then the function transforms the string of 8-bit codes into an UTF-8 encoded string.

Note that the default wcx_from_os functions ignore their context argument.


Node:WCX Foreign Interface, Next:, Previous:WCX Hooks, Up:Handling Wide Characters

Summary of WCX features in the foreign interface

All strings passed to foreign code, or expected from foreign code, which correspond to atoms or lists of character codes on the Prolog side, are in the internal encoding form, UTF-8. Note that this is of concern only if the strings contain non-ASCII characters (e.g. accented letters in the latin1 encoding).

Specifically, the C arguments corresponding to the following foreign specifications are passed and received as strings in the internal encoding:

+chars +string +string(N)
-chars -string -string(N)
[-chars] [-string] [-string(N)]

Similarly, the following functions defined in the foreign interface expect and deliver internally encoded strings in their char * and char ** arguments.

int SP_put_string(SP_term_ref t, char *name)
int SP_put_list_chars(SP_term_ref t, SP_term_ref tail, char *s)
int SP_put_list_n_chars(SP_term_ref t, SP_term_ref tail,
                    long n, char *s)
int SP_get_string(SP_term_ref t, char **name)
int SP_get_list_chars(SP_term_ref t, char **s)
int SP_get_list_n_chars(SP_term_ref t, SP_term_ref tail,
                    long n, long *w, char *s)
void SP_puts(char *string)
void SP_fputs(char *string, SP_stream *s)
int  SP_printf(char *format, ...)
int  SP_fprintf(SP_stream *s, char *format, ...)
SP_atom SP_atom_from_string(char *s)
char *SP_string_from_atom(SP_atom a)
SP_pred_ref SP_predicate(char *name_string,
                     long arity,
                     char *module_string)
int SP_load(char *filename)
int SP_restore(char *filename)
int SP_read_from_string()

The following functions deliver or accept wide character codes (up to 31 bits), and read or write them on the appropriate stream in the external encoding form:

int  SP_getc(void)
int  SP_fgetc(SP_stream *s)
void SP_putc(int c)
void SP_fputc(int c, SP_stream *s)

In the following function, strings are expected in the encoding format relevant for the operating system:

int SP_initialize(int argc, char **argv, char *boot_path)

Here, argv is an array of strings, as received from the operating system. These strings will be transformed to internal form using the wcx_from_os(WCX_OPTION,...) hook function. Also boot_path is expected to be in the format file names are encoded, and wcx_from_os(WCX_FILE,...) will be used to decode it.

There are other functions in the foreign interface that take or return strings. For these, the encoding is not relevant, either because the strings are guaranteed to be ASCII (SP_error_message(), SP_put_number_chars(), SP_get_number_chars()), or because the strings in question have no relation to Prolog code, as in SP_on_fault(), SP_raise_fault().

The SP_make_stream_context() foreign interface function is a variant of SP_make_stream() with two additional arguments: option and context. This extended form can be used to create streams from C with specified WCX features.

The context argument the SP_make_stream_context function can be one of the following values:

SP_STREAMHOOK_WCI
SP_STREAMHOOK_BIN
SP_STREAMHOOK_C, SP_STREAMHOOK_C+1, ...

SP_STREAMHOOK_WCI means that input and output on the given stream should be performed using the SICStus internal encoding scheme, UTF-8, while SP_STREAMHOOK_BIN indicates that no encoding should be applied (binary files).

In the last two cases the wcx_open hook will not be called. In all other cases SP_make_stream_context will call the wcx_open hook function, with the option and context supplied to it. The option argument of SP_make_stream_context can be the standard representation of a Prolog atom, or the constant SP_WCX_FLAG, which prescribes that the value of the prolog flag wcx should be supplied to the open hook function.

The user may add further context constants for his own use, with values greater than SP_STREAMHOOK_C.


Node:WCX Features in Libraries, Next:, Previous:WCX Foreign Interface, Up:Handling Wide Characters

Summary of WCX-related features in the libraries

Some libraries are affected by the introduction of wide characters.

When using library(jasper) SICStus Prolog properly receives non-ASCII strings from Java, and similarly, non-ASCII strings can be correctly passed to Java. This is in contrast with versions of SICStus Prolog earlier then 3.8 (i.e. without the WCX extensions), where, for example, strings containing non-ASCII characters passed from Java to Prolog resulted in an UTF-8 encoded atom or character code list on the Prolog side.

Several predicates in libraries sockets, system and tcltk create streams. These now use the SP_make_stream_context() function, with SP_WCX_FLAG as the option and the relevant SP_STREAMHOOK_LIB constant as the context argument. For example, if the WCX mode is set using environment variables (see WCX Environment Variables), then this implies that the selected encoding will be used for streams created in the libraries. E.g. if the SP_CTYPE environment variable is set to utf8, then the output of non-ASCII characters to a socket stream will be done using UTF-8 encoding. If a wcx_open hook is supplied, then the user is free to select a different encoding for the libraries, as he is informed about the stream being opened by a library through the context argument of the wcx_open function.

Some of the arguments of library predicates contain atoms which are file names, environment variable names, commands, etc. If these contain non-ASCII characters, then they will be passed to the appropriate operating system function following a conversion to the system encoding in force (wcx_to_os hook), and similarly such atoms coming from the OS functions undergo a conversion from system encoding (wcx_from_os). Note however that host names (e.g. in system:host_name(S)) are assumed to be consisting of ASCII characters only.


Node:WCX Utility Functions, Next:, Previous:WCX Features in Libraries, Up:Handling Wide Characters

WCX related utility functions

The default functions for reading in and writing out character codes using one of the three supported encodings are available through

SP_WcxGetcHook *SP_wcx_getc(int usage);
SP_WcxPutcHook *SP_wcx_putc(int usage);

These functions return the decoding/encoding functions appropriate for usage, where the latter is one of the constants WCX_USE_LATIN1, WCX_USE_UTF8, WCX_USE_EUC.

The following utility functions may be useful when dealing with wide characters in internal encoding (WCI). These functions are modeled after multibyte character handling functions of Solaris.

int SP_wci_code(int *pcode, char *wci);

SP_wci_code() determines the number of bytes that comprise the internally encoded character pointed to by wci. Also, if pcode is not a null pointer, SP_wci_code() converts the internally encoded character to a wide character code and places the result in the object pointed to by pcode. (The value of the wide character corresponding to the null character is zero.) At most WCI_MAX_BYTES bytes will be examined, starting at the byte pointed to by wci.

If wci is a null pointer, SP_wci_code() simply returns 0. If wci is not a null pointer, then, if wci points to the null character, SP_wci_code() returns 0; if the next bytes form a valid internally encoded character, SP_wci_code() returns the number of bytes that comprise the internal encoding; otherwise wci does not point to a valid internally encoded character and SP_wci_code() returns the negated length of the invalid byte sequence. This latter case can not happen, if wci points to the beginning of a Prolog atom string, or to a position within such a string reached by repeated stepping over correctly encoded wide characters.


WCI_MAX_BYTES
WCI_MAX_BYTES is a constant defined by SICStus Prolog showing the maximal length (in bytes) of the internal encoding of a single character code. (As the internal encoding is UTF-8, this constant has the value 6).

int SP_wci_len(char *wci);

SP_wci_len() determines the number of bytes comprising the multi-byte character pointed to by wci. It is equivalent to:

SP_wci_code((int *)0, wci);
  

int SP_code_wci(char *wci, int code);

SP_code_wci() determines the number of bytes needed to represent the internal encoding of the character code, and, if wci is not a null pointer, stores the internal encoding in the array pointed to by wci. At most WCI_MAX_BYTES bytes are stored.

SP_code_wci() returns -1 if the value of code is outside the wide character code range; otherwise it returns the number of bytes that comprise the internal encoding of code.

The following functions give access to the default character type mapping and the currently selected operating system encoding/decoding functions.

int SP_latin1_chartype(int char_code);

SP_latin1_chartype returns the character type category of the character code char_code, according to the ISO 8859/1 code-set. The char_code value is assumed to be in the 1..255 range.

char* SP_to_os(char *string, int context)
char* SP_from_os(char *string, int context)

These functions simply invoke the wcx_to_os() and wcx_from_os() hook functions, respectively. These are useful in foreign functions which handle strings passed to/from the operating system, such as file names, options, etc.


Node:Representation of EUC Wide Characters, Next:, Previous:WCX Utility Functions, Up:Handling Wide Characters

Representation of EUC wide characters

As opposed to UNICODE, the definition of EUC specifies only the external representation. The actual wide character codes assigned to the multibyte characters are not specified. UNIX systems supporting EUC have their own C data type, wchar_t, which stores a wide character, but the mapping between this type and the external representation is not standardized.

We have decided to use a custom made mapping from the EUC encoding to the character code set, as opposed to using the UNIX type wchar_t. This decision was made so that the code set is machine independent and results in a compact representation of atoms.

EUC consists of four sub-code-sets, three of which can have multibyte external representation. Sub-code-set 0 consists of ASCII characters and is mapped one-to-one to codes 0..127. Sub-code-set 1 has an external representation of one to three bytes in the range 128-255, the length determined by the locale. Sub-code-sets 2 and 3 are similar, but their external representation is started by a so called single shift character code, known as SS2 and SS3, respectively. The following table shows the mapping from the EUC external encoding to SICStus Prolog character codes.

Sub-
code-set  External encoding                 Character code (binary)

 0        0xxxxxxx                          00000000 00000000 0xxxxxxx

 1        1xxxxxxx                          00000000 00000000 1xxxxxxx
          1xxxxxxx 1yyyyyyy                 00000000 xxxxxxx0 1yyyyyyy
          1xxxxxxx 1yyyyyyy 1zzzzzzzz       0xxxxxxx yyyyyyy0 1zzzzzzz

 2        SS2 1xxxxxxx                      00000000 00000001 0xxxxxxx
          SS2 1xxxxxxx 1yyyyyyy             00000000 xxxxxxx1 0yyyyyyy
          SS2 1xxxxxxx 1yyyyyyy 1zzzzzzzz   0xxxxxxx yyyyyyy1 0zzzzzzz

 3        SS3 1xxxxxxx                      00000000 00000001 1xxxxxxx
          SS3 1xxxxxxx 1yyyyyyy             00000000 xxxxxxx1 1yyyyyyy
          SS3 1xxxxxxx 1yyyyyyy 1zzzzzzzz   0xxxxxxx yyyyyyy1 1zzzzzzz

For sub-code-sets other than 0, the sub-code-set length indicated by the locale determines which of three mappings are used (but see below the SP_CSETLEN environment variable). When converting SICStus Prolog character codes to EUC on output, we ignore bits that have no significance in the mapping selected by the locale.

The byte lengths associated with the EUC sub-code-sets are determined by using the csetlen() function. If this function is not available in the system configuration used, then Japanese Solaris lengths are assumed, namely 2, 1, 2 for sub-code-sets 1, 2, and 3, respectively (the lengths exclude the single shift character).

To allow experimentation with sub-code-sets differing from the locale, the sub-code-set length values can be overridden by setting the SP_CSETLEN environment variable to xyz, where x, y, and z are digits in the range 1..3. Such a setting will cause the sub-code-sets 1, 2, 3 to have x, y, and z associated with them as their byte lengths.


Node:A Sample WCX Box, Previous:Representation of EUC Wide Characters, Up:Handling Wide Characters

A sample Wide Character Extension (WCX) box

This example implements a WCX box supporting the use of four external encodings within the same SICStus Prolog invocation: ISO Latin1, ISO Latin2 (ISO 8859/2), UNICODE, and EUC. The code is included in the distribution as library(wcx_example).

The default encoding functions supplied in SICStus Prolog deal with a single encoding only. However, the interface does allow the implementation of WCX boxes supporting different encodings for different streams.

A basic assumption in SICStus Prolog is that there is a single character set. If we are to support multiple encodings we have to map them into a single character set. For example, the single-byte character sets ISO Latin1 and ISO Latin2 can be easily mapped to the Unicode character set. On the other hand there does not seem to be a simple mapping of the whole of EUC character set to UNICODE or the other way round.

Therefore, in this example, we use a composite character set, which covers both EUC and Unicode, but does not deal with unifying the character codes of characters which appear in both character sets, except for the case of ASCII characters.

The figure below depicts the structure of the composite character set of the sample WCX box.

.------------------.
|  EUC             |
|                  |
|                  |
|        .+++++++++++++++++++++++++++.
|        +  ASCII  *  LATIN1  |      +
.--------+=========*==========       +
         + LATIN2  *                 +
         +**********                 +
         +                           +
         +                           +
         +                 UNICODE   +
         .+++++++++++++++++++++++++++.

This character code set uses character codes up to 24 bit wide:

0 =< code =< 2^16-1
A UNICODE character with the given code, including ASCII.
code = 2^16 + euc_code
A non-ASCII EUC character with code euc_code (as described in Representation of EUC Wide Characters).

The four external encodings supported by the sample WCX box can be specified on a stream-by-stream basis, by supplying a wcx(ENC) option to open/4, where ENC is one of the atoms latin1, latin2, unicode or euc.

The mapping of these external encodings to the composite character code set is done in the following way:

latin1
is mapped one-to-one to UNICODE codes 0x0..0xff
latin2
is mapped to UNICODE codes 0x0..0x02dd, using an appropriate conversion table for the non-ASCII part.
unicode
assumes UTF-8 external encoding and maps one-to-one to the 0x0..0xffff UNICODE range.
euc
assumes EUC external encoding and maps sub-code-set 0 to UNICODE range 0x0..0x7f, and sub-code-sets 1-3 to internal codes above 0xffff, as shown above.

Note that in order to support this composite character code set, we had to give up the ability to read and write UTF-8-encoded files with character codes above 0xffff (which is possible using the built-in utf8 WCX-mode of SICStus Prolog, (see Prolog Level WCX Features)).

The example uses a primitive character-type mapping: characters in the 0x80-0xff range are classified according to the latin1 encoding, above that range all characters are considered small-letters. However, as an example of re-classification, code 0xa1 (inverted exclamation mark) is categorized as solo-char.

The default system encoding is used (truncate to 8-bits).

The box has to be initialized by calling the C function wcx_setup(), which first reads the environment variable WCX_TYPE, and uses its value as the default encoding. It then calls SP_set_wcx_hooks(), and initializes its own conversion tables. In a runtime system wcx_setup() should be called before SP_initialize(), so that it effects the standard streams created there. The second phase of initialization, wcx_init_atoms(), has to be called after SP_initialize(), to set up variables storing the atoms naming the external encodings.

In a development system the two initialization phases can be put together, this is implemented as wcx_init(), and is declared to be a foreign entry point in wcx.pl.

On any subsequent creation of a stream, the hook function my_wcx_open() is called. This sets the wide character get and put function pointers in the stream according to the atom supplied in the wcx(...) option, or according to the value of the prolog flag wcx.

Within the put function it may happen that a character code is to be output, which the given encoding cannot accommodate (a non-ASCII Unicode character on an EUC stream or vice-versa). No bytes are output in such a case and -1 is returned as an error code.

There is an additional foreign C function implemented in the sample WCX box: wcx_set_encoding(), available from Prolog as set_encoding/2. This allows changing the encoding of an already open stream. This is used primarily for standard input-output streams, while experimenting with the box.


Node:Writing Efficient Programs, Next:, Previous:Handling Wide Characters, Up:Top

Writing Efficient Programs


Node:Overview, Next:, Previous:Writing Efficient Programs, Up:Writing Efficient Programs

Overview

This chapter gives a number of tips on how to organize your programs for increased efficiency. A lot of clarity and efficiency is gained by sticking to a few basic rules. This list is necessarily very incomplete. The reader is referred to textbooks such as [O'Keefe 90] for a thorough exposition of the elements of Prolog programming style and techniques.


Node:The Cut, Next:, Previous:Overview, Up:Writing Efficient Programs

The Cut


Node:Cut Overview, Next:, Previous:The Cut, Up:The Cut

Overview

One of the more difficult things to master when learning Prolog is the proper use of the cut. Often, when beginners find unexpected backtracking occurring in their programs, they try to prevent it by inserting cuts in a rather random fashion. This makes the programs harder to understand and sometimes stops them from working.

During program development, each predicate in a program should be considered independently to determine whether or not it should be able to succeed more than once. In most applications, many predicates should at most succeed only once; that is, they should be determinate. Having decided that a predicate should be determinate, it should be verified that, in fact, it is. The debugger can help in verifying that a predicate is determinate (see The Determinacy Checker).


Node:Making Predicates Determinate, Next:, Previous:Cut Overview, Up:The Cut

Making Predicates Determinate

Consider the following predicate which calculates the factorial of a number:

fac(0, 1).
fac(N, X) :-
        N1 is N - 1,
        fac(N1, Y),
        X is N * Y.

The factorial of 5 can be found by typing:

| ?- fac(5, X).

X = 120

However, backtracking into the above predicate by typing a semicolon at this point, causes an infinite loop because the system starts attempting to satisfy the goals fac(-1, X)., fac(-2, X)., etc. The problem is that there are two clauses that match the goal fac(0, F)., but the effect of the second clause on backtracking has not been taken into account. There are at least three possible ways of fixing this:

  1. Efficient solution: rewrite the first clause as
    fac(0,1) :- !.
    

    Adding the cut essentially makes the first solution the only one for the factorial of 0 and hence solves the immediate problem. This solution is space-efficient because as soon as Prolog encounters the cut, it knows that the predicate is determinate. Thus, when it tries the second clause, it can throw away the information it would otherwise need in order to backtrack to this point. Unfortunately, if this solution is implemented, typing fac(-1, X) still generates an infinite search.

  2. Robust solution: rewrite the second clause as
    fac(N, X) :-
            N > 0,
            N1 is N - 1,
            fac(N1, Y),
            X is N * Y.
    

    This also solves the problem, but it is a more robust solution because this way it is impossible to get into an infinite loop.

    This solution makes the predicate logically determinate--there is only one possible clause for any input--but the Prolog system is unable to detect this and must waste space for backtracking information. The space-efficiency point is more important than it may at first seem; if fac/2 is called from another determinate predicate, and if the cut is omitted, Prolog cannot detect the fact that fac/2 is determinate. Therefore, it will not be able to detect the fact that the calling predicate is determinate, and space will be wasted for the calling predicate as well as for fac/2 itself. This argument applies again if the calling predicate is itself called by a determinate predicate, and so on, so that the cost of an omitted cut can be very high in certain circumstances.

  3. Preferred solution: rewrite the entire predicate as the single clause
    fac(N, X) :-
        (   N > 0 ->
                N1 is N - 1,
                fac(N1, Y),
                X is N * Y
        ;   N =:= 0 ->
                X = 1
        ).
    

    This solution is as robust as solution 2, and more efficient than solution 1, since it exploits conditionals with arithmetic tests (see Conditionals and Disjunction for more information on optimization using conditionals).


Node:Placement of Cuts, Next:, Previous:Making Predicates Determinate, Up:The Cut

Placement of Cuts

Programs can often be made more readable by the placing of cuts as early as possible in clauses. For example, consider the predicate p/0 defined by

p :- a, b, !, c, d.
p :- e, f.

Suppose that b/0 is a test that determines which clause of p/0 applies; a/0 may or may not be a test, but c/0 and d/0 are not supposed to fail under any circumstances. A cut is most appropriately placed after the call to b/0. If in fact a/0 is the test and b/0 is not supposed to fail, then it would be much clearer to move the cut before the call to b/0.

A tool to aid in determinacy checking is included in the distribution. It is described in depth in The Determinacy Checker.


Node:Terminating a Backtracking Loop, Previous:Placement of Cuts, Up:The Cut

Terminating a Backtracking Loop

Cut is also commonly used in conjunction with the generate-and-test programming paradigm. For example, consider the predicate find_solution/1 defined by

find_solution(X) :-
        candidate_solution(X),
        test_solution(X),
        !.

where candidate_solution/1 generates possible answers on backtracking. The intent is to stop generating candidates as soon as one is found that satisfies test_solution/1. If the cut were omitted, a future failure could cause backtracking into this clause and restart the generation of candidate solutions. A similar example is shown below:

process_file(F) :-
        see(F),
        repeat,
            read(X),
            process_and_fail(X),
        !,
        seen.

process_and_fail(end_of_file) :- !.
process_and_fail(X) :-
        process(X),
        fail.

The cut in process_file/1 is another example of terminating a generate-and-test loop. In general, a cut should always be placed after a repeat/0 so that the backtracking loop is clearly terminated. If the cut were omitted in this case, on later backtracking Prolog might try to read another term after the end of the file had been reached.

The cut in process_and_fail/1 might be considered unnecessary because, assuming the call shown is the only call to it, the cut in process_file/1 ensures that backtracking into process_and_fail/1 can never happen. While this is true, it is also a good safeguard to include a cut in process_and_fail/1 because someone may unwittingly change process_file/1 in the future.


Node:Indexing, Next:, Previous:The Cut, Up:Writing Efficient Programs

Indexing


Node:Indexing Overview, Next:, Previous:Indexing, Up:Indexing

Overview

In SICStus Prolog, predicates are indexed on their first arguments. This means that when a predicate is called with an instantiated first argument, a hash table is used to gain fast access to only those clauses having a first argument with the same primary functor as the one in the predicate call. If the first argument is atomic, only clauses with a matching first argument are accessed. Indexes are maintained automatically by the built-in predicates manipulating the Prolog database (for example, assert/1, retract/1, and compile/1.

Keeping this feature in mind when writing programs can help speed their execution. Some hints for program structuring that will best use the indexing facility are given below. Note that dynamic predicates as well as static predicates are indexed. The programming hints given in this section apply equally to static and dynamic code.


Node:Data Tables, Next:, Previous:Indexing Overview, Up:Indexing

Data Tables

The major advantage of indexing is that it provides fast access to tables of data. For example, a table of employee records might be represented as shown below in order to gain fast access to the records by employee name:

%  employee(LastName,FirstNames,Department,Salary,DateOfBirth)

employee('Smith', ['John'], sales,       20000, 1-1-59).
employee('Jones', ['Mary'], engineering, 30000, 5-28-56).
 ...

If fast access to the data via department is also desired, the data can be organized little differently. The employee records can be indexed by some unique identifier, such as employee number, and additional tables can be created to facilitate access to this table, as shown in the example below. For example,

%  employee(Id,LastName,FirstNames,Department,Salary,DateOfBirth)

employee(1000000, 'Smith', ['John'], sales,       20000, 1-1-59).
employee(1000020, 'Jones', ['Mary'], engineering, 30000, 5-28-56).
 ...

%  employee_name(LastName,EmpId)

employee_name('Smith', 1000000).
employee_name('Jones', 1000020).
 ...

%  department_member(Department,EmpId)

department_member(sales,       1000000).
department_member(engineering, 1000020).
 ...

Indexing would now allow fast access to the records of every employee named Smith, and these could then be backtracked through looking for John Smith. For example:

| ?- employee_name('Smith', Id),
     employee(Id, 'Smith', ['John'], Dept, Sal, DoB).

Similarly, all the members of the engineering department born since 1965 could be efficiently found like this:

| ?- department_member(engineering, Id),
     employee(Id, LN, FN, engineering, _, M-D-Y),
     Y > 65.


Node:Determinacy Detection, Previous:Data Tables, Up:Indexing

Determinacy Detection

The other advantage of indexing is that it often makes possible early detection of determinacy, even if cuts are not included in the program. For example, consider the following simple predicate which joins two lists together:

concat([], L, L).
concat([X|L1], L2, [X|L3]) :- concat(L1, L2, L3).

If this predicate is called with an instantiated first argument, the first argument indexing of SICStus Prolog will recognize that the call is determinate--only one of the two clauses for concat/3 can possibly apply. Thus, the Prolog system knows it does not have to store backtracking information for the call. This significantly reduces memory use and execution time.

Determinacy detection can also reduce the number of cuts in predicates. In the above example, if there was no indexing, a cut would not strictly be needed in the first clause as long as the predicate was always to be called with the first argument instantiated. If the first clause matched, then the second clause could not possibly match; discovery of this fact, however, would be postponed until backtracking. The programmer might thus be tempted to use a cut in the first clause to signal determinacy and recover space for backtracking information as early as possible.

With indexing, if the example predicate is always called with its first argument instantiated, backtracking information is never stored. This gives substantial performance improvements over using a cut rather than indexing to force determinacy. At the same time greater flexibility is maintained: the predicate can now be used in a nondeterminate fashion as well, as in

| ?- concat(L1, L2, [a,b,c,d]).

which will generate on backtracking all the possible partitions of the list [a,b,c,d] on backtracking. If a cut had been used in the first clause, this would not work.


Node:Last Clause Determinacy Detection, Next:, Previous:Indexing, Up:Writing Efficient Programs

Last Clause Determinacy Detection

Even if the determinacy detection made possible by indexing is unavailable to a predicate call, SICStus Prolog still can detect determinacy before determinate exit from the predicate. Space for backtracking information can thus be recovered as early as possible, reducing memory requirements and increasing performance. For instance, the predicate member/2 (found in the SICStus Prolog library) could be defined by:

member(Element, [Element|_]).
member(Element, [_|Rest]) :-
        member(Element, Rest).

member/2 might be called with an instantiated first argument in order to check for membership of the argument in a list, which is passed as a second argument, as in

| ?- member(4, [1,2,3,4]).

The first arguments of both clauses of member/2 are variables, so first argument indexing cannot be used. However, determinacy can still be detected before determinate exit from the predicate. This is because on entry to the last clause of a nondeterminate predicate, a call becomes effectively determinate; it can tell that it has no more clauses to backtrack to. Thus, backtracking information is no longer needed, and its space can be reclaimed. In the example, each time a call fails to match the first clause and backtracks to the second (last) clause, backtracking information for the call is automatically deleted.

Because of last clause determinacy detection, a cut is never needed as the first subgoal in the last clause of a predicate. Backtracking information will have been deleted before a cut in the last clause is executed, so the cut will have no effect except to waste time.

Note that last clause determinacy detection is exploited by dynamic code as well as static code in SICStus Prolog.


Node:The Determinacy Checker, Next:, Previous:Last Clause Determinacy Detection, Up:Writing Efficient Programs

The Determinacy Checker

The determinacy checker can help you spot unwanted nondeterminacy in your programs. This tool examines your program source code and points out places where nondeterminacy may arise. It is not in general possible to find exactly which parts of a program will be nondeterminate without actually running the program, but this tool can find most unwanted nondeterminacy. Unintended nondeterminacy should be eradicated because

  1. it may give you wrong answers on backtracking
  2. it may cause a lot of memory to be wasted


Node:Using the Determinacy Checker, Next:, Previous:The Determinacy Checker, Up:The Determinacy Checker

Using the Determinacy Checker

There are two different ways to use the determinacy checker, either as a stand-alone tool, or during compilation. You may use it whichever way fits best with the way you work. Either way, it will discover the same nondeterminacy in your program.

The stand-alone determinacy checker is called spdet, and is run from the shell prompt, specifying the names of the Prolog source files you wish to check. You may omit the .pl suffix if you like.

% spdet [-r] [-d] [-D] [-i ifile] fspec...

The spdet tool is automatically installed when you install SICStus Prolog. The tool takes a number of options:

-r
Process files recursively, fully checking the specified files and all the files they load.
-d
Print out declarations that should be added.
-D
Print out all needed declarations.
-i ifile
An initialization file, which is loaded before processing begins.

The determinacy checker can also be integrated into the compilation process, so that you receive warnings about unwanted nondeterminacy along with warnings about singleton variables or discontiguous clauses. To make this happen, simply insert the line

:- load_files(library(detcheck),
              [when(compile_time), if(changed)]).

Once this line is added, every time that file is loaded, it will be checked for unwanted nondeterminacy.


Node:Declaring Nondeterminacy, Next:, Previous:Using the Determinacy Checker, Up:The Determinacy Checker

Declaring Nondeterminacy

Some predicates are intended to be nondeterminate. By declaring intended nondeterminacy, you avoid warnings about predicates you intend to be nondeterminate. Equally importantly, you also inform the determinacy checker about nondeterminate predicates. It uses this information to identify unwanted nondeterminacy.

Nondeterminacy is declared by putting a declaration of the form

:- nondet name/arity.

in your source file. This is similar to a dynamic or discontiguous declaration. You may have multiple nondet declarations, and a single declaration may mention several predicates, separating them by commas.

Similarly, a predicate P/N may be classified as nondeterminate by the checker, whereas in reality it is determinate. This may happen e.g. if P/N calls a dynamic predicate which in reality never has more than one clause. To prevent false alarms asiring from this, you can inform the checker about determinate predicates by declarations of the form:

:- det name/arity.

If you wish to include det and nondet declarations in your file and you plan to use the stand-alone determinacy checker, you must include the line

:- load_files(library(nondetdecl),
              [when(compile_time), if(changed)]).

near the top of each file that contains such declarations. If you use the integrated determinacy checker, you do not need (and should not have) this line.


Node:Checker Output, Next:, Previous:Declaring Nondeterminacy, Up:The Determinacy Checker

Checker Output

The output of the determinacy checker is quite simple. For each clause containing unexpected nondeterminacy, a single line is printed showing the module, name, arity, and clause number (counting from 1). The form of the information is:

* Non-determinate: module:name/arity (clause number)

A second line for each nondeterminate clause indicates the cause of the nondeterminacy. The recognized causes are:

The determinacy checker also occasionally prints warnings when declarations are made too late in the file or not at all. For example, if you include a dynamic, nondet, or discontiguous declaration for a predicate after some clauses for that predicate, or if you put a dynamic or nondet declaration for a predicate after a clause that includes a call to that predicate, the determinacy checker may have missed some nondeterminacy in your program. The checker also detects undeclared discontiguous predicates, which may also have undetected nondeterminacy. Finally, the checker looks for goals in your program that indicate that predicates are dynamic; if no dynamic declaration for those predicates exists, you will be warned.

These warnings take the following form:

! warning: predicate module:name/arity is property.
!          Some nondeterminacy may have been missed.
!          Add (or move) the directive
!              :- property module:name/arity.
!          near the top of this file.


Node:Example, Next:, Previous:Checker Output, Up:The Determinacy Checker

Example

Here is an example file:

:- load_files(library(detcheck),
              [when(compile_time), if(changed)]).

parent(abe, rob).
parent(abe, sam).
parent(betty, rob).
parent(betty, sam).

is_parent(Parent) :- parent(Parent, _).

The determinacy checker notices that the first arguments of clauses 1 and 2 have the same principal functor, and similarly for clauses 3 and 4. It reports:

* Non-determinate: user:parent/2 (clause 1)
*     Indexing cannot distinguish this from clause 2.
* Non-determinate: user:parent/2 (clause 3)
*     Indexing cannot distinguish this from clause 4.

In fact, parent/2 should be nondeterminate, so we should add the declaration

:- nondet parent/2.

before the clauses for parent/2. If run again after modifying file, the determinacy checker prints:

* Non-determinate: user:is_parent/1 (clause 1)
*     This clause calls user:parent/2, which may be nondeterminate.

It no longer complains about parent/2 being nondeterminate, since this is declared. But now it notices that because parent/2 is nondeterminate, then so is is_parent/1.


Node:Options, Next:, Previous:Example, Up:The Determinacy Checker

Options

When run from the command line, the determinacy checker has a few options to control its workings.

The -r option specifies that the checker should recursively check files in such a way that it finds nondeterminacy caused by calls to other nondeterminate predicates, whether they are declared so or not. Also, predicates that appear to determinate will be treated as such, whether declared nondet or not. This option is quite useful when first running the checker on a file, as it will find all predicates that should be either made determinate or declared nondet at once. Without this option, each time a nondet declaration is added, the checker may find previously unnoticed nondeterminacy.

For example, if the original example above, without any nondet declarations, were checked with the -r option, the output would be:

* Non-determinate: user:parent/2 (clause 1)
*     Indexing cannot distinguish this from clause 2.
* Non-determinate: user:parent/2 (clause 3)
*     Indexing cannot distinguish this from clause 4.
* Non-determinate: user:is_parent/1 (clause 1)
*     Calls nondet predicate user:parent/2.

The -d option causes the tool to print out the needed nondet declarations. These can be readily pasted into the source files. Note that it only prints the nondet declarations that are not already present in the files. However, these declarations should not be pasted into your code without each one first being checked to see if the reported nondeterminacy is intended.

The -D option is like -d, except that it prints out all nondet declarations that should appear, whether they are already in the file or not. This is useful if you prefer to replace all old nondet declarations with new ones.

Your code will probably rely on operator declarations and possibly term expansion. The determinacy checker handles this in much the same way as fcompile/1: you must supply an initialization file, using the -i ifile option. Contrary to fcompile/1, spdet will execute any operator declaration it encounters.


Node:What is Detected, Previous:Options, Up:The Determinacy Checker

What is Detected

As mentioned earlier, it is not in general possible to find exactly which places in a program will lead to nondeterminacy. The determinacy checker gives predicates the benefit of the doubt: when it's possible that a predicate will be determinate, it will not be reported. The checker will only report places in your program which will be nondeterminate regardless of which arguments are bound. Despite this, the checker catches most unwanted nondeterminacy in practice.

The determinacy checker looks for the following sources of nondeterminacy:


Node:Last Call Optimization, Next:, Previous:The Determinacy Checker, Up:Writing Efficient Programs

Last Call Optimization

Another important efficiency feature of SICStus Prolog is last call optimization. This is a space optimization technique which applies when a predicate is determinate at the point where it is about to call the last goal in the body of a clause. For example,

% for(Int, Lower, Upper)
% Lower and Upper should be integers such that Lower =< Upper.
% Int should be uninstantiated; it will be bound successively on
% backtracking to Lower, Lower+1, ... Upper.

for(Int, Int, _Upper).
for(Int, Lower, Upper) :-
        Lower < Upper,
        Next is Lower + 1,
        for(Int, Next, Upper).

This predicate is determinate at the point where the recursive call is about to be made, since this is the last clause and the preceding goals (<)/2 and is/2) are determinate. Thus last call optimization can be applied; effectively, the stack space being used for the current predicate call is reclaimed before the recursive call is made. This means that this predicate uses only a constant amount of space, no matter how deep the recursion.


Node:Accumulating Parameters, Next:, Previous:Last Call Optimization, Up:Last Call Optimization

Accumulating Parameters

To take best advantage of this feature, make sure that goals in recursive predicates are determinate, and whenever possible put the recursive call at the end of the predicate.

This isn't always possible, but often can be done through the use of accumulating parameters. An accumulating parameter is an added argument to a predicate that builds up the result as computation proceeds. For example, in our factorial example, the last goal in the body of the recursive case is is/2, not the recursive call to fac/2.

fac(N, X) :-
    (   N > 0 ->
            N1 is N - 1,
            fac(N1, Y),
            X is N * Y
    ;   N =:= 0 ->
            X = 1
    ).

This can be corrected by adding another argument to fac/2 to accumulate the factorial.

fac(N, X) :- fac(N, 1, X).

%  fac(+N, +M, -X)
%  X is M * the factorial of N.

fac(N, M, X) :-
    (   N > 0 ->
            N1 is N - 1,
            M1 is N * M,
            fac(N1, M1, X)
    ;   N =:= 0 ->
            X = M
    ).

Here, we do the multiplication before calling fac/3 recursively. Note that we supply the base case, 1, at the start of the computation, and that we are multiplying by decreasing numbers. In the earlier version, fac/2, we multiply after the recursive call, and so we multiply by increasing numbers. Effectively, the new version builds the result backwards. This is correct because multiplication is associative.


Node:Accumulating Lists, Previous:Accumulating Parameters, Up:Last Call Optimization

Accumulating Lists

This technique becomes much more important when extended to lists, as in this case it can save much building of unneeded lists through unnecessary calls to append sublists together. For example, the naive way to reverse a list is:

nreverse([], []).
nreverse([H|T], L) :-
        nreverse(T, L1),
        append(L1, [H], L).

This is very wasteful, since each call to append/3 copies the initial part of the list, and adds one element to it. Fortunately, this can be very easily rewritten to use an accumulating parameter:

reverse(L1, L2) :- reverse(L1, [], L2).

%  reverse(+X, +Y, -Z)
%  Z is X reversed, followed by Y
reverse([], Z, Z).
reverse([H|T], L0, L) :-
        reverse(T, [H|L0], L).

This version of reverse is many times faster than the naive version, and uses much less memory. The key to understanding the behavior of this predicate is the observation made earlier: using an accumulating parameter, we build the result backwards.

Don't let this confuse you. Building a list forward is easy. For example, a predicate which returns a list L of consecutive numbers from 1 to N could be written in two different ways: counting up and collecting the resulting list forward, or counting down and accumulating the result backward.

iota1(N, L) :- iota1(1, N, L).
iota1(N, Max, L) :-
        (   N > Max ->
                L = []
        ;   N1 is N+1,
            L = [N|L1],
            iota1(N1, Max, L1)
        ).

or,

iota2(N, L) :- iota2(N, [], L).
iota2(N, L0, L) :-
        (   N =< 0 ->
                L = L0
        ;   N1 is N-1,
            iota2(N1, [N|L0], L)
        ).

Both versions generate the same results, and neither waste any space. The second version is slightly faster. Choose whichever approach you prefer.


Node:Building and Dismantling Terms, Next:, Previous:Last Call Optimization, Up:Writing Efficient Programs

Building and Dismantling Terms

The built-in predicate (=..)/2 is a clear way of building terms and taking them apart. However, it is almost never the most efficient way.

functor/3 and arg/3 are generally much more efficient, though less direct. The best blend of efficiency and clarity is to write a clearly-named predicate which implements the desired operation and to use functor/3 and arg/3 in that predicate.

Here is an actual example. The task is to reimplement the built-in predicate (==)/2. The first variant uses (=..)/2 (this symbol is pronounced "univ" for historical reasons). Some Prolog textbooks recommend code similar to this.

ident_univ(X, Y) :-
        var(X),                 % If X is a variable,
        !,
        var(Y),                 % so must Y be, and
        samevar(X, Y).          % they must be the same.
ident_univ(X, Y) :-             % If X is not a variable,
        nonvar(Y),              % neither may Y be;
        X =.. [F|L],            % they must have the
        Y =.. [F|M],            % same function symbol F
        ident_list(L, M).       % and identical arguments

ident_list([], []).
ident_list([H1|T1], [H2|T2]) :-
        ident_univ(H1, H2),
        ident_list(T1, T2).

samevar(29, Y) :-               % If binding X to 29
        var(Y),                 % leaves Y unbound,
        !,                      % they were not the same
        fail.                   % variable.
samevar(_, _).                  % Otherwise they were.

This code performs the function intended; however, every time it touches a non-variable term of arity N, it constructs a list with N+1 elements, and if the two terms are identical, these lists are reclaimed only when backtracked over or garbage-collected.

Better code uses functor/3 and arg/3.

ident_farg(X, Y) :-
        (   var(X) ->           % If X is a variable,
                var(Y),         % so must Y be, and
                samevar(X, Y)   % they must be the same;
        ;   nonvar(Y),          % otherwise Y must be nonvar
            functor(X, F, N),   % The principal functors of X
            functor(Y, F, N),   % and Y must be identical,
            ident_farg(N, X, Y) % including the last N args.
        ).

ident_farg(0, _, _) :- !.
ident_farg(N, X, Y) :-          % The last N arguments are
        arg(N, X, Xn),          % identical
        arg(N, Y, Yn),          % if the Nth arguments
        ident_farg(Xn, Yn),     % are identical,
        M is N-1,               % and the last N-1 arguments
        ident_farg(M, X, Y).    % are also identical.

This approach to walking through terms using functor/3 and arg/3 avoids the construction of useless lists.

The pattern shown in the example, in which a predicate of arity K calls an auxiliary predicate of the same name of arity K+1 (the additional argument denoting the number of items remaining to process), is very common. It is not necessary to use the same name for this auxiliary predicate, but this convention is generally less prone to confusion.

In order to simply find out the principal function symbol of a term, use

| ?- the_term_is(Term),
|    functor(Term, FunctionSymbol, _).

The use of (=..)/2, as in

| ?- the_term_is(Term),
|    Term =.. [FunctionSymbol|_].
is wasteful, and should generally be avoided. The same remark applies if the arity of a term is desired.

(=..)/2 should not be used to locate a particular argument of some term. For example, instead of

Term =.. [_F,_,ArgTwo|_]

you should write

arg(2, Term, ArgTwo)

It is generally easier to get the explicit number 2 right than to write the correct number of anonymous variables in the call to (=..)/2. Other people reading the program will find the call to arg/3 a much clearer expression of the program's intent. The program will also be more efficient. Even if several arguments of a term must be located, it is clearer and more efficient to write

arg(1, Term, First),
arg(3, Term, Third),
arg(4, Term, Fourth)

than to write

Term =.. [_,First,_,Third,Fourth|_]

Finally, (=..)/2 should not be used when the functor of the term to be operated on is known (that is, when both the function symbol and the arity are known). For example, to make a new term with the same function symbol and first arguments as another term, but one additional argument, the obvious solution might seem to be to write something like the following:

add_date(OldItem, Date, NewItem) :-
        OldItem =.. [item,Type,Ship,Serial],
        NewItem =.. [item,Type,Ship,Serial,Date].

However, this could be expressed more clearly and more efficiently as

add_date(OldItem, Date, NewItem) :-
        OldItem = item(Type,Ship,Serial),
        NewItem = item(Type,Ship,Serial,Date).

or even

add_date(item(Type,Ship,Serial),
         Date,
         item(Type,Ship,Serial,Date)
        ).


Node:Conditionals and Disjunction, Next:, Previous:Building and Dismantling Terms, Up:Writing Efficient Programs

Conditionals and Disjunction

There is an efficiency advantage in using conditionals whose test part consists only of arithmetic comparisons or type tests. Consider the following alternative definitions of the predicate type_of_character/2. In the first definition, four clauses are used to group characters on the basis of arithmetic comparisons.

type_of_character(Ch, Type) :-
        Ch >= "a", Ch =< "z",
        !,
        Type = lowercase.
type_of_character(Ch, Type) :-
        Ch >= "A", Ch =< "Z",
        !,
        Type = uppercase.
type_of_character(Ch, Type) :-
        Ch >= "0", Ch =< "9",
        !,
        Type = digit.
type_of_character(_Ch, Type) :-
        Type = other.

In the second definition, a single clause with a conditional is used. The compiler generates equivalent, optimized code for both versions.

type_of_character(Ch, Type) :-
        (   Ch >= "a", Ch =< "z" ->
                Type = lowercase
        ;   Ch >= "A", Ch =< "Z" ->
                Type = uppercase
        ;   Ch >= "0", Ch =< "9" ->
                Type = digit
        ;   otherwise ->
                Type = other
        ).

Following is a list of builtin predicates that are compiled efficiently in conditionals:

atom/1
atomic/1
callable/1
compound/1
float/1
ground/1
integer/1
nonvar/1
number/1
simple/1
var/1
</2
=</2
=:=/2
=\=/2
>=/2
>/2
@</2
@=</2
==/2
\==/2
@>=/2
@>/2

This optimization is actually somewhat more general than what is described above. A sequence of guarded clauses:

Head1 :- Guard1, !, Body1.
...
Headm :- Guardm, !, Bodym.
Headn :- Bodym.

is eligible for the same optimization, provided that the arguments of the clause heads are all unique variables and that the "guards" are simple tests as listed above.


Node:Programming Examples, Next:, Previous:Conditionals and Disjunction, Up:Writing Efficient Programs

Programming Examples

The rest of this chapter contains a number of simple examples of Prolog programming, illustrating some of the techniques described above.


Node:Simple List, Next:, Previous:Programming Examples, Up:Programming Examples

Simple List Processing

The goal concatenate(L1,L2,L3) is true if list L3 consists of the elements of list L1 concatenated with the elements of list L2. The goal member(X,L) is true if X is one of the elements of list L. The goal reverse(L1,L2) is true if list L2 consists of the elements of list L1 in reverse order.

concatenate([], L, L).
concatenate([X|L1], L2, [X|L3]) :- concatenate(L1, L2, L3).

member(X, [X|_]).
member(X, [_|L]) :- member(X, L).

reverse(L, L1) :- reverse_concatenate(L, [], L1).

reverse_concatenate([], L, L).
reverse_concatenate([X|L1], L2, L3) :-
        reverse_concatenate(L1, [X|L2], L3).


Node:Family Example, Next:, Previous:Simple List, Up:Programming Examples

Family Example (descendants)

The goal descendant(X,Y) is true if Y is a descendant of X.

descendant(X, Y) :- offspring(X, Y).
descendant(X, Z) :- offspring(X, Y), descendant(Y, Z).

offspring(abraham, ishmael).
offspring(abraham, isaac).
offspring(isaac, esau).
offspring(isaac, jacob).

If for example the query

| ?- descendant(abraham, X).

is executed, Prolog's backtracking results in different descendants of Abraham being returned as successive instances of the variable X, i.e.

X = ishmael
X = isaac
X = esau
X = jacob


Node:Association Lists, Next:, Previous:Family Example, Up:Programming Examples

Association List Primitives

These predicates implement "association list" primitives. They use a binary tree representation. Thus the time complexity for these predicates is O(lg N), where N is the number of keys. These predicates also illustrate the use of compare/3 (see Term Compare) for case analysis.

The goal get_assoc(Key, Assoc, Value) is true when Key is identical to one of the keys in Assoc, and Value unifies with the associated value.

get_assoc(Key, t(K,V,L,R), Val) :-
        compare(Rel, Key, K),
        get_assoc(Rel, Key, V, L, R, Val).

get_assoc(=, _, Val, _, _, Val).
get_assoc(<, Key, _, Tree, _, Val) :-
        get_assoc(Key, Tree, Val).
get_assoc(>, Key, _, _, Tree, Val) :-
        get_assoc(Key, Tree, Val).


Node:Derivative, Next:, Previous:Association Lists, Up:Programming Examples

Differentiation

The goal d(E1, X, E2) is true if expression E2 is a possible form for the derivative of expression E1 with respect to X.

d(X, X, D) :- atomic(X), !, D = 1.
d(C, X, D) :- atomic(C), !, D = 0.
d(U+V, X, DU+DV) :- d(U, X, DU), d(V, X, DV).
d(U-V, X, DU-DV) :- d(U, X, DU), d(V, X, DV).
d(U*V, X, DU*V+U*DV) :- d(U, X, DU), d(V, X, DV).
d(U**N, X, N*U**N1*DU) :- integer(N), N1 is N-1, d(U, X, DU).
d(-U, X, -DU) :- d(U, X, DU).


Node:Use Of Meta, Next:, Previous:Derivative, Up:Programming Examples

Use of Meta-Logical Predicates

This example illustrates the use of the meta-logical predicates var/1, arg/3, and functor/3 (see Meta Logic). The procedure call variables(Term, L, []) instantiates variable L to a list of all the variable occurrences in the term Term. e.g.

| ?- variables(d(U*V, X, DU*V+U*DV), L, []).

L = [U,V,X,DU,V,U,DV]
variables(X, [X|L0], L) :- var(X), !, L = L0.
variables(T, L0, L) :-
%       nonvar(T),
        functor(T, _, A),
        variables(0, A, T, L0, L).

variables(A, A, _, L0, L) :- !, L = L0.
variables(A0, A, T, L0, L) :-
%       A0<A,
        A1 is A0+1,
        arg(A1, T, X),
        variables(X, L0, L1),
        variables(A1, A, T, L1, L).


Node:Use Of Term Exp, Next:, Previous:Use Of Meta, Up:Programming Examples

Use of Term Expansion

This example illustrates the use of user:term_expansion/[2,4] to augment the built-in predicate expand_term/2 which works as a filter on the input to compile and consult. The code below will allow the declaration :- wait f/3 as an alias for :- block f(-,?,?). Wait declarations were used in previous versions of SICStus Prolog.

Note the multifile declaration, which prevents this user:term_expansion/[2,4] clause from erasing any other clauses for the same predicate that might have been loaded.

:- op(1150, fx, [wait]).

:- multifile user:term_expansion/2.
user:term_expansion((:- wait F/N), (:- block Head)) :-
        functor(Head, F, N),
        wb_args(N, Head).

wb_args(0, _Head).
wb_args(1, Head) :- arg(1, Head, -).
wb_args(N, Head) :-
        N>1,
        arg(N, Head, ?),
        N1 is N-1,
        wb_args(N1, Head).


Node:Interpreter, Next:, Previous:Use Of Term Exp, Up:Programming Examples

Prolog in Prolog

This example shows how simple it is to write a Prolog interpreter in Prolog, and illustrates the use of a variable goal. In this mini-interpreter, goals and clauses are represented as ordinary Prolog data structures (i.e. terms). Terms representing clauses are specified using the predicate my_clause/1, e.g.

my_clause( (grandparent(X, Z) :- parent(X, Y), parent(Y, Z)) ).

A unit clause will be represented by a term such as

my_clause( (parent(john, mary) :- true) ).

The mini-interpreter consists of three clauses:

execute((P,Q)) :- !, execute(P), execute(Q).
execute(P) :- predicate_property(P, built_in), !, P.
execute(P) :- my_clause((P :- Q)), execute(Q).

The second clause enables the mini-interpreter to cope with calls to ordinary Prolog predicates, e.g. built-in predicates. The mini-interpreter needs to be extended to cope with the other control structures, i.e. !, (P;Q), (P->Q), (P->Q;R), (\+ P), and if(P,Q,R).


Node:Translate, Previous:Interpreter, Up:Programming Examples

Translating English Sentences into Logic Formulae

The following example of a definite clause grammar defines in a formal way the traditional mapping of simple English sentences into formulae of classical logic. By way of illustration, if the sentence

Every man that lives loves a woman.

is parsed as a sentence by the call

| ?- phrase(sentence(P), [every,man,that,lives,loves,a,woman]).

then P will get instantiated to

all(X):(man(X)&lives(X) => exists(Y):(woman(Y)&loves(X,Y)))

where :, & and => are infix operators defined by

:- op(900, xfx, =>).
:- op(800, xfy, &).
:- op(550, xfy, :). /* predefined */

The grammar follows:

sentence(P) --> noun_phrase(X, P1, P), verb_phrase(X, P1).

noun_phrase(X, P1, P) -->
        determiner(X, P2, P1, P), noun(X, P3), rel_clause(X, P3, P2).
noun_phrase(X, P, P) --> name(X).

verb_phrase(X, P) --> trans_verb(X, Y, P1), noun_phrase(Y, P1, P).
verb_phrase(X, P) --> intrans_verb(X, P).

rel_clause(X, P1, P1&P2) --> [that], verb_phrase(X, P2).
rel_clause(_, P, P) --> [].

determiner(X, P1, P2, all(X):(P1=>P2)) --> [every].
determiner(X, P1, P2, exists(X):(P1&P2)) --> [a].

noun(X, man(X)) --> [man].
noun(X, woman(X)) --> [woman].

name(john) --> [john].

trans_verb(X, Y, loves(X,Y)) --> [loves].
intrans_verb(X, lives(X)) --> [lives].


Node:The Cross-Referencer, Previous:Programming Examples, Up:Writing Efficient Programs

The Cross-Referencer


Node:Xref Introduction, Next:, Previous:The Cross-Referencer, Up:The Cross-Referencer

Introduction

The main purpose of the cross-referencer, spxref, is to find undefined predicates and unreachable code. To this end, it begins by looking for initializations, hooks and public directives to start tracing the reachable code from. If an entire application is being checked, it also traces from user:runtime_entry/1. If individual module-files are being checked, it also traces from their export lists.

A second function of spxref is to aid in the formation of module statements. spxref can list all of the required module/2 and use_module/2 statements by file.


Node:Xref Basic Use, Next:, Previous:Xref Introduction, Up:The Cross-Referencer

Basic Use

The cross-referencer is run from the shell prompt, specifying the names of the Prolog source files you wish to check. You may omit the .pl suffix if you like.

% spxref [-R] [-v] [-c] [-i ifile] [-w wfile] [-x xfile] [-u ufile] fspec ...

spxref takes a number of options, as follows. File arguments should be given as atoms or as -, denoting the standard output stream.

-R
Check an application, i.e. follow user:runtime_entry/1, as opposed to module declarations.
-c
Generate standard compiler style error messages.
-v
Verbose output. This echoes the names of the files being read.
-i ifile
An initialization file, which is loaded before processing begins.
-w wfile
Warning file. Warnings are written to the standard error stream by default.
-x xfile
Generate a cross-reference file. This is not generated by default.
-m mfile
Generate a file indicating which predicates are imported and which are exported for each file. This is not generated by default.
-u ufile
Generate a file listing all the undefined predicates. This is not generated by default.


Node:Xref Practice and Experience, Previous:Xref Basic Use, Up:The Cross-Referencer

Practice and Experience

Your code will probably rely on operator declarations and possibly term expansion. The cross-referencer handles this in much the same way as fcompile/1: you must supply an initialization file. Contrary to fcompile/1, spxref will execute any operator declaration it encounters.

Supply meta-predicate declarations for your meta-predicates. Otherwise, the cross-referencer will not follow the meta-predicates' arguments. Be sure the cross-referencer encounters the meta-predicate declarations before it encounters calls to the declared predicates.

The cross-referencer traces from initializations, hooks, predicates declared public, and optionally from user:runtime_entry/1 and module declarations. The way it handles meta-predicates requires that your application load its module-files before its non-module-files.

This cross-referencer was written in order to tear out the copious dead code from the application that the author became responsible for. If you are doing such a thing, the cross-referencer is an invaluable tool. Be sure to save the output from the first run that you get from the cross referencer: this is very useful resource to help you find things that you've accidentally ripped out and that you really needed after all.

There are situations where the cross-referencer does not follow certain predicates. This can happen if the predicate name is constructed on the fly, or if it is retrieved from the database. In this case, add public declarations for these. Alternatively, you could create term expansions that are peculiar to the cross-referencer.


Node:The SICStus Tools, Next:, Previous:Writing Efficient Programs, Up:Top

The SICStus Tools

The SICStus tools are the programs that are automatically installed with SICStus Prolog as shell commands. They are all described in detail elsewhere in this manual; this is just a summary.

sicstus
The SICStus development system. See Start.
splfr
The foreign resource linker. See The Foreign Resource Linker.
spld
The application builder. See The Application Builder.
spdet
The determinacy checker. See The Determinacy Checker.
spxref
The cross-referencer. See The Cross-Referencer.


Node:The Prolog Library, Next:, Previous:The SICStus Tools, Up:Top

The Prolog Library

The Prolog library comprises a number of packages which are thought to be useful in a number of applications. Note that the predicates in the Prolog library are not built-in predicates. One has to explicitly load each package to get access to its predicates. The following packages are provided:

arrays
provides an implementation of extendible arrays with logarithmic access time.
assoc
uses AVL trees to implement "association lists", i.e. extendible finite mappings from terms to terms.
atts
provides a means of associating with variables arbitrary attributes, i.e. named properties that can be used as storage locations as well as hooks into Prolog's unification.
heaps
implements binary heaps, the main application of which are priority queues.
lists
provides basic operations on lists.
terms
provides a number of operations on terms.
ordsets
defines operations on sets represented as lists with the elements ordered in Prolog standard order.
queues
defines operations on queues (FIFO stores of information).
random
provides a random number generator.
system
provides access to operating system services.
trees
uses binary trees to represent non-extendible arrays with logarithmic access time. The functionality is very similar to that of library(arrays), but library(trees) is slightly more efficient if the array does not need to be extendible.
ugraphs
provides an implementation of directed and undirected graphs with unlabeled edges.
wgraphs
provides an implementation of directed and undirected graphs where each edge has an integral weight.
sockets
provides an interface to system calls for manipulating sockets.
linda/client
linda/server
provides an implementation of the Linda concept for process communication.
bdb
provides an interface to Berkeley DB, for storage and retrieval of terms on disk files with user-defined multiple indexing.
clpb
provides constraint solving over Booleans.
clpq
clpr
provides constraint solving over Q (Rationals) or R (Reals).
clpfd
provides constraint solving over Finite (Integer) Domains
chr
provides Constraint Handling Rules
fdbg
provides a debugger for finite domain constraint programs
objects
provides the combination of the logic programming and the object-oriented programming paradigms.
tcltk
An interface to the Tcl/Tk language and toolkit.
vbsp
An interface for calling Prolog from Visual Basic.
gauge
is a profiling tool for Prolog programs with a graphical interface based on tcltk.
charsio
defines I/O predicates that read from, or write to, a list of character codes.
jasper
An interface to the Java language.
COM Client
An interface to Microsoft COM automaton objects.
flinkage
is a tool for generating glue code for the Foreign Language Interface when building statically linked runtime systems or development systems. No longer supported but provided for porting really old code.
timeout
provides a way of running goals with an execution time limit.
wcx_example
provides a sample implementation of a Wide Character Extension (WCX) box.

To load a library package Package, you will normally enter a query

| ?- use_module(library(Package)).

A library package normally consists of one or more hidden modules.

An alternative way of loading from the library is using the built-in predicate require/1 (see Read In). The index file INDEX.pl needed by require/1 can be created by the make_index program. This program is loaded as:

| ?- use_module(library(mkindex)).
make_index:make_library_index(+LibraryDirectory)

Creates a file INDEX.pl in LibraryDirectory. All *.pl files in the directory and all its subdirectories are scanned for module/2 declarations. From these declarations, the exported predicates are entered into the index.


Node:Arrays, Next:, Previous:The Prolog Library, Up:Top

Array Operations

This package provides an implementation of extendible arrays with logarithmic access time.

Beware: the atom $ is used to indicate an unset element, and the functor $ /4 is used to indicate a subtree. In general, array elements whose principal function symbol is $ will not work.

To load the package, enter the query

| ?- use_module(library(arrays)).
new_array(-Array)

Binds Array to a new empty array. Example:

| ?- new_array(A).

A = array($($,$,$,$),2) ?

yes

is_array(+Array)

Is true when Array actually is an array.

aref(+Index, +Array, ?Element)

Element is the element at position Index in Array. It fails if Array[Index] is undefined.

arefa(+Index, +Array, ?Element)

Is like aref/3 except that Element is a new array if Array[Index] is undefined. Example:

| ?- arefa(3, array($($,$,$,$),2), E).

E = array($($,$,$,$),2) ?

yes

arefl(+Index, +Array, ?Element)

Is as aref/3 except that Element is [] for undefined cells. Example:

| ?- arefl(3, array($($,$,$,$),2), E).

E = [] ?

yes

array_to_list(+Array, -List)

List is a list with the pairs Index-Element of all the elements of Array. Example:

| ?- array_to_list(array($(a,b,c,d),2), List).

List = [0-a,1-b,2-c,3-d] ?

yes

aset(+Index, +Array, +Element, -NewArray)

NewArray is the result of setting Array[Index] to Element. Example:

| ?- aset(3,array($($,$,$,$),2), a, Newarr).

Newarr = array($($,$,$,a),2) ?

yes


Node:Assoc, Next:, Previous:Arrays, Up:Top

Association Lists

In this package, finite mappings ("association lists") are represented by AVL trees, i.e. they are subject to the Adelson-Velskii-Landis balance criterion:

A tree is balanced iff for every node the heights of its two subtrees differ by at most 1.

The empty tree is represented as t. A tree with key K, value V, and left and right subtrees L and R is represented as t(K,V,|R|-|L|,L,R), where |T| denotes the height of T.

The advantage of this representation is that lookup, insertion and deletion all become--in the worst case--O(log n) operations.

The algorithms are from [Wirth 76], section 4.4.6-4.4.8.

To load the package, enter the query

| ?- use_module(library(assoc)).
empty_assoc(?Assoc)

Assoc is an empty AVL tree.

assoc_to_list(+Assoc, ?List)

List is a list of Key-Value pairs in ascending order with no duplicate Keys specifying the same finite function as the association tree Assoc. Use this to convert an association tree to a list.

is_assoc(+Assoc)

Assoc is a (proper) AVL tree. It checks both that the keys are in ascending order and that Assoc is properly balanced.

min_assoc(+Assoc, ?Key, ?Val)

Key is the smallest key in Assoc and Val is its value.

max_assoc(+Assoc, ?Key, ?Val)

Key is the greatest key in Assoc and Val is its value.

gen_assoc(?Key, +Assoc, ?Value)

Key is associated with Value in the association tree Assoc. Can be used to enumerate all Values by ascending Keys.

get_assoc(+Key, +Assoc, ?Value)

Key is identical (==) to one of the keys in the association tree Assoc, and Value unifies with the associated value.

get_assoc(+Key, +OldAssoc, ?OldValue, ?NewAssoc, ?NewValue)

OldAssoc and NewAssoc are association trees of the same shape having the same elements except that the value for Key in OldAssoc is OldValue and the value for Key in NewAssoc is NewValue.

get_next_assoc(+Key, +Assoc, ?Knext, ?Vnext)

Knext and Vnext is the next key and associated value after Key in Assoc.

get_prev_assoc(+Key, +Assoc, ?Kprev, ?Vprev)

Kprev and Vprev is the previous key and associated value after Key in Assoc.

list_to_assoc(+List, ?Assoc)

List is a proper list of Key-Value pairs (in any order) and Assoc is an association tree specifying the same finite function from Keys to Values.

ord_list_to_assoc(+List, ?Assoc)

List is a proper list of Key-Value pairs (keysorted) and Assoc is an association tree specifying the same finite function from Keys to Values.

map_assoc(:Pred, ?Assoc)

Assoc is an association tree, and for each Key, if Key is associated with Value in Assoc, Pred(Value) is true.

map_assoc(:Pred, ?OldAssoc, ?NewAssoc)

OldAssoc and NewAssoc are association trees of the same shape, and for each Key, if Key is associated with Old in OldAssoc and with New in NewAssoc, Pred(Old,New) is true.

put_assoc(+Key, +OldAssoc, +Val, ?NewAssoc)

OldAssoc and NewAssoc define the same finite function, except that NewAssoc associates Val with Key. OldAssoc need not have associated any value at all with Key.

del_assoc(+Key, +OldAssoc, ?Val, ?NewAssoc)

OldAssoc and NewAssoc define the same finite function except that OldAssoc associates Key with Val and NewAssoc doesn't associate Key with any value.

del_min_assoc(+OldAssoc, ?Key, ?Val, ?NewAssoc)

OldAssoc and NewAssoc define the same finite function except that OldAssoc associates Key with Val and NewAssoc doesn't associate Key with any value and Key precedes all other keys in OldAssoc.

del_max_assoc(+OldAssoc, ?Key, ?Val, -NewAssoc)

OldAssoc and NewAssoc define the same finite function except that OldAssoc associates Key with Val and NewAssoc doesn't associate Key with any value and Key is preceded by all other keys in OldAssoc.


Node:Attributes, Next:, Previous:Assoc, Up:Top

Attributed Variables

This package implements attributed variables. It provides a means of associating with variables arbitrary attributes, i.e. named properties that can be used as storage locations as well as to extend the default unification algorithm when such variables are unified with other terms or with each other. This facility was primarily designed as a clean interface between Prolog and constraint solvers, but has a number of other uses as well. The basic idea is due to Christian Holzbaur and he was actively involved in the final design. For background material, see the dissertation [Holzbaur 90].

To load the package, enter the query

| ?- use_module(library(atts)).

The package provides a means to declare and access named attributes of variables. The attributes are compound terms whose arguments are the actual attribute values. The attribute names are private to the module in which they are defined. They are defined with a declaration

:- attribute AttributeSpec, ..., AttributeSpec.

where each AttributeSpec has the form (Name/Arity). There must be at most one such declaration in a module Module.

Having declared some attribute names, these attributes can now be added, updated and deleted from unbound variables. For each declared attribute name, any variable can have at most one such attribute (initially it has none).

The declaration causes the following two access predicates to become defined by means of the user:goal_expansion/3 mechanism. They take a variable and an AccessSpec as arguments where an AccessSpec is either +(Attribute), -(Attribute), or a list of such. The + prefix may be dropped for convenience. The meaning of the +/- prefix is documented below:


Module:get_atts(-Var, ?AccessSpec)
Gets the attributes of Var according to AccessSpec. If AccessSpec is unbound, it will be bound to a list of all set attributes of Var. Non-variable terms cause a type error to be raised. The prefixes in the AccessSpec have the following meaning:
+(Attribute)
The corresponding actual attribute must be present and is unified with Attribute.
-(Attribute)
The corresponding actual attribute must be absent. The arguments of Attribute are ignored, only the name and arity are relevant.

Module:put_atts(-Var, +AccessSpec)
Sets the attributes of Var according to AccessSpec. Non-variable terms cause a type error to be raised. The effects of put_atts/2 are undone on backtracking.
+(Attribute)
The corresponding actual attribute is set to Attribute. If the actual attribute was already present, it is simply replaced.
-(Attribute)
The corresponding actual attribute is removed. If the actual attribute was already absent, nothing happens.

A module that contains an attribute declaration has an opportunity to extend the default unification algorithm by defining the following predicate:


Module:verify_attributes(-Var, +Value, -Goals) [Hook]
This predicate is called whenever a variable Var that might have attributes in Module is about to be bound to Value (it might have none). The unification resumes after the call to verify_attributes/3. Value is a non-variable term, or another attributed variable. Var might have no attributes present in Module; the unification extension mechanism is not sophisticated enough to filter out exactly the variables that are relevant for Module.

verify_attributes/3 is called before Var has actually been bound to Value. If it fails, the unification is deemed to have failed. It may succeed nondeterministically, in which case the unification might backtrack to give another answer. It is expected to return, in Goals, a list of goals to be called after Var has been bound to Value.

verify_attributes/3 may invoke arbitrary Prolog goals, but Var should not be bound by it. Binding Var will result in undefined behavior.

If Value is a non-variable term, verify_attributes/3 will typically inspect the attributes of Var and check that they are compatible with Value and fail otherwise. If Value is another attributed variable, verify_attributes/3 will typically copy the attributes of Var over to Value, or merge them with Value's, in preparation for Var to be bound to Value. In either case, verify_attributes/3 may determine Var's current attributes by calling get_atts(Var,List) with an unbound List.

An important use for attributed variables is in implementing coroutining facilities as an alternative or complement to the built-in coroutining mechanisms. In this context it might be useful to be able to interpret some of the attributes of a variable as a goal that is blocked on that variable. Certain built-in predicates (frozen/2, call_residue/2) and the Prolog top-level need to access blocked goals, and so need a means of getting the goal interpretation of attributed variables by calling:


Module:attribute_goal(-Var, -Goal) [Hook]
This predicate is called in each module that contains an attribute declaration, when an interpretation of the attributes as a goal is needed, for example in frozen/2 and call_residue/2. It should unify Goal with the interpretation, or merely fail if no such interpretation is available.

An important use for attributed variables is to provide an interface to constraint solvers. An important function for a constraint solver in the constraint logic programming paradigm is to be able to perform projection of the residual constraints onto the variables that occurred in the top-level query. A module that contains an attribute declaration has an opportunity to perform such projection of its residual constraints by defining the following predicate:


Module:project_attributes(+QueryVars, +AttrVars) [Hook]
This predicate is called by the Prolog top level and by the built-in predicate call_residue/2 in each module that contains an attribute declaration. QueryVars is the list of variables occurring in the query, or in terms bound to such variables, and AttrVars is a list of possibly attributed variables created during the execution of the query. The two lists of variables may or may not be disjoint.

If the attributes on AttrVars can be interpreted as constraints, this predicate will typically "project" those constraints onto the relevant QueryVars. Ideally, the residual constraints will be expressed entirely in terms of the QueryVars, treating all other variables as existentially quantified. Operationally, project_attributes/2 must remove all attributes from AttrVars, and add transformed attributes representing the projected constraints to some of the QueryVars.

Projection has the following effect on the Prolog top-level. When the top-level query has succeeded, project_attributes/2 is called first. The top-level then prints the answer substition and residual constraints. While doing so, it searches for attributed variables created during the execution of the query. For each such variable, it calls attribute_goal/2 to get a printable representation of the constraint encoded by the attribute. Thus, project_attributes/2 is a mechanism for controlling how the residual constraints should be displayed at top-level.

Similarly during the execution of call_residue(Goal,Residue), when Goal has succeeded, project_attributes/2 is called. After that, all attributed variables created during the execution of Goal are located. For each such variable, attribute_goal/2 produces a term representing the constraint encoded by the attribute, and Residue is unified with the list of all such terms.

The exact definition of project_attributes/2 is constraint system dependent, but see Projection for details about projection in clp(Q,R).

In the following example we sketch the implementation of a finite domain "solver". Note that an industrial strength solver would have to provide a wider range of functionality and that it quite likely would utilize a more efficient representation for the domains proper. The module exports a single predicate domain(-Var,?Domain) which associates Domain (a list of terms) with Var. A variable can be queried for its domain by leaving Domain unbound.

We do not present here a definition for project_attributes/2. Projecting finite domain constraints happens to be difficult.

:- module(domain, [domain/2]).

:- use_module(library(atts)).
:- use_module(library(ordsets), [
        ord_intersection/3,
        ord_intersect/2,
        list_to_ord_set/2
   ]).

:- attribute dom/1.

verify_attributes(Var, Other, Goals) :-
        get_atts(Var, dom(Da)), !,          % are we involved?
        (   var(Other) ->                   % must be attributed then
            (   get_atts(Other, dom(Db)) -> %   has a domain?
                ord_intersection(Da, Db, Dc),
                Dc = [El|Els],              % at least one element
                (   Els = [] ->             % exactly one element
                    Goals = [Other=El]      % implied binding
                ;   Goals = [],
                    put_atts(Other, dom(Dc))% rescue intersection
                )
            ;   Goals = [],
                put_atts(Other, dom(Da))    % rescue the domain
            )
        ;   Goals = [],
            ord_intersect([Other], Da)      % value in domain?
        ).
verify_attributes(_, _, []).                % unification triggered
                                            % because of attributes
                                            % in other modules

attribute_goal(Var, domain(Var,Dom)) :-     % interpretation as goal
        get_atts(Var, dom(Dom)).

domain(X, Dom) :-
        var(Dom), !,
        get_atts(X, dom(Dom)).
domain(X, List) :-
        list_to_ord_set(List, Set),
        Set = [El|Els],                     % at least one element
        (   Els = [] ->                     % exactly one element
            X = El                          % implied binding
        ;   put_atts(Fresh, dom(Set)),
            X = Fresh                       % may call
                                            % verify_attributes/3
        ).

Note that the "implied binding" Other=El was deferred until after the completion of verify_attribute/3. Otherwise, there might be a danger of recursively invoke verify_attribute/3, which might bind Var, which is not allowed inside the scope of verify_attribute/3. Deferring unifications into the third argument of verify_attribute/3 effectively serializes th calls to verify_attribute/3.

Assuming that the code resides in the file domain.pl, we can use it via:

| ?- use_module(domain).

Let's test it:

| ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]).

domain(X,[1,5,6,7]),
domain(Y,[3,4,5,6]),
domain(Z,[1,6,7,8]) ?

yes
| ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]),
     X=Y.

Y = X,
domain(X,[5,6]),
domain(Z,[1,6,7,8]) ?

yes
| ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]),
     X=Y, Y=Z.

X = 6,
Y = 6,
Z = 6

To demonstrate the use of the Goals argument of verify_attributes/3, we give an implementation of freeze/2. We have to name it myfreeze/2 in order to avoid a name clash with the built-in predicate of the same name.

:- module(myfreeze, [myfreeze/2]).

:- use_module(library(atts)).

:- attribute frozen/1.

verify_attributes(Var, Other, Goals) :-
        get_atts(Var, frozen(Fa)), !,       % are we involved?
        (   var(Other) ->                   % must be attributed then
            (   get_atts(Other, frozen(Fb)) % has a pending goal?
            ->  put_atts(Other, frozen((Fa,Fb))) % rescue conjunction
            ;   put_atts(Other, frozen(Fa)) % rescue the pending goal
            ),
            Goals = []
        ;   Goals = [Fa]
        ).
verify_attributes(_, _, []).

attribute_goal(Var, Goal) :-                % interpretation as goal
        get_atts(Var, frozen(Goal)).

myfreeze(X, Goal) :-
        put_atts(Fresh, frozen(Goal)),
        Fresh = X.

Assuming that this code lives in file myfreeze.pl, we would use it via:

| ?- use_module(myfreeze).
| ?- myfreeze(X,print(bound(x,X))), X=2.

bound(x,2)                      % side effect
X = 2                           % bindings

The two solvers even work together:

| ?- myfreeze(X,print(bound(x,X))), domain(X,[1,2,3]),
     domain(Y,[2,10]), X=Y.

bound(x,2)                      % side effect
X = 2,                          % bindings
Y = 2

The two example solvers interact via bindings to shared attributed variables only. More complicated interactions are likely to be found in more sophisticated solvers. The corresponding verify_attributes/3 predicates would typically refer to the attributes from other known solvers/modules via the module prefix in Module:get_atts/2.


Node:Heaps, Next:, Previous:Attributes, Up:Top

Heap Operations

A binary heap is a tree with keys and associated values that satisfies the heap condition: the key of every node is greater than or equal to the key of its parent, if it has one. The main application of binary heaps are priority queues. To load the package, enter the query

| ?- use_module(library(heaps)).

add_to_heap(+OldHeap, +Key, +Datum, ?NewHeap)

Inserts the new Key-Datum pair into the current heap OldHeap producing the new heap NewHeap. The insertion is not stable, that is, if you insert several pairs with the same Key it is not defined which of them will come out first, and it is possible for any of them to come out first depending on the history of the heap. Example:

| ?- add_to_heap(t(0,[],t),3,678,N).

N = t(1,[],t(3,678,t,t)) ?

yes

get_from_heap(+OldHeap, ?Key, ?Datum, ?NewHeap)

Returns the Key-Datum pair in OldHeap with the smallest Key, and also a NewHeap which is the OldHeap with that pair deleted. Example:

get_from_heap(t(1,[],t(1,543,t,t)),K,D,N).

D = 543,
K = 1,
N = t(0,[1],t) ?

yes

empty_heap(?Heap)

is true when Heap is the empty heap.

heap_size(+Heap, ?Size)

Size is the number of elements in the heap Heap.

heap_to_list(+Heap, -List)

Returns the current set of Key-Datum pairs in the Heap as a keysorted List.

is_heap(+Heap)

is true when Heap is a valid heap.

list_to_heap(+List, -Heap)

Takes a list List of Key-Datum pairs and forms them into a heap Heap. Example:

| ?- list_to_heap([1-34,2-345,5-678],H).

H = t(3,[],t(1,34,t(2,345,t,t),t(5,678,t,t))) ?

yes

min_of_heap(+Heap, ?Key, ?Datum)

Returns the Key-Datum pair at the top of the heap Heap without removing it. Fails if the heap is empty.

min_of_heap(+Heap, ?Key1, ?Datum1, ?Key2, ?Datum2)

Returns the smallest (Key1-Datum1) and second smallest (Key2-Datum2) pairs in the Heap, without deleting them. It fails if the heap does not have at least two elements.

delete_from_heap(+OldHeap, +Key, ?Datum, ?NewHeap)

deletes a single Key-Datum pair in OldHeap producing NewHeap. This is useful if you want to e.g. change the priority of Datum. Beware: this operation needs to search the whole heap in the worst case.


Node:Lists, Next:, Previous:Heaps, Up:Top

List Operations

This package defines operations on lists. Lists are a very basic data structure, but nevertheless certain very frequent operations are provided in this package.

To load the package, enter the query

| ?- use_module(library(lists)).
append(?Prefix, ?Suffix, ?Combined)

Combined is the combined list of the elements in Prefix followed by the elements in Suffix. It can be used to form Combined or it can be used to find Prefix and/or Suffix from a given Combined.

delete(+List, +Element, ?Residue)

Residue is the result of removing all identical occurrences of Element in List.

is_list(+List)

List is a proper list.

last(?List, ?Last)

Last is the last element in List. Example:

| ?- last([x,y,z], Z).

Z = z ?

yes

max_list(+ListOfNumbers, ?Max)

Max is the largest of the elements in ListOfNumbers.

member(?Element, ?List)

Element is a member of List. It may be used to test for membership in a list, but it can also be used to enumerate all the elements in List. Example:

| ?- member(X, [a,b,c]).

X = a ? ;

X = b ? ;

X = c ?

yes

memberchk(+Element, +List)

Element is a member of List, but memberchk/2 only succeeds once and can therefore not be used to enumerate the elements in List. Example:

| ?- memberchk(X, [a,b,c]).

X = a ? ;

no

min_list(+ListOfNumbers, ?Min)

Min is the smallest of the numbers in the list ListOfNumbers.

nextto(?X, ?Y, ?List)

X and Y appears side-by-side in List. Example:

| ?- nextto(X, Y, [1,2,3]).

X = 1,
Y = 2 ? ;

X = 2,
Y = 3 ? ;

no

no_doubles(?List)

List contains no duplicated elements. This is true when dif(X, Y) holds for all pairs of members X and Y of the list.

non_member(?Element, ?List)

Element does not occur in List. This is true when dif(Element, Y) holds for all members Y of the list.

nth(?N, ?List, ?Element)

Element is the Nth element of List. The first element is number 1. Example:

| ?- nth(N, [a,b,c,d,e,f,g,h,i], f).

N = 6 ?

yes

nth(?N, ?List, ?Element, ?Rest)

Element is in position N in the List and Rest is all elements in List except Element.

nth0(?N, ?List, ?Element)

Element is the Nth element of List, counting the first element as 0.

nth0(?N, ?List, ?Element, ?Rest)

Element is the Nth element of List, counting the first element as 0. Rest is all the other elements in List. Example:

| ?- nth0(N, [a,b,c,d,e,f,g,h,i,j], f, R).

N = 5,
R = [a,b,c,d,e,g,h,i,j] ?

yes

permutation(?List, ?Perm)

Perm is a permutation of List.

prefix(?Prefix, ?List)

Prefix is a prefix of List. Example:

| ?- prefix([1,2,3], [1,2,3,4,5,6]).

yes

remove_duplicates(+List, ?Pruned)

Pruned is the result of removing all identical duplicate elements in List. Example:

| ?- remove_duplicates([1,2,3,2,3,1], P).

P = [1,2,3] ? ;

no

reverse(?List, ?Reversed)

Reversed has the same elements as List but in a reversed order.

same_length(?List1, ?List2)

List1 and List2 have the same number of elements.

same_length(?List1, ?List2, ?Length)

List1 and List2 have the same number of elements and that number is Length. Example:

| ?- same_length([1,2,3], [9,8,7], N).

N = 3 ? ;

no

select(?Element, ?List, ?List2)

The result of removing an occurrence of Element in List is List2.

sublist(?Sub, ?List)

Sub contains some of the elements of List, in the same order.

substitute(+X, +Xlist, +Y, ?Ylist)

Xlist and Ylist are equal except for replacing identical occurrences of X by Y. Example:

| ?- substitute(1, [1,2,3,4], 5, X).

X = [5,2,3,4] ?

yes

sum_list(+ListOfNumbers, ?Sum)

Sum is the result of adding the ListOfNumbers together.

suffix(?Suffix, ?List)

Suffix is a suffix of List.


Node:Term Utilities, Next:, Previous:Lists, Up:Top

Term Utilities

This package defines operations on terms for subsumption checking, "anti-unification", testing acyclicity, and getting the variables. NOTE: anti-unification is a purely syntactic operation; any attributes attached to the variables are ignored.

To load the package, enter the query

| ?- use_module(library(terms)).
subsumes_chk(?General, ?Specific)

Specific is an instance of General, i.e. if there is a substitution that leaves Specific unchanged and makes General identical to Specific. It doesn't bind any variables.

subsumes_chk(f(X), f(a)).

true

| ?- subsumes_chk(f(a), f(X)).

no

| ?- subsumes_chk(A-A, B-C).

no

| ?- subsumes_chk(A-B, C-C).

true

subsumes(?General, ?Specific)

Specific is an instance of General. It will bind variables in General (but not those in Specific) so that General becomes identical to Specific.

variant(?Term, ?Variant)

Term and Variant are identical modulo renaming of variables, provided Term and Variant have no variables in common.

term_subsumer(?Term1, ?Term2, ?General)

General is the most specific term that generalizes Term1 and Term2. This process is sometimes called anti-unification, as it is the dual of unification.

| ?- term_subsumer(f(g(1,h(_))), f(g(_,h(1))), T).

T = f(g(_B,h(_A)))

| ?- term_subsumer(f(1+2,2+1), f(3+4,4+3), T).

T = f(_A+_B,_B+_A)


term_hash(?Term, ?Hash)
term_hash(?Term, +Depth, +Range, ?Hash)

If Term is instantiated up to the given Depth, an integer hash value in the range [0,Range) as a function of Term is unified with Hash. Otherwise, the goal just succeeds, leaving Hash uninstantiated.

If Term contains floats or integers outside the small integer range, the hash value will be platform dependent. Otherwise, the hash value will be identical across runs and platforms.

The depth of a term is defined as follows: the (principal functor of) the term itself has depth 1, and an argument of a term with depth i has depth i+1.

Depth should be an integer >= -1. If Depth = -1 (the default), Term must be ground, and all subterms of Term are relevant in computing Hash. Otherwise, only the subterms up to depth Depth of Term are used in the computation.

Range should be an integer >= 1. The default will give hash values in a range appropriate for all platforms.

| ?- term_hash([a,b,_], 3, 4, H).

H = 2

| ?- term_hash([a,b,_], 4, 4, H).

true

| ?- term_hash(f(a,f(b,f(_,[]))), 2, 4, H).

H = 2

term_hash/[2,4] is provided primarily as a tool for the construction of sophisticated Prolog clause access schemes. Its intended use is to generate hash values for terms that will be used with first argument clause indexing, yielding compact and efficient multi-argument or deep argument indexing.

term_variables(?Term, ?Variables)

Variables is the set of variables occurring in Term.

term_variables_bag(?Term, ?Variables)

Variables is the list of variables occurring in Term, in first occurrence order. Each variable occurs once only in the list.

acyclic_term(?X)

True if X is finite (acyclic). Runs in linear time.

cyclic_term(?X)

True if X is infinite (cyclic). Runs in linear time.


Node:Ordsets, Next:, Previous:Term Utilities, Up:Top

Ordered Set Operations

This package defines operations on ordered sets. Ordered sets are sets represented as lists with the elements ordered in a standard order. The ordering is defined by the @< family of term comparison predicates and it is the ordering produced by the built-in predicate sort/2 (see Term Compare).

To load the package, enter the query

| ?- use_module(library(ordsets)).
is_ordset(+Set)

Set is an ordered set.

list_to_ord_set(+List, ?Set)

Set is the ordered representation of the set denoted by the unordered representation List. Example:

| ?- list_to_ord_set([p,r,o,l,o,g], P).

P = [g,l,o,p,r] ?

yes


ord_add_element(+Set1, +Element ?Set2)

Set2 is Set1 with Element inserted in it, preserving the order. Example:

| ?- ord_add_element([a,c,d,e,f], b, N).

N = [a,b,c,d,e,f] ?

yes

ord_del_element(+Set1, +Element, ?Set2)

Set2 is like Set1 but with Element removed.

ord_disjoint(+Set1, +Set2)

The two ordered sets have no elements in common.

ord_intersect(+Set1, +Set2)

The two ordered sets have at least one element in common.

ord_intersection(+Set1, +Set2, ?Intersect)

Intersect is the ordered set representation of the intersection between Set1 and Set2.

ord_intersection(+Set1, +Set2, ?Intersect, ?Diff)

Intersect is the intersection between Set1 and Set2, and Diff is the difference between Set2 and Set1.

ord_intersection(+Sets, ?Intersection)

Intersection is the ordered set representation of the intersection of all the sets in Sets. Example:

| ?- ord_intersection([[1,2,3],[2,3,4],[3,4,5]], I).

I = [3] ?

yes


ord_member(+Elt, +Set)

is true when Elt is a member of Set.

ord_seteq(+Set1, +Set2)

Is true when the two arguments represent the same set. Since they are assumed to be ordered representations, they must be identical.

ord_setproduct(+Set1, +Set2, ?SetProduct)

SetProduct is the Cartesian Product of the two Sets. The product is represented as pairs: Elem1-Elem2 where Elem1 is an element from Set1 and Elem2 is an element from Set2. Example

| ?- ord_setproduct([1,2,3], [4,5,6], P).

P = [1-4,1-5,1-6,2-4,2-5,2-6,3-4,3-5,3-6] ?

yes

ord_subset(+Set1, +Set2)

Every element of the ordered set Set1 appears in the ordered set Set2.

ord_subtract(+Set1, +Set2, ?Difference)

Difference contains all and only the elements of Set1 which are not also in Set2. Example:

| ?- ord_subtract([1,2,3,4], [3,4,5,6], S).

S = [1,2] ?

yes

ord_symdiff(+Set1, +Set2, ?Difference)

Difference is the symmetric difference of Set1 and Set2. Example:

| ?- ord_symdiff([1,2,3,4], [3,4,5,6], D).

D = [1,2,5,6] ?

yes

ord_union(+Set1, +Set2, ?Union)

Union is the union of Set1 and Set2.

ord_union(+Set1, +Set2, ?Union, ?New)

Union is the union of Set1 and Set2, and New is the difference between Set2 and Set1. This is useful if you are accumulating members of a set and you want to process new elements as they are added to the set.

ord_union(+Sets, ?Union)

Union is the union of all the sets in Sets. Example:

| ?- ord_union([[1,2,3],[2,3,4],[3,4,5]], U).

U = [1,2,3,4,5] ?

yes


Node:Queues, Next:, Previous:Ordsets, Up:Top

Queue Operations

A queue is a first-in, first-out store of information. This implementation of queues uses difference-lists, the head of the difference-list represents the beginning of the queue and the tail represents the end of the queue. The members of the difference-list are the elements in the queue. The first argument in the queue-representation is the number of elements in the queue in unary representation.

Thus, a queue with n elements is represented as follows:

q(s(...s(0)...), [X1,...,Xn,Y1,...,Ym], [Y1,...,Ym])

where n is the length of the queue and X1...Xn are the elements of the queue.

To load the package, enter the query

| ?- use_module(library(queues)).
empty_queue(?Queue)

Is true if Queue has no elements.

is_queue(+Queue)

is true when Queue is a valid queue.

queue(?X, ?Queue)

Is true if Queue has one element and that is X.

queue_head(?Head, ?Queue1, ?Queue2)

Queue1 and Queue2 are the same queues except that Queue2 has Head inserted in the front. It can be used to enqueue the first element in Queue2. Example:

| ?- queue_head(Head, Nq,
                q(s(s(s(s(0)))),[1,2,3,4|R],R)).

Head = 1,
Nq = q(s(s(s(0))),[2,3,4|_193],_193),
R = _193 ?

yes

queue_head_list(+HeadList, ?Queue1, ?Queue2)

Queue1 and Queue2 have the same elements except that Queue2 has HeadList inserted in the front.

queue_last(?Last, ?Queue1, ?Queue2)

Queue2 is like Queue1 but have Last as the last element in the queue.

queue_last_list(+LastList, ?Queue1, ?Queue2)

Queue1 and Queue2 are the same queues except that Queue2 has the list of elements LastList last in the queue. Example:

| ?- queue_last_list([5,6], q(s(s(0)))), [1,2|R], R), NQ).

NQ = q(s(s(s(s(0)))))),[1,2,5,6|_360],_360),
R = [5,6|_360] ?

yes

list_queue(+List, ?Queue)

Queue is the queue representation of the elements in List. Example:

| ?- list_queue([1,2,3,4], Q).

Q = q(s(s(s(s(0)))),[1,2,3,4|_138],_138) ?

yes
| ?-

queue_length(+Queue, ?Length)

Length is the number of elements in Queue. Example:

| ?- queue_length(q(s(s(s(s(s(0))))),[a,b,c,d,e|R],R), L).

L = 5,
R = _155 ?

yes


Node:Random, Next:, Previous:Queues, Up:Top

Random Number Generator

This package provides a random number generator. To load the package, enter the query

| ?- use_module(library(random)).

This library fully supports multiple SICStus run-times in a process.

random(-Number)

Binds Number to a random float in the interval [0.0, 1.0). Note that 1.0 will never be generated.

random(+Lower, +Upper, -Number)

Binds Number to a random integer in the interval [Lower,Upper) if Lower and Upper are integers. Otherwise, Number is bound to a random float between Lower and Upper. Upper will never be generated.

randseq(+K, +N, -RandomSeq)

Generates a unordered set of K unique integers, chosen randomly in the range 1..N. RandomSeq is not returned in any particular order.

randset(+K, +N, -RandomSet)

Generates an ordered set of K unique integers, chosen randomly in the range 1..N. The set is returned in standard order.

getrand(?State)

Tries to unify State with the term rand(X,Y,Z) where X, Y, and Z are integers describing the state of the random generator.

setrand(rand(+X,+Y,+Z))

Sets the state of the random generator. X, Y, and Z must be integers in the ranges [1,30269), [1,30307), and [1,30323), respectively.


Node:System Utilities, Next:, Previous:Random, Up:Top

Operating System Utilities

This package contains utilities for invoking services from the operating system. To load the package, enter the query

| ?- use_module(library(system)).

Certain predicates described below take names of files or directories as arguments. These must be given as atoms, and the predicates below will not call absolute_file_name/3 on them.

Some predicates are described as invoking the default shell. Specifically this means invoking /bin/sh on UNIX platforms. On MSDOS, Windows and OS/2, the command interpreter given by the environment variable COMSPEC is invoked.

This library fully supports multiple SICStus run-times in a process.


now(-When)
Unifies the current date and time as a UNIX timestamp with When.
datime(-Datime)

Unifies Datime with the current date and time as a datime/6 record of the form datime(Year,Month,Day,Hour,Min,Sec). All fields are integers.

datime(+When,-Datime)

Given a UNIX timestamp When, unifies Datime with the corresponding date and time as a datime/6 record.

delete_file(+FileName,+Options)

FileName is the name of an existing file or directory. Options is a list of options. Possible options are directory, recursive or ignore. If FileName is not a directory it is deleted; otherwise, if the option directory is specified but not recursive, the directory will be deleted if it is empty. If recursive is specified and FileName is a directory, the directory and all its subdirectories and files will be deleted. If the operation fails, an exception is raised unless the ignore option is specified.

delete_file(+FileName)

Equivalent to delete_file(FileName,[recursive]).

directory_files(+Directory,-FileList)

FileList is the list of entries (files, directories, etc.) in Directory.

make_directory(+DirectoryName)

Makes a new directory.

environ(?Var, ?Value)

Var is the name of an environment variable, and Value is its value. Both are atoms. Can be used to enumerate all current environment variables.

exec(+Command, [+Stdin,+Stdout,+Stderr], -Pid)

Passes Command to a new default shell process for execution. The standard I/O streams of the new process are connected according to what is specified by the terms +Stdin, +Stdout, and +Stderr respectively. Possible values are:

null
Connected to /dev/null or equivalent.
std
The standard stream is shared with the calling process. Note that the standard stream may not be referring to a console if the calling process is windowed. To portably print the output from the subprocess on the Prolog console, pipe/1 must be used and the program must explicitly read the pipe and write to the console. Similarly for the input to the subprocess.
pipe(-Stream)
A pipe is created which connects the Prolog stream Stream to the standard stream of the new process. It must be closed using close/1; it is not closed automatically when the process dies.

Pid is the process identifier of the new process.

On UNIX, the subprocess will be detached provided none of its standard streams is specified as std. This means it will not receive an interruption signal as a result of ^C being typed.

file_exists(+FileName)
FileName is the name of an existing file or directory.
file_exists(+FileName, +Permissions)
FileName is the name of an existing file or directory which can be accessed according to Permissions. Permissions is an atom, an integer (see access(2)), or a list of atoms and/or integers. The atoms must be drawn from the list [read,write,search,exists].
file_property(+FileName, ?Property)
FileName has the property Property. The possible properties are:
type(Type)
Type is one of regular, directory, fifo, symlink, socket or unknown.
size(Size)
Size is the size of FileName.
mod_time(ModTime)
ModTime is the time of the last modification of FileName, as a UNIX timestamp. library(system) (see System Utilities) provides operations on such timestamps.

If Property is uninstantiated, the predicate will enumerate the properties on backtracking.

host_id(-HID)
HID is the unique identifier, represented by an atom, of the host executing the current SICStus Prolog process.
host_name(-HostName)
HostName is the standard host name of the host executing the current SICStus Prolog process.
pid(-PID)
PID is the identifier of the current SICStus Prolog process.
kill(+Pid, +Signal)

Sends the signal Signal to process Pid.

mktemp(+Template, -FileName)

Interface to the UNIX function mktemp(3). A unique file name is created and unified with FileName. Template should contain a file name with six trailing Xs. The unique file name is that template with the six Xs replaced by a character string.

popen(+Command, +Mode, ?Stream)

Interface to the UNIX function popen(3). Passes Command to a new default shell process for execution. Mode may be either read or write. In the former case the output from the process is piped to Stream. In the latter case the input to the process is piped from Stream. Stream may be read/written using the ordinary StreamIO predicates. It must be closed using close/1; it is not closed automatically when the process dies.

rename_file(+OldName, +NewName)

OldName is the name of an existing file or directory, which will be renamed to NewName. If the operation fails, an exception is raised.

shell

Starts a new interactive shell named by the environment variable SHELL. The control is returned to Prolog upon termination of the shell process.

shell(+Command)

Passes Command to a new shell named by the environment variable SHELL for execution. Succeeds if the C library function system() returns 0.

On MSDOS, Windows or OS/2, if SHELL is defined it is expected to name a UNIX like shell which will be invoked with the argument -c Command. If SHELL is undefined, the shell named by COMSPEC will be invoked with the argument /C Command.

shell(+Command, -Status)

Passes Command to a new shell named by the environment variable SHELL for execution. Status is unified with the value returned by the C library function system(). See also shell/1 above.

sleep(+Seconds)

Puts the SICStus Prolog process asleep for Second seconds, where Seconds may be an integer or a float. On UNIX, the usleep function will be used if Seconds is less than one, and sleep otherwise. On MSDOS, Windows or OS/2, the Sleep function will be used.

system

Starts a new interactive default shell process. The control is returned to Prolog upon termination of the shell process.

system(+Command)

Passes Command to a new default shell process for execution. Succeeds if the C library function system() returns 0.

system(+Command, -Status)

Passes Command to a new default shell process for execution. Status is unified with the value returned by the C library function system().

tmpnam(-FileName)

Interface to the ANSI C function tmpnam(3). A unique file name is created and unified with FileName.

wait(+Pid, -Status)

Waits for the child process Pid to terminate. The exit status is returned in Status. The function is similar to that of the UNIX function waitpid(3).

working_directory(?OldDirectory, ?NewDirectory)
OldDirectory is the current working directory, and the working directory is set to NewDirectory. In particular, the goal working_directory(Dir,Dir) unifies Dir with the current working directory without changing anything.


Node:Trees, Next:, Previous:System Utilities, Up:Top

Updatable Binary Trees

This package uses binary trees to represent arrays of N elements where N is fixed, unlike library(arrays). To load the package, enter the query

| ?- use_module(library(trees)).

Binary trees have the following representation: t denotes the empty tree, and t(Label,Left,Right) denotes the binary tree with label Label and children Left and Right.

gen_label(?Index, +Tree, ?Label)

Label labels the Index-th element in the Tree. Can be used to enumerate all Labels by ascending Index. Use get_label/3 instead if Index is instantiated.

get_label(+Index, +Tree, ?Label)

Label labels the Index-th element in the Tree.

list_to_tree(+List, -Tree)

Constructs a binary Tree from List where get_label(K,Tree,Lab) iff Lab is the Kth element of List.

map_tree(:Pred, +OldTree, -NewTree)

OldTree and NewTree are binary trees of the same shape and Pred(Old,New) is true for corresponding elements of the two trees.

put_label(+I, +OldTree, +Label, -NewTree)

Constructs NewTree which has the same shape and elements as OldTree, except that the I-th element is Label.

put_label(+I, +OldTree, ?OldLabel, -NewTree, ?NewLabel)

Constructs NewTree which has the same shape and elements as OldTree, except that the I-th element is changed from OldLabel to NewLabel.

tree_size(+Tree, ?Size)

Calculates as Size the number of elements in the Tree.

tree_to_list(+Tree, ?List)

Is the converse operation to list_to_tree/2. Any mapping or checking operation can be done by converting the tree to a list, mapping or checking the list, and converting the result, if any, back to a tree.


Node:UGraphs, Next:, Previous:Trees, Up:Top

Unweighted Graph Operations

Directed and undirected graphs are fundamental data structures representing arbitrary relationships between data objects. This package provides a Prolog implementation of directed graphs, undirected graphs being a special case of directed graphs.

An unweighted directed graph (ugraph) is represented as a list of (vertex-neighbors) pairs, where the pairs are in standard order (as produced by keysort with unique keys) and the neighbors of each vertex are also in standard order (as produced by sort), every neighbor appears as a vertex even if it has no neighbors itself, and no vertex is a neighbor to itself.

An undirected graph is represented as a directed graph where for each edge (U,V) there is a symmetric edge (V,U).

An edge (U,V) is represented as the term U-V. U and V must be distinct.

A vertex can be any term. Two vertices are distinct iff they are not identical (==).

A path from u to v is represented as a list of vertices, beginning with u and ending with v. A vertex cannot appear twice in a path. A path is maximal in a graph if it cannot be extended.

A tree is a tree-shaped directed graph (all vertices have a single predecessor, except the root node, which has none).

A strongly connected component of a graph is a maximal set of vertices where each vertex has a path in the graph to every other vertex.

Sets are represented as ordered lists (see Ordsets).

To load the package, enter the query

| ?- use_module(library(ugraphs)).

The following predicates are defined for directed graphs.


vertices_edges_to_ugraph(+Vertices, +Edges, -Graph)
Is true if Vertices is a list of vertices, Edges is a list of edges, and Graph is a graph built from Vertices and Edges. Vertices and Edges may be in any order. The vertices mentioned in Edges do not have to occur explicitly in Vertices. Vertices may be used to specify vertices that are not connected by any edges.
vertices(+Graph, -Vertices)
Unifies Vertices with the vertices in Graph.
edges(+Graph, -Edges)
Unifies Edges with the edges in Graph.
add_vertices(+Graph1, +Vertices, -Graph2)
Graph2 is Graph1 with Vertices added to it.
del_vertices(+Graph1, +Vertices, -Graph2)
Graph2 is Graph1 with Vertices and all edges to and from them removed from it.
add_edges(+Graph1, +Edges, -Graph2)
Graph2 is Graph1 with Edges and their "to" and "from" vertices added to it.
del_edges(+Graph1, +Edges, -Graph2)
Graph2 is Graph1 with Edges removed from it.
transpose(+Graph, -Transpose)
Transpose is the graph computed by replacing each edge (u,v) in Graph by its symmetric edge (v,u). Takes O(N^2) time.
neighbors(+Vertex, +Graph, -Neighbors)
neighbours(+Vertex, +Graph, -Neighbors)
Vertex is a vertex in Graph and Neighbors are its neighbors.
complement(+Graph, -Complement)
Complement is the complement graph of Graph, i.e. the graph that has the same vertices as Graph but only the edges that are not in Graph.
compose(+G1, +G2, -Composition)
Computes Composition as the composition of two graphs, which need not have the same set of vertices.
transitive_closure(+Graph, -Closure)
Computes Closure as the transitive closure of Graph in O(N^3) time.
symmetric_closure(+Graph, -Closure)
Computes Closure as the symmetric closure of Graph, i.e. for each edge (u,v) in Graph, add its symmetric edge (v,u). Takes O(N^2) time. This is useful for making a directed graph undirected.
top_sort(+Graph, -Sorted)
Finds a topological ordering of a Graph and returns the ordering as a list of Sorted vertices. Fails iff no ordering exists, i.e. iff the graph contains cycles. Takes O(N^2) time.
max_path(+V1, +V2, +Graph, -Path, -Cost)
Path is a longest path of cost Cost from V1 to V2 in Graph, there being no cyclic paths from V1 to V2. Takes O(N^2) time.
min_path(+V1, +V2, +Graph, -Path, -Cost)
Path is a shortest path of cost Cost from V1 to V2 in Graph. Takes O(N^2) time.
min_paths(+Vertex, +Graph, -Tree)
Tree is a tree of all the shortest paths from Vertex to every other vertex in Graph. This is the single-source shortest paths problem.
path(+Vertex, +Graph, -Path)
Given a Graph and a Vertex of Graph, returns a maximal Path rooted at Vertex, enumerating more paths on backtracking.
reduce(+Graph, -Reduced)
Reduced is the reduced graph for Graph. The vertices of the reduced graph are the strongly connected components of Graph. There is an edge in Reduced from u to v iff there is an edge in Graph from one of the vertices in u to one of the vertices in v.
reachable(+Vertex, +Graph, -Reachable)
Given a Graph and a Vertex of Graph, returns the set of vertices that are reachable from that Vertex, including Vertex itself. Takes O(N^2) time.
random_ugraph(+P, +N, -Graph)
Where P is a probability, unifies Graph with a random graph of vertices 1..N where each possible edge is included with probability P.

The following predicates are defined for undirected graphs only.


min_tree(+Graph, -Tree, -Cost)
Tree is a spanning tree of Graph with cost Cost, if it exists.
clique(+Graph, +K, -Clique)
Clique is a maximal clique (complete subgraph) of N vertices of Graph, where N>=K. N is not necessarily maximal.
independent_set(+Graph, +K, -Set)
Set is a maximal independent (unconnected) set of N vertices of Graph, where N>=K. N is not necessarily maximal.
coloring(+Graph, +K, -Coloring)
colouring(+Graph, +K, -Coloring)
Coloring is a mapping from vertices to colors 1..N of Graph such that all edges have distinct end colors, where N=<K. The mapping is represented as an ordered list of Vertex-Color pairs. N is not necessarily minimal.


Node:WGraphs, Next:, Previous:UGraphs, Up:Top

Weighted Graph Operations

A weighted directed graph (wgraph) is represented as a list of (vertex-edgelist) pairs, where the pairs are in standard order (as produced by keysort with unique keys), the edgelist is a list of (neighbor-weight) pair also in standard order (as produced by keysort with unique keys), every weight is a nonnegative integer, every neighbor appears as a vertex even if it has no neighbors itself, and no vertex is a neighbor to itself.

An undirected graph is represented as a directed graph where for each edge (U,V) there is a symmetric edge (V,U).

An edge (U,V) with weight W is represented as the term U-(V-W). U and V must be distinct.

A vertex can be any term. Two vertices are distinct iff they are not identical (==).

A path from u to v is represented as a list of vertices, beginning with u and ending with v. A vertex cannot appear twice in a path. A path is maximal in a graph if it cannot be extended.

A tree is a tree-shaped directed graph (all vertices have a single predecessor, except the root node, which has none).

A strongly connected component of a graph is a maximal set of vertices where each vertex has a path in the graph to every other vertex.

Sets are represented as ordered lists (see Ordsets).

To load the package, enter the query

| ?- use_module(library(wgraphs)).

The following predicates are defined for directed graphs.


wgraph_to_ugraph(+WeightedGraph, -Graph)
Graph has the same vertices and edges as WeightedGraph, except the edges of Graph are unweighted.
ugraph_to_wgraph(+Graph, -WeightedGraph)
WeightedGraph has the same vertices and edges as Graph, except the edges of WeightedGraph all have weight 1.
vertices_edges_to_wgraph(+Vertices, +Edges, -WeightedGraph)
Vertices is a list of vertices, Edges is a list of edges, and WeightedGraph is a graph built from Vertices and Edges. Vertices and Edges may be in any order. The vertices mentioned in Edges do not have to occur explicitly in Vertices. Vertices may be used to specify vertices that are not connected by any edges.
vertices(+WeightedGraph, -Vertices)
Unifies Vertices with the vertices in WeightedGraph.
edges(+WeightedGraph, -Edges)
Unifies Edges with the edges in WeightedGraph.
add_vertices(+WeightedGraph1, +Vertices, -WeightedGraph2)
WeightedGraph2 is WeightedGraph1 with Vertices added to it.
del_vertices(+WeightedGraph1, +Vertices, -WeightedGraph2)
WeightedGraph2 is WeightedGraph1 with Vertices and all edges to and from them removed from it.
add_edges(+WeightedGraph1, +Edges, -WeightedGraph2)
WeightedGraph2 is WeightedGraph1 with Edges and their "to" and "from" vertices added to it.
del_edges(+WeightedGraph1, +Edges, -WeightedGraph2)
WeightedGraph2 is WeightedGraph1 with Edges removed from it.
transpose(+WeightedGraph, -Transpose)
Transpose is the graph computed by replacing each edge (u,v) in WeightedGraph by its symmetric edge (v,u). It can only be used one way around. Takes O(N^2) time.
neighbors(+Vertex, +WeightedGraph, -Neighbors)
neighbours(+Vertex, +WeightedGraph, -Neighbors)
Vertex is a vertex in WeightedGraph and Neighbors are its weighted neighbors.
transitive_closure(+WeightedGraph, -Closure)
Computes Closure as the transitive closure of WeightedGraph in O(N^3) time.
symmetric_closure(+WeightedGraph, -Closure)
Computes Closure as the symmetric closure of WeightedGraph, i.e. for each edge (u,v) in WeightedGraph, add its symmetric edge (v,u). Takes O(N^2) time. This is useful for making a directed graph undirected.
top_sort(+WeightedGraph, -Sorted)
Finds a topological ordering of a WeightedGraph and returns the ordering as a list of Sorted vertices. Fails iff no ordering exists, i.e. iff the graph contains cycles. Takes O(N^2) time.
max_path(+V1, +V2, +WeightedGraph, -Path, -Cost)
Path is a maximum-cost path of cost Cost from V1 to V2 in WeightedGraph, there being no cyclic paths from V1 to V2. Takes O(N^2) time.
min_path(+V1, +V2, +WeightedGraph, -Path, -Cost)
Path is a minimum-cost path of cost Cost from V1 to V2 in WeightedGraph. Takes O(N^2) time.
min_paths(+Vertex, +WeightedGraph, -Tree)
Tree is a tree of all the minimum-cost paths from Vertex to every other vertex in WeightedGraph. This is the single-source minimum-cost paths problem.
path(+Vertex, +WeightedGraph, -Path)
Given a WeightedGraph and a Vertex of WeightedGraph, returns a maximal Path rooted at Vertex, enumerating more paths on backtracking.
reduce(+WeightedGraph, -Reduced)
Reduced is the reduced graph for WeightedGraph. The vertices of the reduced graph are the strongly connected components of WeightedGraph. There is an edge in Reduced from u to v iff there is an edge in WeightedGraph from one of the vertices in u to one of the vertices in v.
reachable(+Vertex, +WeightedGraph, -Reachable)
Given a WeightedGraph and a Vertex of WeightedGraph, returns the set of vertices that are reachable from that Vertex. Takes O(N^2) time.
random_wgraph(+P, +N, +W, -WeightedGraph)
Where P is a probability, unifies WeightedGraph with a random graph of vertices 1..N where each possible edge is included with probability P and random weight in 1..W.

The following predicate is defined for undirected graphs only.


min_tree(+WeightedGraph, -Tree, -Cost)
Tree is a minimum-cost spanning tree of WeightedGraph with cost Cost, if it exists.


Node:Sockets, Next:, Previous:WGraphs, Up:Top

Socket I/O

This library package defines a number of predicates manipulating sockets. They are all rather straight-forward interfaces to the corresponding BSD-type socket functions with the same name (except current_host/1). The reader should therefore study the appropriate documents for a deeper description.

The Domain is either the atom 'AF_INET' or 'AF_UNIX'. They correspond directly to the same domains in BSD-type sockets. 'AF_UNIX' may not be available on non-UNIX platforms.

An Address is either 'AF_INET'(Host,Port) or 'AF_UNIX'(SocketName). Host is an atom denoting a hostname (not an IP-address), Port is a portnumber and SocketName is an atom denoting a socket. A reader familiar with BSD sockets will understand this immediately.

All streams below can be both read from and written on. All I/O-predicates operating on streams can be used, for example read/2, write/2, format/3, current_stream/3, etc. Socket streams are block buffered both on read and write by default. This can be changed by calling socket_buffering/4.

To load the package, enter the query

| ?- use_module(library(sockets)).
socket(+Domain, -Socket)

A socket Socket in the domain Domain is created.

socket_close(+Socket)

Socket is closed. Sockets used in socket_connect/2 should not be closed by socket_close/1 as they will be closed when the corresponding stream is closed.

socket_bind(+Socket, 'AF_UNIX'(+SocketName))
socket_bind(+Socket, 'AF_INET'(?Host,?Port))

The socket Socket is bound to the address. If Port is uninstantiated, the operating system picks a port number to which Port is bound.

socket_connect(+Socket, 'AF_UNIX'(+SocketName), -Stream)
socket_connect(+Socket, 'AF_INET'(+Host,+Port), -Stream)

The socket Socket is connected to the address. Stream is a special stream on which items can be both read and written.

socket_listen(+Socket, +Length)

The socket Socket is defined to have a maximum backlog queue of Length pending connections.

socket_accept(+Socket, -Stream)
socket_accept(+Socket, -Client, -Stream)

The first connection to socket Socket is extracted. The stream Stream is opened for read and write on this connection. For the 'AF_INET' domain, Client will unified with an atom containing the Internet host address of the connecting entity in numbers-and-dots notation. For other domains, Client will be unbound.

socket_buffering(+Stream, +Direction, -OldBuf, +NewBuf)

The buffering in the Direction of the socket stream Stream is changed from OldBuf to NewBuf. Direction should be read or write. OldBuf and NewBuf should be unbuf for unbuffered I/O or fullbuf for block buffered I/O.

socket_select(+TermsSockets, -NewTermsStreams, +TimeOut, +Streams, -ReadStreams)

The list of streams in Streams is checked for readable characters. The list ReadStreams returns the streams with readable data. On Windows only socket streams can be used with socket_select. On UNIX a stream can be any stream associated with a file descriptor but socket_select/5 may block for non-socket streams even though there is data available. The reason is that non-socket streams can have buffered data available, e.g. within a C stdio FILE*.

socket_select/5 also waits for connections to the sockets specified by TermsSockets. This argument should be a list of Term-Socket pairs, where Term, which can be any term, is used as an identifier. NewTermsStreams is a list of Term-connection(Client,Stream) pairs, where Stream is a new stream open for communicating with a process connecting to the socket identified with Term, Client is the client host address (see socket_accept/3).

If TimeOut is instantiated to off, the predicate waits until something is available. If TimeOut is S:U the predicate waits at most S seconds and U microseconds. Both S and U must be integers >=0. If there is a timeout, ReadStreams and NewTermsStreams are [].

socket_select(+Sockets, -NewStreams, +TimeOut, +Streams, -ReadStreams)
socket_select(+Socket, -NewStream, +TimeOut, +Streams, -ReadStreams)
socket_select(+Sockets, -NewStreams, -NewClients, +TimeOut, +Streams, -ReadStreams)
socket_select(+Socket, -NewStream, -NewClient, +TimeOut, +Streams, -ReadStreams)

These forms, which are provided for backward compatibility only, differs in how sockets are specified and new streams returned.

socket_select/[5,6] also wait for connections to the sockets in the list Sockets. NewStreams is the list of new streams opened for communicating with the connecting processes. NewClients is the corresponding list of client host addresses (see socket_accept/3).

The second form requires one socket (not a list) for the first argument and returns a stream, NewStream, if a connection is made.

current_host(?HostName)

HostName is unified with the fully qualified name of the machine the process is executing on. The call will also succeed if HostName is instantiated to the unqualified name of the machine.

hostname_address(+HostName, -HostAddress)
hostname_address(-HostName, +HostAddress)

The Internet host is resolved given either the host name or address. HostAddress should be an atom containing the Internet host address in numbers-and-dots notation. The predicate will fail if the host name or address cannot be resolved.


Node:Linda Library, Next:, Previous:Sockets, Up:Top

Linda--Process Communication

Linda is a concept for process communication.

For an introduction and a deeper description, see [Carreiro & Gelernter 89a] or [Carreiro & Gelernter 89b], respectively.

One process is running as a server and one or more processes are running as clients. The processes are communicating with sockets and supports networks.

The server is in principle a blackboard on which the clients can write (out/1), read (rd/1) and remove (in/1) data. If the data is not present on the blackboard, the predicates suspend the process until they are available.

There are some more predicates besides the basic out/1, rd/1 and in/1. The in_noblock/1 and rd_noblock/1 does not suspend if the data is not available--they fail instead. A blocking fetch of a conjunction of data can be done with in/2 or rd/2.

Example: A simple producer-consumer. In client 1:

producer :-
       produce(X),
       out(p(X)),
       producer.

produce(X) :- .....

In client 2:

consumer :-
       in(p(A)),
       consume(A),
       consumer.

consume(A) :- .....

Example: Synchronization

       ...,
       in(ready),  %Waits here until someone does out(ready)
       ...,

Example: A critical region

       ...,
       in(region_free),  % wait for region to be free
       critical_part,
       out(region_free), % let next one in
       ...,

Example: Reading global data

       ...,
       rd(data(Data)),
       ...,

or, without blocking:
       ...,
       rd_noblock(data(Data)) ->
             do_something(Data)
       ;     write('Data not available!'),nl
       ),
       ...,

Example: Waiting for one of several events

       ...,
       in([e(1),e(2),...,e(n)], E),
%  Here is E instantiated to the first tuple that became available
       ...,


Node:Server, Next:, Previous:Linda Library, Up:Linda Library

Server

The server is the process running the "blackboard process". It is an ordinary SICStus process which can be run on a separate machine if necessary.

To load the package, enter the query

| ?- use_module(library('linda/server')).

and start the server with linda/0 or linda/1.

linda

Starts a Linda-server in this SICStus. The network address is written to current output stream as Host:PortNumber.

linda(+Hook)

Starts a Linda-server in this SICStus. When it is started, a goal passed in Hook is evaluated. Hook must have the form Address-Goal where Address must be unifiable with Host:Port and Goal must be instantiated to a goal. Example:

| ?- linda((Host:Port)-(my_module:mypred(Host,Port))).
will call mypred/2 in module my_module when the server is started. mypred/2 could start the client-processes, save the address for the clients etc. Note that the module must be present in Goal.


Node:Client, Previous:Server, Up:Linda Library

Client

The clients are one or more sicstus processes which have connection(s) to the server.

To load the package, enter the query

| ?- use_module(library('linda/client')).

Some of the following predicates fail if they don't receive an answer from the Linda-server in a reasonable amount of time. That time is set with the predicate linda_timeout/2.

linda_client(+Address)

Establishes a connection to a Linda-server specified by Address. The Address is of the format Host:PortNumber as given by linda/[0,1] and linda/1.

It is not possible to be connected to two Linda-servers at the same time.

This predicate can fail due to a timeout.

close_client

Closes the connection to the server.

shutdown_server/0

Sends a Quit signal to the server, which keeps running after receiving this signal, until such time as all the clients have closed their connections. It is up to the clients to tell each other to quit. When all the clients are done, the server stops (i.e. linda/[0,1] succeeds). Courtesy of Malcolm Ryan. Note that close_client/0 should be called after shutdown_server/0. shutdown_server/0 will raise an error if there is no connection between the client and the server.

linda_timeout(?OldTime, ?NewTime)

This predicate controls Linda's timeout. OldTime is unified with the old timeout and then timeout is set to NewTime. The value is either off or of the form Seconds:Milliseconds. The former value indicates that the timeout mechanism is disabled, that is, eternal waiting. The latter form is the timeout-time.

out(+Tuple)

Places the tuple Tuple in Linda's tuple-space.

in(?Tuple)

Removes the tuple Tuple from Linda's tuple-space if it is there. If not, the predicate blocks until it is available (that is, someone performs an out/1).

in_noblock(?Tuple)

Removes the tuple Tuple from Linda's tuple-space if it is there. If not, the predicate fails.

This predicate can fail due to a timeout.

in(+TupleList, ?Tuple)

As in/1 but succeeds when either of the tuples in TupleList is available. Tuple is unified with the fetched tuple. If that unification fails, the tuple is not reinserted in the tuple-space.

rd(?Tuple)

Succeeds if Tuple is available in the tuple-space, suspends otherwise until it is available. Compare this with in/1: the tuple is not removed.

rd_noblock(?Tuple)

Succeeds if Tuple is available in the tuple-space, fails otherwise.

This predicate can fail due to a timeout.

rd(+TupleList, ?Tuple)

As in/2 but does not remove any tuples.

bagof_rd_noblock(?Template, +Tuple, ?Bag)

Bag is the list of all instances of Template such that Tuple exists in the tuple-space.

The behavior of variables in Tuple and Template is as in bagof/3. The variables could be existentially quantified with ^/2 as in bagof/3.

The operation is performed as an atomic operation.

This predicate can fail due to a timeout.

Example: Assume that only one client is connected to the server and that the tuple-space initially is empty.

| ?- out(x(a,3)), out(x(a,4)), out(x(b,3)), out(x(c,3)).

yes
| ?- bagof_rd_noblock(C-N, x(C,N), L).

C = _32,
L = [a-3,a-4,b-3,c-3],
N = _52 ?

yes
| ?- bagof_rd_noblock(C, N^x(C,N), L).

C = _32,
L = [a,a,b,c],
N = _48 ?

yes


Node:BDB, Next:, Previous:Linda Library, Up:Top

External Storage of Terms (Berkeley DB)

This library module handles storage and retrieval of terms on files. By using indexing, the store/retrieve operations are efficient also for large data sets. The package is an interface to the Berkeley DB toolset.

The package is loaded by the query:

| ?- use_module(library(bdb)).


Node:Basics, Next:, Previous:BDB, Up:BDB

Basics

The idea is to get a behavior similar to assert/1, retract/1 and clause/2, but the terms are stored on files instead of in primary memory.

The differences compared with the internal database are:

Some commercial databases can't store non-ground terms or more than one instance of a term. This library module can however store terms of either kind.


Node:Current Limitations, Next:, Previous:Basics, Up:BDB

Current Limitations


Node:Berkeley DB, Next:, Previous:Current Limitations, Up:BDB

Berkeley DB

This library module is an interface to the Berkeley DB toolset to support persistent storage of Prolog terms. Some of the notions of Berkeley DB are directly inherited, e.g. the environment.

The interface uses the Concurrent Access Methods product of Berkeley DB. This means that multiple processes can open the same databas, but transactions and disaster recovery are not supported.

The environment and the database files are ordinary Berkeley DB entities which means that the standard support utilities (e.g. db_stat) will work.


Node:The DB-Spec Informal Description, Next:, Previous:Berkeley DB, Up:BDB

The DB-Spec--Informal Description

The db-spec defines which functors are allowed and which parts of a term are used for indexing in a database. The syntax of a spec resembles to that of the mode specification. The db-spec is a list of atoms and compound terms where the arguments are either + or -. A term can be inserted in the database if there is a spec in the spec list with the same functor.

Multilevel indexing is not supported, terms have to be "flattened".

Every spec with the functor of the indexed term specifies an indexing. Every argument where there is a + in the spec is indexed on.

The idea of the db-spec is illustrated with a few examples. (A section further down explains the db-spec in a more formal way).

Given a spec of [f(+,-), .(+,-), g, f(-,+)] the indexing works as follows. (The parts with indexing are underlined.)

Term Store Fetch

g(x,y) domain error domain error

f(A,B) f(A,B) instantiation error
-

f(a,b) f(a,b) f(a,b) f(a,b)
- - - - - -

[a,b] .(a,.(b,[])) .(a,.(b,[]))
- - - -

g g g
- -

The specification [f(+,-), f(-,+)] is different from [f(+,+)]. The first specifies that two indices are to be made whereas the second specifies that only one index is to be made on both arguments of the term.


Node:Predicates, Next:, Previous:The DB-Spec Informal Description, Up:BDB

Predicates


Node:Conventions, Next:, Previous:Predicates, Up:Predicates

Conventions

The following conventions are used in the predicate descriptions below.


Node:The environment, Next:, Previous:Conventions, Up:Predicates

The environment

To enable sharing of databases between process, programs have to create environments and the databases should be opened in these environments. A database can be shared between processes that open it in the same environment. An environment physically consists of a directory containing the files needed to enable sharing databases between processes. The directory of the environment has to be located in a local file system.

Databases can be opened outside any environment (see db_open/4), but in that case a process writing the database must ensure exclusive access or the behavior of the predicates is undefined.


Node:Memory leaks, Next:, Previous:The environment, Up:Predicates

Memory leaks

In order to avoid memory leaks, environments, databases and iterators should always be closed explicitly. Consider using call_cleanup/2 to automate the closing/deallocation of these objects. You can always use db_current_env/1, db_current/5 and db_current_iterator/3 to enumerate the currently living objects. NOTE: a database must not be closed while there are outstanding choices for some db_fetch/3 goal that refers to that database. Outstanding choices can be removed with a cut (!).


Node:The predicates, Previous:Memory leaks, Up:Predicates

The predicates

db_open_env(+EnvName, -EnvRef)
db_open_env(+EnvName, +CacheSize, -EnvRef)

Opens an environment with the name EnvName. A directory with this name is created for the environment if necessary. EnvName is not subject to absolute_file_name/3 conversion.

By using db_open_env/3 one can specify the size of the cache: CacheSize is the (integer) size of the cache in kilobytes. The size of the cache cannot be less than 20 kilobytes. db_open_env/2 will create a cache of the system's default size.

The size of the cache is determined when the environment is created and cannot be changed by future openings.

A process cannot open the same environment more than once.

db_close_env(+EnvRef)

Closes an environment. All databases opened in the environment will be closed as well.

db_current_env(?EnvName, ?EnvRef)

Unifies the arguments with the open environments. This predicate can be used for enumerating all currently open environments through backtracking.

db_open(+DBName, +Mode, ?SpecList, -DBRef)
db_open(+DBName, +Mode, ?SpecList, +Options, -DBRef)

Opens a database with the name DBName. The database physically consists of a directory with the same name, containing the files that make up the database. If the directory does not exist, it is created. In that case Mode must be update and the db-spec SpecList must be ground. If an existing database is opened and Mode is read or update, SpecList is unified with the db-spec given when the database was created. If the unification fails an error is raised. DBRef is unified with a reference to the opened database. DBName is not subject to absolute_file_name/3 conversion.

If Mode is enumerate then the indexing specification is not read, and SpecList is left unbound.

Options provides a way to specify an environment in which to open the database, or a cache size. Options should be a list of terms of the following form:

environment(EnvRef)
The database will be opened in this environment.
cache_size(CacheSize)
This is the (integer) size of the cache in kilobytes. The size of the cache cannot be less than 20 kilobytes. If CacheSize is given as the atom default, a default cache size will be used. If CacheSize is given as the atom off or the atom none, all modified records will be flushed to disk after each operation.

To avoid inconsistency, if multiple processes open the same database, then all of them should do that with Mode set to read or enumerate. (This is not enforced by the system.)

db_close(+DBRef)

Closes the database referenced by DBRef. Any iterators opened in the database will be deallocated.

db_current(?DBName, ?Mode, ?SpecList, ?EnvRef, ?DBRef)

Unifies the arguments with the open databases. This predicate can be used to enumerate all currently open databases through backtracking. If the database was opened without an environment, then EnvRef will be unified with the atom none.

db_store(+DBRef, +Term, -TermRef)

Stores Term in the database DBRef. TermRef is unified with a corresponding term reference. The functor of Term must match the functor of a spec in the db-spec associated with DBRef.

db_fetch(+DBRef, ?Term, ?TermRef)

Unifies Term with a term from the database DBRef. At the same time, TermRef is unified with a corresponding term reference. Backtracking over the predicate unifies with all terms matching Term.

If TermRef is not instantiated then both the functor and the instantiatedness of Term must match a spec in the db-spec associated with DBRef.

If TermRef is instantiated, the referenced term is read and unified with Term.

If you simply want to find all matching terms, it is more efficient to use db_findall/5 or db_enumerate/3.

db_findall(+DBRef, +Template, +Term, :Goal, ?Bag)

Unifies Bag with the list of instances of Template in all proofs of Goal found when Term is unified with a matching term from the database DBRef. Both the functor and the instantiatedness of Term must match a spec in the db-spec associated with DBRef. Conceptually, this predicate is equivalent to findall(Template, (db_fetch(DBRef, Term, _), Goal), Bag).

db_erase(+DBRef, +TermRef)
db_erase(+DBRef, +TermRef, +Term)

Deletes the term from the database DBRef that is referenced by TermRef.

In the case of db_erase/2 the term associated with TermRef has to be looked up. db_erase/3 assumes that the term Term is identical with the term associated with TermRef (modulo variable renaming). If this is not the case, the behavior is undefined.

db_enumerate(+DBRef, ?Term, ?TermRef)

Unifies Term with a term from the database DBRef. At the same time, TermRef is unified with a corresponding term reference. Backtracking over the predicate unifies with all terms matching Term.

Implemented by linear search--the db-spec associated with DBRef is ignored. It is not useful to call this predicate with TermRef instantiated.

db_compress(+DBRef, +DBName)
db_compress(+DBRef, +DBName, +SpecList)
Copies the database given by DBRef to a new database named by DBName. The new database will be a compressed version of the first one in the sense that it will not have "holes" resulting from deletion of terms. Deleted term references will also be reused, which implies that references that refer to terms in the old database will be invalid in the new one.

db_compress/2 looks for a database with the db-spec of the original one. db_compress/3 stores the terms found in the original database with the indexing specification SpecList. db_compress/2 cannot be used if the database DBRef was opened in mode enumerate.

If the database DBName already exists then the terms of DBRef will be appended to it. Of course DBName must have an indexing specification which enables the terms in DBRef to be inserted into it.

In the case of db_compress/3 if the database DBName does not exist, then SpecList must be a valid indexing specification.

db_make_iterator(+DBRef, -Iterator)
db_make_iterator(+DBRef, +Term, -Iterator)

Creates a new iterator and unifies it with Iterator. Iterators created with db_make_iterator/2 iterate through the whole database. Iterators created with db_make_iterator/3 iterate through the terms that would be found by db_fetch(DBRef, Term, _).

Every iterator created by db_make_iterator/[2,3] must be destroyed with db_iterator_done/1.

db_iterator_next(+Iterator, ?Term, ?TermRef)

Iterator advances to the next term, Term and TermRef is unified with the term and its reference pointed to by Iterator. If there is no next term, the predicate fails.

db_iterator_done(+Iterator)

Deallocates Iterator, which must not be in use anymore.

db_current_iterator(?DBRef, ?Term, ?Iterator)

Unifies the the variables with the respective properties of the living iterators. This predicate can be used to enumerate all currently alive iterators through backtracking. If Iterator was made with db_make_iterator/2 then Term will be left unbound.


Node:An Example Session, Next:, Previous:Predicates, Up:BDB

An Example Session

| ?- db_open('/tmp/db', update, [a(+,-)], '$db_env'(-33470544), DBRef).

DBRef = '$db'(-33470432) ?

yes
| ?- db_store('$db'(-33470432), a(b,1), _).

yes
| ?- db_store('$db'(-33470432), a(c,2), _).

yes
| ?- db_fetch('$db'(-33470432), a(b,X), _).

X = 1 ? ;

no
| ?- db_enumerate('$db'(-33470432), X, _).

X = a(b,1) ? ;

X = a(c,2) ? ;

no
| ?- db_current(DBName, Mode, Spec, EnvRef, DBRef).

Mode = update,
Spec = [a(+,-)],
DBRef = '$db'(-33470432),
DBName = '/tmp/db',
EnvRef = '$db_env'(-33470544) ? ;

no
| ?- db_close_env('$db_env'(-33470544)).

yes


Node:The DB-Spec, Previous:An Example Session, Up:BDB

The DB-Spec

A db-spec has the form of a speclist:

speclist
= [spec1, ..., specM]
spec
= functor(argspec1, ..., argspecN)
argspec
= + | -
where functor is a Prolog atom. The case N = 0 is allowed.

A spec F(argspec1, ..., argspecN) is applicable to any nonvar term with principal functor F/N.

When storing a term T we generate a hash code for every applicable spec in the db-spec, and a reference to T is stored with each of them. (More precisely with each element of the set of generated hash codes). If T contains nonvar elements on each + position in the spec, then the hash code depends on each of these elements. If T does contain some variables on + position, then the hash code depends only on the functor of T.

When fetching a term Q we look for an applicable spec for which there are no variables in Q on positions maked +. If no applicable spec can be found a domain error is raised. If no spec can be found where on each + position a nonvar term occurs in Q an instantiation error is raised. Otherwise, we choose the the spec with the most + postitions in it breaking ties by choosing the leftmost one.

The terms that contain nonvar terms on every + postition will be looked up using indexing based on the principal functor of the term and the principal functor of terms on + postitions. The other (more general) terms will be looked up using an indexing based on the principal functor of the term only.

As can be seen, storing and fetching terms with variables on + positions are not vigorously supported operations.


Node:CLPB, Next:, Previous:BDB, Up:Top

Boolean Constraint Solver

The clp(B) system provided by this library module is an instance of the general Constraint Logic Programming scheme introduced in [Jaffar & Michaylov 87]. It is a solver for constraints over the Boolean domain, i.e. the values 0 and 1. This domain is particularly useful for modeling digital circuits, and the constraint solver can be used for verification, design, optimization etc. of such circuits.

To load the solver, enter the query:

| ?- use_module(library(clpb)).

The solver contains predicates for checking the consistency and entailment of a constraint wrt. previous constraints, and for computing particular solutions to the set of previous constraints.

The underlying representation of Boolean functions is based on Boolean Decision Diagrams [Bryant 86]. This representation is very efficient, and allows many combinatorial problems to be solved with good performance.

Boolean expressions are composed from the following operands: the constants 0 and 1 (FALSE and TRUE), logical variables, and symbolic constants, and from the following connectives. P and Q are Boolean expressions, X is a logical variable, Is is a list of integers or integer ranges, and Es is a list of Boolean expressions:

~ P
True if P is false.
P * Q
True if P and Q are both true.
P + Q
True if at least one of P and Q is true.
P # Q
True if exactly one of P and Q is true.
X ^ P
True if there exists an X such that P is true. Same as P[X/0] + P[X/1].
P =:= Q
Same as ~P # Q.
P =\= Q
Same as P # Q.
P =< Q
Same as ~P + Q.
P >= Q
Same as P + ~Q.
P < Q
Same as ~P * Q.
P > Q
Same as P * ~Q.
card(Is, Es)
True if the number of true expressions in Es is a member of the set denoted by Is.

Symbolic constants (Prolog atoms) denote parametric values and can be viewed as all-quantified variables whose quantifiers are placed outside the entire expression. They are useful for forcing certain variables of an equation to be treated as input parameters.


Node:CLPB Interface, Next:, Previous:CLPB, Up:CLPB

Solver Interface

The following predicates are defined:

sat(+Expression)

Expression is a Boolean expression. This checks the consistency of the expression wrt. the accumulated constraints, and, if the check succeeds, tells the constraint that the expression be true.

If a variable X, occurring in the expression, is subsequently unified with some term T, this is treated as a shorthand for the constraint

?- sat(X=:=T).

taut(+Expression, ?Truth)

Expression is a Boolean expression. This asks whether the expression is now entailed by the accumulated constraints (Truth=1), or whether its negation is entailed by the accumulated constraints (Truth=0). Otherwise, it fails.

labeling(+Variables)

Variables is a list of variables. The variables are instantiated to a list of 0s and 1s, in a way that satisfies any accumulated constraints. Enumerates all solutions by backtracking, but creates choicepoints only if necessary.


Node:CLPB Examples, Previous:CLPB Interface, Up:CLPB

Examples


Node:Example 1, Next:, Previous:CLPB Examples, Up:CLPB Examples

Example 1

| ?- sat(X + Y).

sat(X=\=_A*Y#Y) ?

illustrates three facts. First, any accumulated constraints affecting the top-level variables are displayed as floundered goals, since the query is not true for all X and Y. Secondly, accumulated constraints are displayed as sat(V=:=Expr) or sat(V=\=Expr) where V is a variable and Expr is a "polynomial", i.e. an exclusive or of conjunctions of variables and constants. Thirdly, _A had to be introduced as an artificial variable, since Y cannot be expressed as a function of X. That is, X + Y is true iff there exists an _A such that X=\=_A*Y#Y. Let's check it!

| ?- taut(_A ^ (X=\=_A*Y#Y) =:= X + Y, T).

T = 1 ?

verifies the above answer. Notice that the formula in this query is a tautology, and so it is entailed by an empty set of constraints.


Node:Example 2, Next:, Previous:Example 1, Up:CLPB Examples

Example 2

| ?- taut(A =< C, T).

no
| ?- sat(A =< B), sat(B =< C), taut(A =< C, T).

T = 1,
sat(A=:=_A*_B*C),
sat(B=:=_B*C) ?

| ?- taut(a, T).

T = 0 ?

yes
| ?- taut(~a, T).

T = 0 ?

illustrates the entailment predicate. In the first query, the expression "A implies C" is neither known to be true nor false, so the query fails. In the second query, the system is told that "A implies B" and "B implies C", so "A implies C" is entailed. The expressions in the third and fourth queries are to be read "for each a, a is true" and "for each a, a is false", respectively, and so T = 0 in both cases since both are unsatisfiable. This illustrates the fact that the implicit universal quantifiers introduced by symbolic constants are placed in front of the entire expression.


Node:Example 3, Next:, Previous:Example 2, Up:CLPB Examples

Example 3

| ?- [user].
| adder(X, Y, Sum, Cin, Cout) :-
     sat(Sum =:= card([1,3],[X,Y,Cin])),
     sat(Cout =:= card([2-3],[X,Y,Cin])).
| {user consulted, 40 msec 576 bytes}

yes
| ?- adder(x, y, Sum, cin, Cout).

sat(Sum=:=cin#x#y),
sat(Cout=:=x*cin#x*y#y*cin) ?

yes
| ?- adder(x, y, Sum, 0, Cout).

sat(Sum=:=x#y),
sat(Cout=:=x*y) ?

yes
| ?- adder(X, Y, 0, Cin, 1), labeling([X,Y,Cin]).

Cin = 0,
X = 1,
Y = 1 ? ;

Cin = 1,
X = 0,
Y = 1 ? ;

Cin = 1,
X = 1,
Y = 0 ? ;

illustrates the use of cardinality constraints and models a one-bit adder circuit. The first query illustrates how representing the input signals by symbolic constants forces the output signals to be displayed as functions of the inputs and not vice versa. The second query computes the simplified functions obtained by setting carry-in to 0. The third query asks for particular input values satisfying sum and carry-out being 0 and 1, respectively.


Node:Example 4, Previous:Example 3, Up:CLPB Examples

Example 4

The predicate fault/3 below describes a 1-bit adder consisting of five gates, with at most one faulty gate. If one of the variables Fi is equal to 1, the corresponding gate is faulty, and its output signal is undefined (i.e. the constraint representing the gate is relaxed).

Assuming that we have found some incorrect output from a circuit, we are interesting in finding the faulty gate. Two instances of incorrect output are listed in fault_ex/2:

fault([F1,F2,F3,F4,F5], [X,Y,Cin], [Sum,Cout]) :-
        sat(
                    card([0-1],[F1,F2,F3,F4,F5]) *
                    (F1 + (U1 =:= X * Cin)) *
                    (F2 + (U2 =:= Y * U3)) *
                    (F3 + (Cout =:= U1 + U2)) *
                    (F4 + (U3 =:= X # Cin)) *
                    (F5 + (Sum =:= Y # U3))
                ).

fault_ex(1, Faults) :- fault(Faults, [1,1,0], [1,0]).
fault_ex(2, Faults) :- fault(Faults, [1,0,1], [0,0]).

To find the faulty gates, we run the query

| ?- fault_ex(I,L), labeling(L).

I = 1,
L = [0,0,0,1,0] ? ;

I = 2,
L = [1,0,0,0,0] ? ;

I = 2,
L = [0,0,1,0,0] ? ;

no

Thus for input data [1,1,0], gate 4 must be faulty. For input data [1,0,1], either gate 1 or gate 3 must be faulty.

To get a symbolic representation of the outputs interms of the input, we run the query

| ?- fault([0,0,0,0,0], [x,y,cin], [Sum,Cout]).

sat(Cout=:=x*cin#x*y#y*cin),
sat(Sum=:=cin#x#y)

which shows that the sum and carry out signals indeed compute the intended functions if no gate is faulty.


Node:CLPQR, Next:, Previous:CLPB, Up:Top

Constraint Logic Programming over Rationals or Reals


Node:Introduction, Next:, Previous:CLPQR, Up:CLPQR

Introduction

The clp(Q,R) system described in this document is an instance of the general Constraint Logic Programming scheme introduced by [Jaffar & Michaylov 87].

The implementation is at least as complete as other existing clp(R) implementations: It solves linear equations over rational or real valued variables, covers the lazy treatment of nonlinear equations, features a decision algorithm for linear inequalities that detects implied equations, removes redundancies, performs projections (quantifier elimination), allows for linear dis-equations, and provides for linear optimization.

The full clp(Q,R) distribution, including a stand-alone manual and an examples directory that is possibly more up to date than the version in the SICStus Prolog distribution, is available from: http://www.ai.univie.ac.at/clpqr/.


Node:Referencing CLPQR, Next:, Previous:Introduction, Up:Introduction

Referencing this Software

When referring to this implementation of clp(Q,R) in publications, you should use the following reference:

Holzbaur C.: OFAI clp(q,r) Manual, Edition 1.3.3, Austrian Research Institute for Artificial Intelligence, Vienna, TR-95-09, 1995.


Node:Acknowledging CLPQR, Previous:Referencing CLPQR, Up:Introduction

Acknowledgments

The development of this software was supported by the Austrian Fonds zur Foerderung der Wissenschaftlichen Forschung under grant P9426-PHY. Financial support for the Austrian Research Institute for Artificial Intelligence is provided by the Austrian Federal Ministry for Science and Research.

We include a collection of examples that has been distributed with the Monash University version of clp(R) [Heintze et al. 87], and its inclusion into this distribution was kindly permitted by Roland Yap.


Node:CLPQR Interface, Next:, Previous:Introduction, Up:CLPQR

Solver Interface

Until rational numbers become first class citizens in SICStus Prolog, rational arithmetics has to be emulated. Because of the emulation it is too expensive to support arithmetics with automatic coercion between all sorts of numbers, like you find it in CommonLisp, for example.

You must choose whether you want to operate in the field of Q (Rationals) or R (Reals):

| ?- use_module(library(clpq)).

or

| ?- use_module(library(clpr)).

You can also load both modules, but the exported predicates listed below will name-clash (see Importation). You can avoid the interactive resolution dialog if the importation is skipped, e.g. via: use_module(library(clpq),[]),use_module(library(clpr),[]).


Node:Notational Conventions, Next:, Previous:CLPQR Interface, Up:CLPQR Interface

Notational Conventions

Throughout this chapter, the prompts clp(q) ?- and clp(r) ?- are used to differentiate between clp(Q) and clp(R) in exemplary interactions.

In general there are many ways to express the same linear relationship. This degree of freedom is manifest in the fact that the printed manual and an actual interaction with the current version of clp(Q,R) may show syntactically different answer constraints, despite the fact the same semantic relationship is being expressed. There are means to control the presentation; see Variable Ordering. The approximative nature of floating point numbers may also produce numerical differences between the text in this manual and the actual results of clp(R), for a given edition of the software.


Node:Solver Predicates, Next:, Previous:Notational Conventions, Up:CLPQR Interface

Solver Predicates

The solver interface for both Q and R consists of the following predicates which are exported from module(linear).

{+Constraint}

Constraint is a term accepted by the the grammar below. The corresponding constraint is added to the current constraint store and checked for satisfiability. Use the module prefix to distinguish the solvers if both clp(Q) and clp(R) were loaded

| ?- clpr:{Ar+Br=10}, Ar=Br, clpq:{Aq+Bq=10}, Aq=Bq.

Aq = 5,
Ar = 5.0,
Bq = 5,
Br = 5.0

Although clp(Q) and clp(R) are independent modules, you are asking for trouble if you (accidently) share variables between them:

| ?- clpr:{A+B=10}, clpq:{A=B}.
! Type error in argument 2 of clpq:=/2
! a rational number expected, but 5.0 found
! goal:  _118=5.0

This is because both solvers eventually compute values for the variables and Reals are incompatible with Rationals.

Here is the constraint grammar:

Constraint  -->          C
                      | C , C          conjunction 

C -->          Expr =:= Expr       equation 
              | Expr  =  Expr       equation 
              | Expr  <  Expr       strict inequation 
              | Expr  >  Expr       strict inequation 
              | Expr =<  Expr       nonstrict inequation 
              | Expr >=  Expr       nonstrict inequation 
              | Expr =\= Expr       disequation 

Expr -->     variable              Prolog variable 
            | number             floating point or integer 
            | + Expr             unary plus 
            | - Expr             unary minus 
            | Expr + Expr        addition 
            | Expr - Expr        subtraction 
            | Expr * Expr        multiplication 
            | Expr / Expr        division 
            | abs(Expr)           absolute value 
            | sin(Expr)           trigonometric sine 
            | cos(Expr)           trigonometric cosine 
            | tan(Expr)           trigonometric tangent 
            | pow(Expr,Expr)      raise to the power 
            | exp(Expr,Expr)      raise to the power 
            | min(Expr,Expr)      minimum of the two arguments 
            | max(Expr,Expr)      maximum of the two arguments 
            | #(Const)            symbolic numerical constants 

Conjunctive constraints {C,C} have been made part of the syntax to control the granularity of constraint submission, which will be exploited by future versions of this software. Symbolic numerical constants are provided for compatibility only; see Monash Examples.

entailed(+Constraint)

Succeeds iff the linear Constraint is entailed by the current constraint store. This predicate does not change the state of the constraint store.

clp(q) ?- {A =< 4}, entailed(A=\=5).

{A=<4}
yes

clp(q) ?- {A =< 4}, entailed(A=\=3).

no

inf(+Expr, -Inf)
inf(+Expr, -Inf, +Vector, -Vertex)

Computes the infimum of the linear expression Expr and unifies it with Inf. If given, Vector should be a list of variables relevant to Expr, and Vertex will be unified a list of the same length as Vector containing the values for Vector, such that the infimum is produced when assigned. Failure indicates unboundedness.

sup(+Expr, -Sup)
sup(+Expr, -Sup, +Vector, -Vertex)

Computes the supremum of the linear expression Expr and unifies it with Sup. If given, Vector should be a list of variables relevant to Expr, and Vertex will be unified a list of the same length as Vector containing the values for Vector, such that the supremum is produced when assigned. Failure indicates unboundedness.

clp(q) ?- { 2*X+Y =< 16, X+2*Y =< 11,
            X+3*Y =< 15, Z = 30*X+50*Y
          }, sup(Z, Sup, [X,Y], Vertex).

Sup = 310,
Vertex = [7,2],
{Z=30*X+50*Y},
{X+1/2*Y=<8},
{X+3*Y=<15},
{X+2*Y=<11}

minimize(+Expr)

Computes the infimum of the linear expression Expr and equates it with the expression, i.e. as if defined as:

minimize(Expr) :- inf(Expr, Expr).

maximize(+Expr)

Computes the supremum of the linear expression Expr and equates it with the expression.

clp(q) ?- { 2*X+Y =< 16, X+2*Y =< 11,
            X+3*Y =< 15, Z = 30*X+50*Y
          }, maximize(Z).

X = 7,
Y = 2,
Z = 310

bb_inf(+Ints, +Expr, -Inf)

Computes the infimum of the linear expression Expr under the additional constraint that all of variables in the list Ints assume integral values at the infimum. This allows for the solution of mixed integer linear optimization problems; see MIP.

clp(q) ?- {X >= Y+Z, Y > 1, Z > 1}, bb_inf([Y,Z],X,Inf).

Inf = 4,
{Y>1},
{Z>1},
{X-Y-Z>=0}

bb_inf(+Ints, +Expr, -Inf, -Vertex, +Eps)

Computes the infimum of the linear expression Expr under the additional constraint that all of variables in the list Ints assume integral values at the infimum. Eps is a positive number between 0 and 0.5 that specifies how close a number X must be to the next integer to be considered integral: abs(round(X)-X) < Eps. The predicate bb_inf/3 uses Eps = 0.001. With clp(Q), Eps = 0 makes sense. Vertex is a list of the same length as Ints and contains the (integral) values for Ints, such that the infimum is produced when assigned. Note that this will only generate one particular solution, which is different from the situation with minimize/1, where the general solution is exhibited.

bb_inf/5 works properly for non-strict inequalities only! Disequations (=\=) and higher dimensional strict inequalities (>,<) are beyond its scope. Strict bounds on the decision variables are honored however:

clp(q) ?- {X >= Y+Z, Y > 1, Z > 1}, bb_inf([Y,Z],X,Inf,Vertex,0).

Inf = 4,
Vertex = [2,2],
{Y>1},
{Z>1},
{X-Y-Z>=0}

The limitation(s) can be addressed by:


ordering(+Spec)

Provides a means to control one aspect of the presentation of the answer constraints; see Variable Ordering.

dump(+Target, -NewVars, -CodedAnswer)

Reflects the constraints on the target variables into a term, where Target and NewVars are lists of variables of equal length and CodedAnswer is the term representation of the projection of constraints onto the target variables where the target variables are replaced by the corresponding variables from NewVars (see Turning Answers into Terms).

clp(q) ?- {A+B =< 10, A>=4},
          dump([A,B],Vs,Cs),
          dump([B],Bp,Cb).

Cb = [_A=<6],
Bp = [_A],
Cs = [_B>=4,_C+_B=<10],
Vs = [_C,_B],
{A>=4},
{A+B=<10}
The current version of dump/3 is incomplete with respect to nonlinear constraints. It only reports nonlinear constraints that are connected to the target variables. The following example has no solution. From the top-level's report we have a chance to deduce this fact, but dump/3 currently has no means to collect global constraints ...
q(X) :-
        {X>=10},
        {sin(Z)>3}.

clp(r) ?- q(X), dump([X],V,C).

C = [_A>=10.0],
V = [_A],
clpr:{3.0-sin(_B)<0.0},
{X>=10.0}

projecting_assert/1(:Clause)

If you use the dynamic data base, the clauses you assert might have constraints associated with their variables. Use this predicate instead of assert/1 in order to ensure that only the relevant and projected constraints get stored in the data base. It will transform the clause into one with plain variables and extra body goals which set up the relevant constraint when called.


Node:Unification, Next:, Previous:Solver Predicates, Up:CLPQR Interface

Unification

Equality constraints are added to the store implicitly each time variables that have been mentioned in explicit constraints are bound - either to another such variable or to a number.

clp(r) ?- {2*A+3*B=C/2}, C=10.0, A=B.

A = 1.0,
B = 1.0,
C = 10.0
Is equivalent modulo rounding errors to
clp(r) ?- {2*A+3*B=C/2, C=10, A=B}.

A = 1.0,
B = 0.9999999999999999,
C = 10.0
The shortcut bypassing the use of {}/1 is allowed and makes sense because the interpretation of this equality in Prolog and clp(R) coincides. In general, equations involving interpreted functors, +/2 in this case, must be fed to the solver explicitly:
clp(r) ?- X=3.0+1.0, X=4.0.

no

Further, variables known by clp(R) may be bound directly to floats only. Likewise, variables known by clp(Q) may be bound directly to rational numbers only; see Rationals. Failing to do so is rewarded with an exception:

clp(q) ?- {2*A+3*B=C/2}, C=10.0, A=B.
! Type error in argument 2 of = /2
! 'a rational number' expected, but 10.0 found
! goal:  _254=10.0

This is because 10.0 is not a rational constant. To make clp(Q) happy you have to say:

clp(q) ?- {2*A+3*B=C/2}, C=rat(10,1), A=B.

A = 1,
B = 1,
C = 10

If you use {}/1, you don't have to worry about such details. Alternatively, you may use the automatic expansion facility, check Syntactic Sugar.


Node:Feedback, Previous:Unification, Up:CLPQR Interface

Feedback and Bindings

What was covered so far was how the user populates the constraint store. The other direction of the information flow consists of the success and failure of the above predicates and the binding of variables to numerical values. Example:

clp(r) ?- {A-B+C=10, C=5+5}.

{A = B},
C = 10.0
The linear constraints imply C=10.0 and the solver consequently exports this binding to the Prolog world. The fact that A=B is deduced and represented by the solver but not exported as a binding. More about answer presentation in Projection.


Node:Linearity, Next:, Previous:CLPQR Interface, Up:CLPQR

Linearity and Nonlinear Residues

The clp(Q,R) system is restricted to deal with linear constraints because the decision algorithms for general nonlinear constraints are prohibitively expensive to run. If you need this functionality badly, you should look into symbolic algebra packages. Although the clp(Q,R) system cannot solve nonlinear constraints, it will collect them faithfully in the hope that through the addition of further (linear) constraints they might get simple enough to solve eventually. If an answer contains nonlinear constraints, you have to be aware of the fact that success is qualified modulo the existence of a solution to the system of residual (nonlinear) constraints:

clp(r) ?- {sin(X) = cos(X)}.

clpr:{sin(X)-cos(X)=0.0}
There are indeed infinitely many solutions to this constraint (X = 0.785398 + n*Pi), but clp(Q,R) has no direct means to find and represent them.

The systems goes through some lengths to recognize linear expressions as such. The method is based on a normal form for multivariate polynomials. In addition, some simple isolation axioms, that can be used in equality constraints, have been added. The current major limitation of the method is that full polynomial division has not been implemented. Examples:

This is an example where the isolation axioms are sufficient to determine the value of X.

clp(r) ?- {sin(cos(X)) = 1/2}.

X = 1.0197267436954502

If we change the equation into an inequation, clp(Q,R) gives up:

clp(r) ?- {sin(cos(X)) < 1/2}.

clpr:{sin(cos(X))-0.5<0.0}

The following is easy again:

clp(r) ?- {sin(X+2+2)/sin(4+X) = Y}.

Y = 1.0

And so is this:

clp(r) ?- {(X+Y)*(Y+X)/X = Y*Y/X+99}.

{Y=49.5-0.5*X}

An ancient symbol manipulation benchmark consists in rising the expression X+Y+Z+1 to the 15th power:

clp(q) ?-  {exp(X+Y+Z+1,15)=0}.
clpq:{Z^15+Z^14*15+Z^13*105+Z^12*455+Z^11*1365+Z^10*3003+...
       ... polynomial continues for a few pages ...
       =0}

Computing its roots is another story.


Node:How Nonlinear Residues are made to disappear, Next:, Previous:Linearity, Up:Linearity

How Nonlinear Residues are made to disappear

Binding variables that appear in nonlinear residues will reduce the complexity of the nonlinear expressions and eventually results in linear expressions:

clp(q) ?- {exp(X+Y+1,2) = 3*X*X+Y*Y}.

clpq:{Y*2-X^2*2+Y*X*2+X*2+1=0}

Equating X and Y collapses the expression completely and even determines the values of the two variables:

clp(q) ?- {exp(X+Y+1,2) = 3*X*X+Y*Y}, X=Y.

X = -1/4,
Y = -1/4


Node:Isolation Axioms, Previous:How Nonlinear Residues are made to disappear, Up:Linearity

Isolation Axioms

These axioms are used to rewrite equations such that the variable to be solved for is moved to the left hand side and the result of the evaluation of the right hand side can be assigned to the variable. This allows, for example, to use the exponentiation operator for the computation of roots and logarithms, see below.

A = B * C
Residuates unless B or C is ground or A and B or C are ground.
A = B / C
Residuates unless C is ground or A and B are ground.
X = min(Y,Z)
Residuates unless Y and Z are ground.
X = max(Y,Z)
Residuates unless Y and Z are ground.
X = abs(Y)
Residuates unless Y is ground.
X = pow(Y,Z), X = exp(Y,Z)
Residuates unless any pair of two of the three variables is ground. Example:
clp(r) ?- { 12=pow(2,X) }.

X = 3.5849625007211565

clp(r) ?- { 12=pow(X,3.585) }.

X = 1.9999854993443926

clp(r) ?- { X=pow(2,3.585) }.

X = 12.000311914286545

X = sin(Y)
Residuates unless X or Y is ground. Example:
clp(r) ?- { 1/2 = sin(X) }.

X = 0.5235987755982989

X = cos(Y)
Residuates unless X or Y is ground.
X = tan(Y)
Residuates unless X or Y is ground.


Node:Numerical Precision, Next:, Previous:Linearity, Up:CLPQR

Numerical Precision and Rationals

The fact that you can switch between clp(R) and clp(Q) should solve most of your numerical problems regarding precision. Within clp(Q), floating point constants will be coerced into rational numbers automatically. Transcendental functions will be approximated with rationals. The precision of the approximation is limited by the floating point precision. These two provisions allow you to switch between clp(R) and clp(Q) without having to change your programs.

What is to be kept in mind however is the fact that it may take quite big rationals to accommodate the required precision. High levels of precision are for example required if your linear program is ill-conditioned, i.e. in a full rank system the determinant of the coefficient matrix is close to zero. Another situation that may call for elevated levels of precision is when a linear optimization problem requires exceedingly many pivot steps before the optimum is reached.

If your application approximates irrational numbers, you may be out of space particularly soon.

The following program implements N steps of Newton's approximation for the square root function at point 2.

%
% from file: library('clpqr/examples/root')
%
root(N, R) :-
  root(N, 1, R).

root(0, S, R) :- !, S=R.
root(N, S, R) :-
  N1 is N-1,
  { S1 = S/2 + 1/S },
  root(N1, S1, R).

It is known that this approximation converges quadratically, which means that the number of correct digits in the decimal expansion roughly doubles with each iteration. Therefore the numerator and denominator of the rational approximation have to grow likewise:

clp(q) ?- use_module(library('clpqr/examples/root')).
clp(q) ?- root(3,R),print_decimal(R,70).
1.4142156862 7450980392 1568627450 9803921568 6274509803 9215686274
5098039215

R = 577/408

clp(q) ?- root(4,R),print_decimal(R,70).
1.4142135623 7468991062 6295578890 1349101165 5962211574 4044584905
0192000543

R = 665857/470832

clp(q) ?- root(5,R),print_decimal(R,70).
1.4142135623 7309504880 1689623502 5302436149 8192577619 7428498289
4986231958

R = 886731088897/627013566048

clp(q) ?- root(6,R),print_decimal(R,70).
1.4142135623 7309504880 1688724209 6980785696 7187537723 4001561013
1331132652

R = 1572584048032918633353217/1111984844349868137938112

clp(q) ?- root(7,R),print_decimal(R,70).
1.4142135623 7309504880 1688724209 6980785696 7187537694 8073176679
7379907324

R = 4946041176255201878775086487573351061418968498177 /
    3497379255757941172020851852070562919437964212608

Iterating for 8 steps produces no further change in the first 70 decimal digits of sqrt(2). After 15 steps the approximating rational number has a numerator and a denominator with 12543 digits each, and the next step runs out of memory.

Another irrational number that is easily computed is e. The following program implements an alternating series for 1/e, where the absolute value of last term is an upper bound on the error.

%
% from file: library('clpqr/examples/root')
%
e(N, E) :-
  { Err =:= exp(10,-(N+2)), Half =:= 1/2 },
  inv_e_series(Half, Half, 3, Err, Inv_E),
  { E =:= 1/Inv_E }.

inv_e_series(Term, S0, _, Err, Sum) :-
  { abs(Term) =< Err }, !,
  S0 = Sum.
inv_e_series(Term, S0, N, Err, Sum) :-
  N1 is N+1,
  { Term1 =:= -Term/N, S1 =:= Term1+S0 },
  inv_e_series(Term1, S1, N1, Err, Sum).

The computation of the rational number E that approximates e up to at least 1000 digits in its decimal expansion requires the evaluation of 450 terms of the series, i.e. 450 calls of inv_e_series/5.

clp(q) ?- e(1000,E).

E = 7149056228932760213666809592072842334290744221392610955845565494
    3708750229467761730471738895197792271346693089326102132000338192
    0131874187833985420922688804220167840319199699494193852403223700
    5853832741544191628747052136402176941963825543565900589161585723
    4023097417605004829991929283045372355639145644588174733401360176
    9953973706537274133283614740902771561159913069917833820285608440
    3104966899999651928637634656418969027076699082888742481392304807
    9484725489080844360397606199771786024695620205344042765860581379
    3538290451208322129898069978107971226873160872046731879753034549
    3130492167474809196348846916421782850086985668680640425192038155
    4902863298351349469211627292865440876581064873866786120098602898
    8799130098877372097360065934827751120659213470528793143805903554
    7928682131082164366007016698761961066948371407368962539467994627
    1374858249110795976398595034606994740186040425117101588480000000
    0000000000000000000000000000000000000000000000000000000000000000
    00000000000000000000000000000000000000
    /
    2629990810403002651095959155503002285441272170673105334466808931
    6863103901346024240326549035084528682487048064823380723787110941
    6809235187356318780972302796570251102928552003708556939314795678
    1978390674393498540663747334079841518303636625888963910391440709
    0887345797303470959207883316838346973393937778363411195624313553
    8835644822353659840936818391050630360633734935381528275392050975
    7271468992840907541350345459011192466892177866882264242860412188
    0652112744642450404625763019639086944558899249788084559753723892
    1643188991444945360726899532023542969572584363761073528841147012
    2634218045463494055807073778490814692996517359952229262198396182
    1838930043528583109973872348193806830382584040536394640895148751
    0766256738740729894909630785260101721285704616818889741995949666
    6303289703199393801976334974240815397920213059799071915067856758
    6716458821062645562512745336709063396510021681900076680696945309
    3660590933279867736747926648678738515702777431353845466199680991
    73361873421152165477774911660108200059

The decimal expansion itself looks like this:

clp(q) ?- e(1000, E), print_decimal(E, 1000).
2.
7182818284 5904523536 0287471352 6624977572 4709369995 9574966967
6277240766 3035354759 4571382178 5251664274 2746639193 2003059921
8174135966 2904357290 0334295260 5956307381 3232862794 3490763233
8298807531 9525101901 1573834187 9307021540 8914993488 4167509244
7614606680 8226480016 8477411853 7423454424 3710753907 7744992069
5517027618 3860626133 1384583000 7520449338 2656029760 6737113200
7093287091 2744374704 7230696977 2093101416 9283681902 5515108657
4637721112 5238978442 5056953696 7707854499 6996794686 4454905987
9316368892 3009879312 7736178215 4249992295 7635148220 8269895193
6680331825 2886939849 6465105820 9392398294 8879332036 2509443117
3012381970 6841614039 7019837679 3206832823 7646480429 5311802328
7825098194 5581530175 6717361332 0698112509 9618188159 3041690351
5988885193 4580727386 6738589422 8792284998 9208680582 5749279610
4841984443 6346324496 8487560233 6248270419 7862320900 2160990235
3043699418 4914631409 3431738143 6405462531 5209618369 0888707016
7683964243 7814059271 4563549061 3031072085 1038375051 0115747704
1718986106 8739696552 1267154688 9570350354


Node:Projection, Next:, Previous:Numerical Precision, Up:CLPQR

Projection and Redundancy Elimination

Once a derivation succeeds, the Prolog system presents the bindings for the variables in the query. In a CLP system, the set of answer constraints is presented in analogy. A complication in the CLP context are variables and associated constraints that were not mentioned in the query. A motivating example is the familiar mortgage relation:

%
% from file: library('clpqr/examples/mg')
%
mg(P,T,I,B,MP):-
  {
     T = 1,
     B + MP = P * (1 + I)
  }.
mg(P,T,I,B,MP):-
  {
     T > 1,
     P1 = P * (1 + I) - MP,
     T1 = T - 1
  },
  mg(P1, T1, I, B, MP).
A sample query yields:
clp(r) ?- use_module(library('clpqr/examples/mg')).
clp(r) ?- mg(P,12,0.01,B,Mp).

{B=1.1268250301319698*P-12.682503013196973*Mp}
Without projection of the answer constraints onto the query variables we would observe the following interaction:
clp(r) ?- mg(P,12,0.01,B,Mp).

{B=12.682503013196973*_A-11.682503013196971*P},
{Mp= -(_A)+1.01*P},
{_B=2.01*_A-1.01*P},
{_C=3.0301*_A-2.0301*P},
{_D=4.060401000000001*_A-3.0604009999999997*P},
{_E=5.101005010000001*_A-4.10100501*P},
{_F=6.152015060100001*_A-5.152015060099999*P},
{_G=7.213535210701001*_A-6.213535210700999*P},
{_H=8.285670562808011*_A-7.285670562808009*P},
{_I=9.368527268436091*_A-8.36852726843609*P},
{_J=10.462212541120453*_A-9.46221254112045*P},
{_K=11.566834666531657*_A-10.566834666531655*P}
The variables _A ... _K are not part of the query, they originate from the mortgage program proper. Although the latter answer is equivalent to the former in terms of linear algebra, most users would prefer the former.


Node:Variable Ordering, Next:, Previous:Projection, Up:Projection

Variable Ordering

In general, there are many ways to express the same linear relationship between variables. clp(Q,R) does not care to distinguish between them, but the user might. The predicate ordering(+Spec) gives you some control over the variable ordering. Suppose that instead of B, you want Mp to be the defined variable:

clp(r) ?- mg(P,12,0.01,B,Mp).

{B=1.1268250301319698*P-12.682503013196973*Mp}
This is achieved with:
clp(r) ?-  mg(P,12,0.01,B,Mp), ordering([Mp]).

{Mp= -0.0788487886783417*B+0.08884878867834171*P}
One could go one step further and require P to appear before (to the left of) B in a addition:
clp(r) ?- mg(P,12,0.01,B,Mp), ordering([Mp,P]).

{Mp=0.08884878867834171*P-0.0788487886783417*B}

Spec in ordering(+Spec) is either a list of variables with the intended ordering, or of the form A<B. The latter form means that A goes to the left of B. In fact, ordering([A,B,C,D]) is shorthand for:

ordering(A < B), ordering(A < C), ordering(A < D),
ordering(B < C), ordering(B < D),
ordering(C < D)

The ordering specification only affects the final presentation of the constraints. For all other operations of clp(Q,R), the ordering is immaterial. Note that ordering/1 acts like a constraint: you can put it anywhere in the computation, and you can submit multiple specifications.

clp(r) ?- ordering(B < Mp), mg(P,12,0.01,B,Mp).

{B= -12.682503013196973*Mp+1.1268250301319698*P}

yes
clp(r) ?- ordering(B < Mp), mg(P,12,0.01,B,Mp), ordering(P < Mp).

{P=0.8874492252651537*B+11.255077473484631*Mp}


Node:Turning Answers into Terms, Next:, Previous:Variable Ordering, Up:Projection

Turning Answers into Terms

In meta-programming applications one needs to get a grip on the results computed by the clp(Q,R) solver. You can use the predicates dump/3 and/or call_residue/2 for that purpose:

clp(r) ?- {2*A+B+C=10,C-D=E,A<10}, dump([A,B,C,D,E],[a,b,c,d,e],Constraints).

Constraints = [e<10.0,a=10.0-c-d-2.0*e,b=c+d],
{C=10.0-2.0*A-B},
{E=10.0-2.0*A-B-D},
{A<10.0}
clp(r) ?- call_residue({2*A+B+C=10,C-D=E,A<10}, Constraints).

Constraints = [
               [A]-{A<10.0},
               [B]-{B=10.0-2.0*A-C},
               [D]-{D=C-E}
              ]


Node:Projecting Inequalities, Previous:Turning Answers into Terms, Up:Projection

Projecting Inequalities

As soon as linear inequations are involved, projection gets more demanding complexity wise. The current clp(Q,R) version uses a Fourier-Motzkin algorithm for the projection of linear inequalities. The choice of a suitable algorithm is somewhat dependent on the number of variables to be eliminated, the total number of variables, and other factors. It is quite easy to produce problems of moderate size where the elimination step takes some time. For example, when the dimension of the projection is 1, you might be better off computing the supremum and the infimum of the remaining variable instead of eliminating n-1 variables via implicit projection.

In order to make answers as concise as possible, redundant constraints are removed by the system as well. In the following set of inequalities, half of them are redundant.

%
% from file: library('clpqr/examples/eliminat')
%
example(2, [X0,X1,X2,X3,X4]) :-
  {
       +87*X0  +52*X1  +27*X2  -54*X3  +56*X4 =<  -93,
       +33*X0  -10*X1  +61*X2  -28*X3  -29*X4 =<   63,
       -68*X0   +8*X1  +35*X2  +68*X3  +35*X4 =<  -85,
       +90*X0  +60*X1  -76*X2  -53*X3  +24*X4 =<  -68,
       -95*X0  -10*X1  +64*X2  +76*X3  -24*X4 =<   33,
       +43*X0  -22*X1  +67*X2  -68*X3  -92*X4 =<  -97,
       +39*X0   +7*X1  +62*X2  +54*X3  -26*X4 =<  -27,
       +48*X0  -13*X1   +7*X2  -61*X3  -59*X4 =<   -2,
       +49*X0  -23*X1  -31*X2  -76*X3  +27*X4 =<    3,
       -50*X0  +58*X1   -1*X2  +57*X3  +20*X4 =<    6,
       -13*X0  -63*X1  +81*X2   -3*X3  +70*X4 =<   64,
       +20*X0  +67*X1  -23*X2  -41*X3  -66*X4 =<   52,
       -81*X0  -44*X1  +19*X2  -22*X3  -73*X4 =<  -17,
       -43*X0   -9*X1  +14*X2  +27*X3  +40*X4 =<   39,
       +16*X0  +83*X1  +89*X2  +25*X3  +55*X4 =<   36,
        +2*X0  +40*X1  +65*X2  +59*X3  -32*X4 =<   13,
       -65*X0  -11*X1  +10*X2  -13*X3  +91*X4 =<   49,
       +93*X0  -73*X1  +91*X2   -1*X3  +23*X4 =<  -87
  }.
Consequently, the answer consists of the system of nine non-redundant inequalities only:
clp(q) ?- use_module(library('clpqr/examples/elimination')).
clp(q) ?- example(2, [X0,X1,X2,X3,X4]).

{X0-2/17*X1-35/68*X2-X3-35/68*X4>=5/4},
{X0-73/93*X1+91/93*X2-1/93*X3+23/93*X4=<-29/31},
{X0-29/25*X1+1/50*X2-57/50*X3-2/5*X4>=-3/25},
{X0+7/39*X1+62/39*X2+18/13*X3-2/3*X4=<-9/13},
{X0+2/19*X1-64/95*X2-4/5*X3+24/95*X4>=-33/95},
{X0+2/3*X1-38/45*X2-53/90*X3+4/15*X4=<-34/45},
{X0-23/49*X1-31/49*X2-76/49*X3+27/49*X4=<3/49},
{X0+44/81*X1-19/81*X2+22/81*X3+73/81*X4>=17/81},
{X0+9/43*X1-14/43*X2-27/43*X3-40/43*X4>=-39/43}

The projection (the shadow) of this polyhedral set into the X0,X1 space can be computed via the implicit elimination of non-query variables:

clp(q) ?- example(2, [X0,X1|_]).

{X0+2619277/17854273*X1>=-851123/17854273},
{X0+6429953/16575801*X1=<-12749681/16575801},
{X0+19130/1213083*X1>=795400/404361},
{X0-1251619/3956679*X1>=21101146/3956679},
{X0+601502/4257189*X1>=220850/473021}

Projection is quite a powerful concept that leads to surprisingly terse executable specifications of nontrivial problems like the computation of the convex hull from a set of points in an n-dimensional space: Given the program

%
% from file: library('clpqr/examples/elimination')
%
conv_hull(Points, Xs) :-
  lin_comb(Points, Lambdas, Zero, Xs),
  zero(Zero),
  polytope(Lambdas).

polytope(Xs) :-
  positive_sum(Xs, 1).

  positive_sum([], Z) :- {Z=0}.
  positive_sum([X|Xs], SumX) :-
    { X >= 0, SumX = X+Sum },
    positive_sum(Xs, Sum).

zero([]).
zero([Z|Zs]) :- {Z=0}, zero(Zs).

lin_comb([],        [],     S1, S1).
lin_comb([Ps|Rest], [K|Ks], S1, S3) :-
  lin_comb_r(Ps, K, S1, S2),
  lin_comb(Rest, Ks, S2, S3).

  lin_comb_r([],     _, [],     []).
  lin_comb_r([P|Ps], K, [S|Ss], [Kps|Ss1]) :-
    { Kps = K*P+S },
    lin_comb_r(Ps, K, Ss, Ss1).
we can post the following query:
clp(q) ?- conv_hull([ [1,1], [2,0], [3,0], [1,2], [2,2] ], [X,Y]).

{Y=<2},
{X+1/2*Y=<3},
{X>=1},
{Y>=0},
{X+Y>=2}
This answer is easily verified graphically:
       |
     2 -    *    *
       |
       |
     1 -    *
       |
       |
     0 -----|----*----*----
            1    2    3
The convex hull program directly corresponds to the mathematical definition of the convex hull. What does the trick in operational terms is the implicit elimination of the Lambdas from the program formulation. Please note that this program does not limit the number of points or the dimension of the space they are from. Please note further that quantifier elimination is a computationally expensive operation and therefore this program is only useful as a benchmark for the projector and not so for the intended purpose.


Node:Why Disequations, Next:, Previous:Projection, Up:CLPQR

Why Disequations

A beautiful example of disequations at work is due to [Colmerauer 90]. It addresses the task of tiling a rectangle with squares of all-different, a priori unknown sizes. Here is a translation of the original Prolog-III program to clp(Q,R):

%
% from file: library('clpqr/examples/squares')
%
filled_rectangle(A, C) :-
  { A >= 1 },
  distinct_squares(C),
  filled_zone([-1,A,1], _, C, []).

distinct_squares([]).
distinct_squares([B|C]) :-
  { B > 0 },
  outof(C, B),
  distinct_squares(C).

outof([],     _).
outof([B1|C], B) :-
  { B =\= B1 },       % *** note disequation ***
  outof(C, B).

filled_zone([V|L], [W|L], C0, C0) :-
  { V=W,V >= 0 }.
filled_zone([V|L], L3, [B|C], C2) :-
  { V < 0 },
  placed_square(B, L, L1),
  filled_zone(L1, L2, C, C1),
  { Vb=V+B },
  filled_zone([Vb,B|L2], L3, C1, C2).

placed_square(B, [H,H0,H1|L], L1) :-
  { B > H, H0=0, H2=H+H1 },
  placed_square(B, [H2|L], L1).
placed_square(B, [B,V|L], [X|L]) :-
  { X=V-B }.
placed_square(B, [H|L], [X,Y|L]) :-
  { B < H, X= -B, Y=H-B }.
There are no tilings with less than nine squares except the trivial one where the rectangle equals the only square. There are eight solutions for nine squares. Six further solutions are rotations of the first two.
clp(q) ?- use_module(library('clpqr/examples/squares')).
clp(q) ?- filled_rectangle(A, Squares).

A = 1,
Squares = [1] ? ;

A = 33/32,
Squares = [15/32,9/16,1/4,7/32,1/8,7/16,1/32,5/16,9/32] ? ;

A = 69/61,
Squares = [33/61,36/61,28/61,5/61,2/61,9/61,25/61,7/61,16/61]

Depending on your hardware, the above query may take a few minutes. Supplying the knowledge about the minimal number of squares beforehand cuts the computation time by a factor of roughly four:

clp(q) ?- length(Squares, 9), filled_rectangle(A, Squares).

A = 33/32,
Squares = [15/32,9/16,1/4,7/32,1/8,7/16,1/32,5/16,9/32] ? ;

A = 69/61,
Squares = [33/61,36/61,28/61,5/61,2/61,9/61,25/61,7/61,16/61]


Node:Syntactic Sugar, Next:, Previous:Why Disequations, Up:CLPQR

Syntactic Sugar

There is a package that transforms programs and queries from a eval-quote variant of clp(Q,R) into corresponding programs and queries in a quote-eval variant. Before you use it, you need to know that in an eval-quote language, all symbols are interpreted unless explicitly quoted. This means that interpreted terms cannot be manipulated syntactically directly. Meta-programming in a CLP context by definition manipulates interpreted terms, therefore you need quote/1 (just as in LISP) and some means to put syntactical terms back to their interpreted life: {}/1.

In a quote-eval language, meta-programming is (pragmatically) simpler because everything is implicitly quoted until explicitly evaluated. On the other hand, now object programming suffers from the dual inconvenience.

We chose to make our version of clp(Q,R) of the quote-eval type because this matches the intended use of the already existing boolean solver of SICStus. In order to keep the users of the eval-quote variant happy, we provide a source transformation package. It is activated via:

| ?- use_module(library('clpqr/expand')).
Loading the package puts you in a mode where the arithmetic functors like +/2, */2 and all numbers (functors of arity 0) are interpreted semantically.
clp(r) ?- 2+2=X.

X = 4.0
The package works by purifying programs and queries in the sense that all references to interpreted terms are made explicit. The above query is expanded prior to evaluation into:
{2.0+2.0=X}
The same mechanism applies when interpreted terms are nested deeper:
some_predicate(10, f(A+B/2), 2*cos(A))
Expands into:
{Xc=2.0*cos(A)},
{Xb=A+B/2},
{Xa=10.0},
some_predicate(Xa, f(Xb), Xc)
This process also applies when files are consulted or compiled. In fact, this is the only situation where expansion can be applied with relative safety. To see this, consider what happens when the top-level evaluates the expansion, namely some calls to the clp(Q,R) solver, followed by the call of the purified query. As we learned in Feedback, the solver may bind variables, which produces a goal with interpreted terms in it (numbers), which leads to another stage of expansion, and so on.

We recommend that you only turn on expansion temporarily while consulting or compiling files needing expansion with expand/0 and noexpand/0.


Node:Monash Examples, Previous:Syntactic Sugar, Up:Syntactic Sugar

Monash Examples

This collection of examples has been distributed with the Monash University Version of clp(R) [Heintze et al. 87], and its inclusion into this distribution was kindly permitted by Roland Yap.

In order to execute the examples, a small compatibility package has to be loaded first:

clp(r) ?- use_module(library('clpqr/monash')).
Then, assuming you are using clp(R):
clp(r) ?- expand, [library('clpqr/examples/monash/rkf45')],
          noexpand.

clp(r) ?- go.
Point    0.00000 :    0.75000    0.00000
Point    0.50000 :    0.61969    0.47793
Point    1.00000 :    0.29417    0.81233
Point    1.50000 :   -0.10556    0.95809
Point    2.00000 :   -0.49076    0.93977
Point    2.50000 :   -0.81440    0.79929
Point    3.00000 :   -1.05440    0.57522

Iteration finished
------------------
 439  derivative evaluations


Node:Compatibility Notes, Previous:Monash Examples, Up:Monash Examples

Compatibility Notes

The Monash examples have been written for clp(R). Nevertheless, all but rkf45 complete nicely in clp(Q). With rkf45, clp(Q) runs out of memory. This is an instance of the problem discussed in Numerical Precision.

The Monash University clp(R) interpreter features a dump/n predicate. It is used to print the target variables according to the given ordering. Within this version of clp(Q,R), the corresponding functionality is provided via ordering/1. The difference is that ordering/1 does only specify the ordering of the variables and no printing is performed. We think Prolog has enough predicates to perform output already. You can still run the examples referring to dump/n from the Prolog top-level:

clp(r) ?- expand, [library('clpqr/examples/monash/mortgage')], noexpand.

% go2
%
clp(r) ?- mg(P,120,0.01,0,MP), dump([P,MP]).

{P=69.7005220313972*MP}

% go3
%
clp(r) ?- mg(P,120,0.01,B,MP), dump([P,B,MP]).

{P=0.30299477968602706*B+69.7005220313972*MP}

% go4
%
clp(r) ?- mg(999, 3, Int, 0, 400), dump.

clpr:{_B-_B*Int+_A+400.0=0.0},
clpr:{_A-_A*Int+400.0=0.0},
{_B=599.0+999.0*Int}


Node:MIP, Next:, Previous:Syntactic Sugar, Up:CLPQR

A Mixed Integer Linear Optimization Example

The predicates bb_inf/3, bb_inf/5 implement a simple Branch and Bound search algorithm for Mixed Integer Linear (MIP) Optimization examples. Serious MIP is not trivial. The implementation library('clpqr/bb.pl') is to be understood as a starting point for more ambitious users who need control over branching, or who want to add cutting planes, for example.

Anyway, here is a small problem from miplib, a collection of MIP models, housed at Rice University:

NAME:         flugpl
ROWS:         18
COLUMNS:      18
INTEGER:      11
NONZERO:      46
BEST SOLN:    1201500 (opt)
LP SOLN:      1167185.73
SOURCE:       Harvey M. Wagner
              John W. Gregory (Cray Research)
              E. Andrew Boyd (Rice University)
APPLICATION:  airline model
COMMENTS:     no integer variables are binary
%
% from file: library('clpqr/examples/mip')
%
example(flugpl, Obj, Vs, Ints, []) :-
  Vs = [ Anm1,Anm2,Anm3,Anm4,Anm5,Anm6,
         Stm1,Stm2,Stm3,Stm4,Stm5,Stm6,
         UE1,UE2,UE3,UE4,UE5,UE6],
  Ints = [Stm6, Stm5, Stm4, Stm3, Stm2,
          Anm6, Anm5, Anm4, Anm3, Anm2, Anm1],

  Obj =    2700*Stm1 + 1500*Anm1 + 30*UE1
         + 2700*Stm2 + 1500*Anm2 + 30*UE2
         + 2700*Stm3 + 1500*Anm3 + 30*UE3
         + 2700*Stm4 + 1500*Anm4 + 30*UE4
         + 2700*Stm5 + 1500*Anm5 + 30*UE5
         + 2700*Stm6 + 1500*Anm6 + 30*UE6,

  allpos(Vs),
  {  Stm1 = 60, 0.9*Stm1 +1*Anm1 -1*Stm2 = 0,
     0.9*Stm2 +1*Anm2 -1*Stm3 = 0, 0.9*Stm3 +1*Anm3 -1*Stm4 = 0,
     0.9*Stm4 +1*Anm4 -1*Stm5 = 0, 0.9*Stm5 +1*Anm5 -1*Stm6 = 0,
     150*Stm1 -100*Anm1 +1*UE1 >= 8000,
     150*Stm2 -100*Anm2 +1*UE2 >= 9000,
     150*Stm3 -100*Anm3 +1*UE3 >= 8000,
     150*Stm4 -100*Anm4 +1*UE4 >= 10000,
     150*Stm5 -100*Anm5 +1*UE5 >= 9000,
     150*Stm6 -100*Anm6 +1*UE6 >= 12000,
     -20*Stm1 +1*UE1 =< 0, -20*Stm2 +1*UE2 =< 0, -20*Stm3 +1*UE3 =< 0,
     -20*Stm4 +1*UE4 =< 0, -20*Stm5 +1*UE5 =< 0, -20*Stm6 +1*UE6 =< 0,
     Anm1 =< 18, 57 =< Stm2, Stm2 =< 75, Anm2 =< 18,
     57 =< Stm3, Stm3 =< 75, Anm3 =< 18, 57 =< Stm4,
     Stm4 =< 75, Anm4 =< 18, 57 =< Stm5, Stm5 =< 75,
     Anm5 =< 18, 57 =< Stm6, Stm6 =< 75, Anm6 =< 18
   }.

  allpos([]).
  allpos([X|Xs]) :- {X >= 0}, allpos(Xs).

We can first check whether the relaxed problem has indeed the quoted infimum:

clp(r) ?- example(flugpl, Obj, _, _, _), inf(Obj, Inf).

Inf = 1167185.7255923203

Computing the infimum under the additional constraints that Stm6, Stm5, Stm4, Stm3, Stm2, Anm6, Anm5, Anm4, Anm3, Anm2, Anm1 assume integer values at the infimum is computationally harder, but the query does not change much:

clp(r) ?- example(flugpl, Obj, _, Ints, _),
          bb_inf(Ints, Obj, Inf, Vertex, 0.001).

Inf = 1201500.0000000005,
Vertex = [75.0,70.0,70.0,60.0,60.0,0.0,12.0,7.0,16.0,6.0,6.0]


Node:Implementation Architecture, Previous:MIP, Up:CLPQR

Implementation Architecture

The system consists roughly of the following components:


Node:Fragments and Bits, Next:, Previous:Implementation Architecture, Up:Implementation Architecture

Fragments and Bits


Node:Rationals, Next:, Previous:Fragments and Bits, Up:Fragments and Bits

Rationals

The internal data structure for rational numbers is rat(Num,Den). Den is always positive, i.e. the sign of the rational number is the sign of Num. Further, Num and Den are relative prime. Note that integer N looks like rat(N,1) in this representation. You can control printing of terms with portray/1.


Node:Partial Evaluation, Next:, Previous:Rationals, Up:Fragments and Bits

Partial Evaluation, Compilation

Once one has a working solver, it is obvious and attractive to run the constraints in a clause definition at read time or compile time and proceed with the answer constraints in place of the original constraints. This gets you constant folding and in fact the full algebraic power of the solver applied to the avoidance of computations at runtime. The mechanism to realize this idea is to use dump/3, call_residue/2 for the expansion of {}/1, via hook predicate user:goal_expansion/3).


Node:Asserting with Constraints, Previous:Partial Evaluation, Up:Fragments and Bits

Asserting with Constraints

If you use the dynamic data base, the clauses you assert might have constraints associated with their variables. You should use projecting_assert/1 instead of assert/1 in order to ensure that only the relevant and projected constraints get stored in the data base.

| ?- {A+B=<33}, projecting_assert(test(A,B)).

{A+B=<33} ?

yes
| ?- listing(test).
test(A, B) :-
        {A+B=<rat(33,1)}.


yes
| ?- test(A,B).

{A+B=<33} ?


Node:Bugs, Previous:Fragments and Bits, Up:Implementation Architecture

Bugs

Please send bug reports to <christian@ai.univie.ac.at>.


Node:CLPFD, Next:, Previous:CLPQR, Up:Top

Constraint Logic Programming over Finite Domains


Node:CLPFD Intro, Next:, Previous:CLPFD, Up:CLPFD

Introduction

The clp(FD) solver described in this chapter is an instance of the general Constraint Logic Programming scheme introduced in [Jaffar & Michaylov 87]. This constraint domain is particularly useful for modeling discrete optimization and verification problems such as scheduling, planning, packing, timetabling etc. The treatise [Van Hentenryck 89] is an excellent exposition of the theoretical and practical framework behind constraint solving in finite domains, and summarizes the work up to 1989.

This solver has the following highlights:

This library fully supports multiple SICStus run-times in a process.

The rest of this chapter is organized as follows: How to load the solver and how to write simple programs is explained in CLPFD Interface. A description of all constraints that the solver provides is contained in Available Constraints. The predicates for searching for solution are documented in Enumeration Predicates. The predicates for getting execution statistics are documented in Statistics Predicates. A few example programs are given in Example Programs. Finally, Syntax Summary contains syntax rules for all expressions.

The following sections discuss advanced features and are probably only relevant to experienced users: How to control the amount of information presented in answers to queries is explained in Answer Constraints. The solver's execution mechanism and primitives are described in The Constraint System. How to add new global constraints via a programming interface is described in Defining Global Constraints. How to define new primitive constraints with indexicals is described in Defining Primitive Constraints.


Node:Referencing CLPFD, Next:, Previous:CLPFD Intro, Up:CLPFD Intro

Referencing this Software

When referring to this implementation of clp(FD) in publications, please use the following reference:

Carlsson M., Ottosson G., Carlson B. "An Open-Ended Finite Domain Constraint Solver" Proc. Programming Languages: Implementations, Logics, and Programs, 1997.


Node:Acknowledgments CLPFD, Previous:Referencing CLPFD, Up:CLPFD Intro

Acknowledgments

The first version of this solver was written as part of Key Hyckenberg's MSc thesis in 1995, with contributions from Greger Ottosson at the Computing Science Department, Uppsala University. The code was later rewritten by Mats Carlsson. Peter Szeredi contributed material for this manual chapter.

The development of this software was supported by the Swedish National Board for Technical and Industrial Development (NUTEK) under the auspices of Advanced Software Technology (ASTEC) Center of Competence at Uppsala University.

We include a collection of examples, some of which have been distributed with the INRIA implementation of clp(FD) [Diaz & Codognet 93].


Node:CLPFD Interface, Next:, Previous:CLPFD Intro, Up:CLPFD

Solver Interface

The solver is available as a library module and can be loaded with a query

:- use_module(library(clpfd)).

The solver contains predicates for checking the consistency and entailment of finite domain constraints, as well as solving for solution values for your problem variables.

In the context of this constraint solver, a finite domain is a subset of small integers, and a finite domain constraint denotes a relation over a tuple of small integers. Hence, only small integers and unbound variables are allowed in finite domain constraints.

All domain variables, i.e. variables that occur as arguments to finite domain constraints get associated with a finite domain, either explicitly declared by the program, or implicitly imposed by the constraint solver. Temporarily, the domain of a variable may actually be infinite, if it does not have a finite lower or upper bound.

The domain of all variables gets narrower and narrower as more constraints are added. If a domain becomes empty, the accumulated constraints are unsatisfiable, and the current computation branch fails. At the end of a successful computation, all domains have usually become singletons, i.e. the domain variables have become assigned.

The domains do not become singletons automatically. Usually, it takes some amount of search to find an assignment that satisfies all constraints. It is the programmer's responsibility to do so. If some domain variables are left unassigned in a computation, the garbage collector will preserve all constraint data that is attached to them.

NOTE: the behavior of the predicates assert/1, findall/3, raise_exception/1 and friends is undefined on non-ground terms containing domain variables. If you need to apply these operations to a term containing domain variables, fd_copy_term/3 may be used to decompose the term into a template and a symbolic representation of the relevant constraints.

The heart of the constraint solver is a scheduler for indexicals [Van Hentenryck et al. 92] and global constraints. Both entities act as coroutines performing incremental constraint solving or entailment checking. They wake up by changes in the domains of its arguments. All constraints provided by this package are implemented as indexicals or global constraints. New constraints can be defined by the user.

Indexicals are reactive functional rules that take part in the solver's basic constraint solving algorithm, whereas each global constraint is associated with its particular constraint solving algorithm. The solver maintains two scheduling queues, giving priority to the queue of indexicals.

The feasibility of integrating the indexical approach with a Prolog based on the WAM was clearly demonstrated by Diaz's clp(FD) implementation [Diaz & Codognet 93], one of the fastest finite domains solvers around.


Node:Posting Constraints, Next:, Previous:CLPFD Interface, Up:CLPFD Interface

Posting Constraints

A constraint is called as any other Prolog predicate. When called, the constraint is posted to the store. For example:

| ?- X in 1..5, Y in 2..8, X+Y #= T.

X in 1..5,
Y in 2..8,
T in 3..13 ?

yes
| ?- X in 1..5, T in 3..13, X+Y #= T.

X in 1..5,
T in 3..13,
Y in -2..12 ?

yes

Note that the answer constraint shows the domains of nonground query variables, but not any constraints that may be attached to them.


Node:A Constraint Satisfaction Problem, Next:, Previous:Posting Constraints, Up:CLPFD Interface

A Constraint Satisfaction Problem

Constraint satisfaction problems (CSPs) are a major class of problems for which this solver is ideally suited. In a CSP, the goal is to pick values from pre-defined domains for certain variables so that the given constraints on the variables are all satisfied.

As a simple CSP example, let us consider the Send More Money puzzle. In this problem, the variables are the letters S, E, N, D, M, O, R, and Y. Each letter represents a digit between 0 and 9. The problem is to assign a value to each digit, such that SEND + MORE equals MONEY.

A program which solves the puzzle is given below. The program contains the typical three steps of a clp(FD) program:

  1. declare the domains of the variables
  2. post the problem constraints
  3. look for a feasible solution via backtrack search, or look for an optimal solution via branch-and-bound search

Sometimes, an extra step precedes the search for a solution: the posting of surrogate constraints to break symmetries or to otherwise help prune the search space. No surrogate constraints are used in this example.

The domains of this puzzle are stated via the domain/3 goal and by requiring that S and M be greater than zero. The two problem constraint of this puzzle are the equation (sum/8) and the constraint that all letters take distinct values (all_different/1). Finally, the backtrack search is performed by labeling/2. Different search strategies can be encoded in the Type parameter. In the example query, the default search strategy is used (select the leftmost variable, try values in ascending order).

:- use_module(library(clpfd)).

mm([S,E,N,D,M,O,R,Y], Type) :-
     domain([S,E,N,D,M,O,R,Y], 0, 9),      % step 1
     S#>0, M#>0,
     all_different([S,E,N,D,M,O,R,Y]),     % step 2
     sum(S,E,N,D,M,O,R,Y),
     labeling(Type, [S,E,N,D,M,O,R,Y]).    % step 3

sum(S, E, N, D, M, O, R, Y) :-
                  1000*S + 100*E + 10*N + D
     +            1000*M + 100*O + 10*R + E
     #= 10000*M + 1000*O + 100*N + 10*E + Y.

| ?- mm([S,E,N,D,M,O,R,Y], []).

D = 7,
E = 5,
M = 1,
N = 6,
O = 0,
R = 8,
S = 9,
Y = 2 ?


Node:Reified Constraints, Previous:A Constraint Satisfaction Problem, Up:CLPFD Interface

Reified Constraints

Instead of merely posting constraints it is often useful to reflect its truth value into a 0/1-variable B, so that:

This mechanism is known as reification. Several frequently used operations can be defined in terms of reified constraints, such as blocking implication [Saraswat 90] and the cardinality operator [Van Hentenryck & Deville 91], to name a few. A reified constraint is written:

| ?- Constraint #<=> B.

where Constraint is reifiable. As an example of a constraint that uses reification, consider exactly(X,L,N) which is true if X occurs exactly N times in the list L. It can be defined thus:

exactly(_, [], 0).
exactly(X, [Y|L], N) :-
    X #= Y #<=> B,
    N #= M+B,
    exactly(X, L, M).


Node:Available Constraints, Next:, Previous:CLPFD Interface, Up:CLPFD

Available Constraints

This section describes the classes of constraints that can be used with this solver.


Node:Arithmetic Constraints, Next:, Previous:Available Constraints, Up:Available Constraints

Arithmetic Constraints

?Expr RelOp ?Expr

defines an arithmetic constraint. The syntax for Expr and RelOp is defined by a grammar (see Syntax of Arithmetic Expressions). Note that the expressions are not restricted to being linear. Constraints over non-linear expressions, however, will usually yield less constraint propagation than constraints over linear expressions. In particular, the expressions X / Y and X mode Y will block until Y is ground.

Arithmetic constraints can be reified as e.g.

| ?- X in 1..2, Y in 3..5, X#=<Y #<=> B.

B = 1,
X in 1..2,
Y in 3..5 ?

Linear arithmetic constraints maintain (at least) interval-consistency and their reified versions detect (at least) interval-entailment and -disentailment; see The Constraint System.

The following constraints are among the library constraints that general arithmetic constraints compile to. They express a relation between a sum or a scalar product and a value, using a dedicated algorithm that avoids creating any temporary variables holding intermediate values. If you are computing a sum or a scalar product, it can be much more efficient to compute lists of coefficients and variables and post a single sum or scalar product constraint than to post a sequence of elementary constraints.

sum(+Xs, +RelOp, ?Value)

where Xs is a list of integers or domain variables, RelOp is a relational symbol as above, and Value is an integer or a domain variable. True if Xs RelOp Value. Cannot be reified.

scalar_product(+Coeffs, +Xs, +RelOp, ?Value)

where Coeffs is a list of length n of integers, Xs is a list of length n of integers or domain variables, RelOp is a relational symbol as above, and Value is an integer or a domain variable. True if Coeffs*Xs RelOp Value. Cannot be reified.

The following constraint is a domain consistent special case of scalar_product/4 with RelOp is #=:

knapsack(+Coeffs, +Xs, ?Value)

where Coeffs is a list of length n of non-negative integers, Xs is a list of length n of non-negative integers or domain variables, and Value is an integer or a domain variable. Any domain variables must have finite bounds. True if Coeffs*Xs = Value. Cannot be reified.


Node:Membership Constraints, Next:, Previous:Arithmetic Constraints, Up:Available Constraints

Membership Constraints

domain(+Variables, +Min, +Max)

where Variables is a list of domain variables or integers, Min is an integer or the atom inf (minus infinity), and Max is an integer or the atom sup (plus infinity). True if the variables all are elements of the range Min..Max. Cannot be reified.

?X in +Range

defines a membership constraint. X is an integer or a domain variable and Range is a ConstantRange (see Syntax of Indexicals). True if X is an element of the range.

?X in_set +FDSet

defines a membership constraint. X is an integer or a domain variable and FDSet is an FD set term (see FD Set Operations). True if X is an element of the FD set.

in/2 and in_set/2 constraints can be reified. They maintain domain-consistency and their reified versions detect domain-entailment and -disentailment; see The Constraint System.


Node:Propositional Constraints, Next:, Previous:Membership Constraints, Up:Available Constraints

Propositional Constraints

Propositional combinators can be used to combine reifiable constraints into propositional formulae over such constraints. Such formulae are goal expanded by the system into sequences of reified constraints and arithmetic constraints. For example,

X #= 4 #\/ Y #= 6

expresses the disjunction of two equality constraints.

The leaves of propositional formulae can be reifiable constraints, the constants 0 and 1, or 0/1-variables. New primitive, reifiable constraints can be defined with indexicals as described in Defining Primitive Constraints. The following propositional combinators are available:

#\ :Q

True if the constraint Q is false.

:P #/\ :Q

True if the constraints P and Q are both true.

:P #\ :Q

True if exactly one of the constraints P and Q is true.

:P #\/ :Q

True if at least one of the constraints P and Q is true.

:P #=> :Q
:Q #<= :P

True if the constraint Q is true or the constraint P is false.

:P #<=> :Q

True if the constraints P and Q are both true or both false.

Note that the reification scheme introduced in Reified Constraints is a special case of a propositional constraint.


Node:Combinatorial Constraints, Next:, Previous:Propositional Constraints, Up:Available Constraints

Combinatorial Constraints

The constraints listed here are sometimes called symbolic constraints. They are currently not reifiable. Unless documented otherwise, they maintain (at most) interval-consistency in their arguments; see The Constraint System.

count(+Val,+List,+RelOp,?Count)

where Val is an integer, List is a list of integers or domain variables, Count an integer or a domain variable, and RelOp is a relational symbol as in Arithmetic Constraints. True if N is the number of elements of List that are equal to Val and N RelOp Count. Thus, count/4 is a generalization of exactly/3 (not an exported constraint) that was used in an example earlier.

count/4 maintains domain-consistency, but in practice, the following constraint is a better alternative.

global_cardinality(+Vars,+Vals)

where Vars is a list of integers or domain variables, and Vals is a list of terms V-K, where V is an integer and K is a domain variable or an integer. Each V must be unique. True if every element of Vars is equal to some V and for each pair V-K, exactly K elements of Vars are equal to V.

If either Vars or Vals is ground, and in many other special cases, global_cardinality/2 maintains domain-consistency, but generally, interval-consistency cannot be guaranteed.

element(?X,+List,?Y)

where X and Y are integers or domain variables and List is a list of integers or domain variables. True if the X:th element of List is Y. Operationally, the domains of X and Y are constrained so that for every element in the domain of X, there is a compatible element in the domain of Y, and vice versa.

This constraint uses an optimized algorithm for the special case where List is ground.

element/3 maintains domain-consistency in X and interval-consistency in List and Y.

relation(?X,+MapList,?Y)

where X and Y are integers or domain variables and MapList is a list of integer-ConstantRange pairs, where the integer keys occur uniquely (see Syntax of Indexicals). True if MapList contains a pair X-R and Y is in the range denoted by R.

Operationally, the domains of X and Y are constrained so that for every element in the domain of X, there is a compatible element in the domain of Y, and vice versa.

If MapList is not ground, the constraint must be wrapped in call/1 to postpone goal expansion until runtime.

An arbitrary binary constraint can be defined with relation/3. relation/3 is implemented in terms of the following, more general constraint, with which arbitrary relations can be defined compactly:

case(Template, Tuples, Dag)
case(Template, Tuples, Dag, Options)

Template is an arbitrary non-ground Prolog term. Its variables are merely place-holders; they should not occur outside the constraint nor inside Tuples.

Tuples is a list of terms of the same shape as Template, They should not share any variables with Template.

Dag is a list of nodes of the form node(ID,X,Children). The first node in the list is the root node. X is a variable that should occur in Template.

Children is a list of terms (Min..Max)-ID, where -ID is optional, so that the Min..Max form disjoint intervals.

ID is an atomic identifier of a node, distinct from [].

Options is a list of zero or more of the following. It can be used to control the waking and pruning conditions of the constraint:

on(Spec)
prune(Spec)

Spec is one of the following, and X should occur in Template:

dom(X)
wake up when the domain of X has changed, resp. perform full pruning on X. This is the default for all variables mentioned in the constraint.
min(X)
wake up when the lower bound of X has changed, resp. prune only the lower bound of X.
max(X)
wake up when the upper bound of X has changed, resp. prune only the upper bound of X.
minmax(X)
wake up when the lower or upper bound of X has changed, resp. prune only the bounds of X.
val(X)
wake up when X has become ground, resp. only prune X when its domain has been narrowed to a singleton.
none(X)
no not suspend the constraint on X at all, resp. never prune X.

A node node(_,X,Children) evaluates to true wrt. a tuple iff:

The constraint holds if the root node evaluates to true wrt. each tuple in Tuples.

For example, recall that element(X,L,Y) wakes up when the domain of X or the lower or upper bound of Y has changed, performs full pruning of X, but only prunes the bounds of Y. The following two constraints:

element(X, [1,1,1,1,2,2,2,2], Y),
element(X, [10,10,20,20,10,10,30,30], Z)

can be replaced by the single constraint:

elts(X, Y, Z) :-
    case(f(A,B,C), [f(X,Y,Z)], [node([],A,[(1..2)-a,(3..4)-b,(5..6)-c,(7..8)-d]),
                                node(a, B,[(1..1)-e]),
                                node(b, B,[(1..1)-f]),
                                node(c, B,[(2..2)-e]),
                                node(d, B,[(2..2)-g]),
                                node(e, C,[(10..10)]),
                                node(f, C,[(20..20)]),
                                node(g, C,[(30..30)])],
                               [on(minmax(B)),on(minmax(C)),
                                prune(minmax(B)),prune(minmax(C))]).

A couple of sample queries:

| ?- elts(X, Y, Z).

X in 1..8,
Y in 1..2,
Z in 10..30 ?

| ?- elts(X, Y, Z), Z #>= 15.

X in(3..4)\/(7..8),
Y in 1..2,
Z in 20..30 ?

| ?- elts(X, Y, Z), Z #\= 20.

X in 1..8,
Y in 1..2,
Z in(10..19)\/(21..30) ?

| ?- elts(X, Y, Z), Y = 1.

Y = 1,
X in 1..4,
Z in 10..20 ?

all_different(+Variables)
all_different(+Variables, +Options)
all_distinct(+Variables)
all_distinct(+Variables, +Options)

where Variables is a list of domain variables with bounded domains or integers. Each variable is constrained to take a value that is unique among the variables. Declaratively, this is equivalent to an inequality constraint for each pair of variables.

Options is a list of zero or more of the following, where Boolean must be true or false (false is the default):

on(On)
How eagerly to wake up the constraint. One of value (the default for all_different/[1,2]), to wake up when a variable becomes ground; range, to wake up when a bound of a variable is changed; or domain (the default for all_distinct/[1,2]), to wake up when the domain of a variable is changed.
complete(Boolean)
Which algorithm to use. If true (the default for all_distinct/[1,2]), a complete algorithm [Regin 94] is used, i.e. it maintains domain-consistency. Otherwise (the default for all_different/[1,2]), an incomplete one is used, achieving exactly the same pruning as a set of pairwise inequality constraints.

The following is a constraint over two lists of length n of variables. Each variable is constrained to take a value in 1,...,n that is unique for its list. Furthermore, the lists are dual in a sense described below.

assignment(+Xs, +Ys)
assignment(+Xs, +Ys, +Options)

where Xs and Ys are lists of domain variables or integers, both of length n. Options is a list of the same form as in all_different/2 with the default value [on(domain),complete(true)]. True if all Xi, Yi in 1,...,n and Xi=j iff Yj=i.

The following constraint can be thought of as constraining n nodes in a graph to form a Hamiltonian circuit. The nodes are numbered from 1 to n. The circuit starts in node 1, visits each node, and returns to the origin.

circuit(+Succ)
circuit(+Succ, +Pred)

where Succ is a list of length n of domain variables or integers. The i:th element of Succ (Pred) is the successor (predecessor) of i in the graph. True if the values form a Hamiltonian circuit.

The following constraint can be thought of as constraining n tasks, each with a start time Sj and a duration Dj, so that no tasks ever overlap. The tasks can be seen as competing for some exclusive resource.

serialized(+Starts,+Durations)
serialized(+Starts,+Durations,+Options)

where Starts = [S1,...,Sn] and Durations = [D1,...,Dn] are lists of domain variables with finite bounds or integers. Durations must be non-negative. True if Starts and Durations denote a set of non-overlapping tasks, i.e.:

for all 1 =< i<j =< n:
  Si+Di =< Sj OR
  Sj+Dj =< Si OR
  Di = 0 OR
  Dj = 0

The serialized/[2,3] constraint is merely a special case of cumulative/[4,5] (see below).

Options is a list of zero or more of the following, where Boolean must be true or false (false is the default):

precedences(Ps)
Ps encodes a set of precedence constraints to apply to the tasks. Ps should be a list of terms of one of the forms:
  • d(i,j,d), where i and j should be task numbers, and d should be a positive integer or sup, denoting:
    Si+d =< Sj OR Sj =< Si, if d is an integer
    Sj =< Si, if d is sup
    
  • i-j in r), where i and j should be task numbers, and r should be a ConstantRange (see Syntax of Indexicals), denoting:
    Si-Sj #= Dij, Dij in r
    

resource(R)
R is unified with a term which can be passed to order_resource/2 (see Enumeration Predicates) in order to find a consistent ordering of the tasks.
path_consistency(Boolean)
if true, a redundant path consistency algorithm will be used inside the constraint in an attempt to improve the pruning.
static_sets(Boolean)
if true, a redundant algorithm will be used which reasons about the set of tasks that must precede (be preceded by) a given task, in an attempt to tighten the lower (upper) bound of a given start variable.
edge_finder(Boolean)
if true, a redundant algorithm will be used which attempts to identify tasks that necessarily precede or are preceded by some set of tasks.
decomposition(Boolean)
if true, an attempt is made to decompose the constraint each time it is resumed.
bounds_only(Boolean)
if true, the constraints will only prune the bounds of the Si variables, and not inside the domains.

Whether it's worthwhile to switch on any of the latter five options is highly problem dependent.

serialized/3 can model a set of tasks to be serialized with sequence-dependent setup times. For example, the following constraint models three tasks, all with duration 5, where task 1 must precede task 2 and task 3 must either complete before task 2 or start at least 10 time units after task 2 started:

?- domain([S1,S2,S3], 0, 20),
   serialized([S1,S2,S3], [5,5,5], [precedences([d(2,1,sup),d(2,3,10)])]).

S1 in 0..15,
S2 in 5..20,
S3 in 0..20 ?

The bounds of S1 and S2 changed because of the precedence constraint. Setting S2 to 5 will propagate S1=0 and S3 in 15..20.

The following constraint can be thought of as constraining n tasks to be placed in time and on m machines. Each machine has a resource limit, which is interpreted on a lower or upper bound on the total amount of resource used on that machine at any point in time that intersects with some task.

A tasks is represented by a term O,D,E,H,M where O is the start time, D the duration, E the end time, H the resource consumption, and M a machine identifier.

A machine is represented by a term machine(M,L) where M is the identifier and L is the resource limit of the machine.

All fields are domain variables with bounded domains, or integers. L must be an integer. D must be non-negative, but H mey be either positive or negative. A negative resource consumption is interpreted as a resource demand.

cumulatives(+Tasks,+Machines)
cumulatives(+Tasks,+Machines,+Options)

Options is a list of zero or more of the following, where Boolean must be true or false (false is the default):

bound(B)
If lower (the default), each resource limit is treated as a lower bound. If upper, each resource limit is treated as an upper bound.
prune(P)
If all (the default), the constraint will try to prune as many variables as possible. If next, only variables that occur in the first non-ground task term (wrt. the order iven when the constraint was posted) can be pruned.
generalization(Boolean)
If true, extra reasoning based on assumptions on machine assignment will be done to infer more.
task_intervals(Boolean)
If true, extra global reasoning will be performed in an attempt to infer more.

The following constraint can be thought of as constraining n tasks, each with a start time Sj, a duration Dj, and a resource amount Rj, so that the total resource consumption does not exceed Limit at any time:

cumulative(+Starts,+Durations,+Resources,?Limit)
cumulative(+Starts,+Durations,+Resources,?Limit,+Options)

where Starts = [S1,...,Sn], Durations = [D1,...,Dn], Resource = [R1,...,Rn] are lists of domain variables with finite bounds or integers, and Limit is a domain variable with finite bounds or an integer. Durations, Resources and Limit must be non-negative. Let:

a = min(S1,...,Sn),
b = max(S1+D1,...,Sn+Dn)
Rij = Rj, if Sj =< i < Sj+Dj
Rij = 0 otherwise

The constraint holds if:

Ri1+...+Rin =< Limit, for all a =< i < b

If given, Options should be of the same form as in serialized/3, except the resource(R) option is not useful in cumulative/5.

The cumulative/4 constraint is due to Aggoun and Beldiceanu [Aggoun & Beldiceanu 93].

The following constraints model a set or lines or rectangles, respectively, so that no pair of objects overlap:

disjoint1(+Lines)
disjoint1(+Lines,+Options)

where Lines is a list of terms F(Sj,Dj) or F(Sj,Dj,Tj), Sj and Dj are domain variables with finite bounds or integers denoting the origin and length of line j respectively, F is any functor, and the optional Tj is an atomic term denoting the type of the line. Tj defaults to 0 (zero).

Options is a list of zero or more of the following, where Boolean must be true or false (false is the default):

decomposition(Boolean)
if true, an attempt is made to decompose the constraint each time it is resumed.
global(Boolean)
if true, a redundant algorithm using global reasoning is used to achieve more complete pruning.
wrap(Min,Max)
If used, the space in which the lines are placed should be thought of as a circle where positions Min and Max coincide, where Min and Max should be integers. That is, the space wraps around. Furthermore, this option forces the domains of the origin variables to be inside Min..(Max-1).
margin(T1,T2,D)
This option imposes a minimal distance D between the end point of any line of type T1 and the origin of any line of type T2. D should be a positive integer or sup. If sup is used, all lines of type T2 must be placed before any line of type T1.

This option interacts with the wrap/2 option in the sense that distances are counted with possible wrap-around, and the distance between any end point and origin is always finite.

The file library('clpfd/examples/bridge.pl') contains an example where disjoint1/2 is used for scheduling non-overlapping tasks.

disjoint2(+Rectangles)
disjoint2(+Rectangles,+Options)

where Rectangles is a list of terms F(Sj1,Dj1,Sj2,Dj2) or F(Sj1,Dj1,Sj2,Dj2,Tj), Sj1 and Dj1 are domain variables with finite bounds or integers denoting the origin and size of rectangle j in the X dimension, Sj2 and Dj2 are the values for the Y dimension, F is any functor, and the optional Tj is an atomic term denoting the type of the rectangle. Tj defaults to 0 (zero).

Options is a list of zero or more of the following, where Boolean must be true or false (false is the default):

decomposition(Boolean)
If true, an attempt is made to decompose the constraint each time it is resumed.
global(Boolean)
If true, a redundant algorithm using global reasoning is used to achieve more complete pruning.
wrap(Min1,Max1,Min2,Max2)
Min1 and Max1 should be either integers or the atoms inf and sup respectively. If they are integers, the space in which the rectangles are placed should be thought of as a cylinder which wraps around the X dimension where positions Min1 and Max1 coincide. Furthermore, this option forces the domains of the Sj1 variables to be inside Min1..(Max1-1).

Min2 and Max2 should be either integers or the atoms inf and sup respectively. If they are integers, the space in which the rectangles are placed should be thought of as a cylinder which wraps around the Y dimension where positions Min2 and Max2 coincide. Furthermore, this option forces the domains of the Sj2 variables to be inside Min2..(Max2-1).

If all four are integers, the space is a toroid which wraps around both dimensions.

margin(T1,T2,D1,D2)
This option imposes minimal distances D1 in the X dimension and D2 in the Y dimension between the end point of any rectangle of type T1 and the origin of any rectangle of type T2. D1 and D2 should be positive integers or sup. If sup is used, all rectangles of type T2 must be placed before any rectangle of type T1 in the relevant dimension.

This option interacts with the wrap/4 option in the sense that distances are counted with possible wrap-around, and the distance between any end point and origin is always finite.

The file library('clpfd/examples/squares.pl') contains an example where disjoint2/2 is used for tiling squares.

synchronization(Boolean)
Let the assignment dimension and the temporal dimension denote the two dimensions, no matter which is the X and which is the Y dimension. If Boolean is true, a redundant algorithm is used to achieve more complete pruning for the following case:

The following example shows an artificial placement problem involving 25 rectangles including four groups of rectangles whose left and right borders must be aligned. If Synch is true, it can be solved with first-fail labeling in 23 backtracks. If Synch is false, 60 million backtracks do not suffice to solve it.

ex([O1,Y1a,Y1b,Y1c,
    O2,Y2a,Y2b,Y2c,Y2d,
    O3,Y3a,Y3b,Y3c,Y3d,
    O4,Y4a,Y4b,Y4c],
   Synch) :-
        domain([Y1a,Y1b,Y1c,
                Y2a,Y2b,Y2c,Y2d,
                Y3a,Y3b,Y3c,Y3d,
                Y4a,Y4b,Y4c], 1, 5),
        O1 in 1..28,
        O2 in 1..26,
        O3 in 1..22,
        O4 in 1..25,
        disjoint2([t(1,1,5,1),    t(20,4,5,1),
                   t(1,1,4,1),    t(14,4,4,1),
                   t(1,2,3,1),    t(24,2,3,1),
                   t(1,2,2,1),    t(21,1,2,1),
                   t(1,3,1,1),    t(14,2,1,1),
                   t(O1,3,Y1a,1),
                   t(O1,3,Y1b,1),
                   t(O1,3,Y1c,1),
                   t(O2,5,Y2a,1),
                   t(O2,5,Y2b,1),
                   t(O2,5,Y2c,1),
                   t(O2,5,Y2d,1),
                   t(O3,9,Y3a,1),
                   t(O3,9,Y3b,1),
                   t(O3,9,Y3c,1),
                   t(O3,9,Y3d,1),
                   t(O4,6,Y4a,1),
                   t(O4,6,Y4b,1),
                   t(O4,6,Y4c,1)],
                  [synchronization(Synch)]).


Node:User-Defined Constraints, Previous:Combinatorial Constraints, Up:Available Constraints

User-Defined Constraints

New, primitive constraints can be added defined by the user on two different levels. On a higher level, constraints can be defined using the global constraint programming interface; see Defining Global Constraints. Such constraints can embody specialized algorithms and use the full power of Prolog. They cannot be reified.

On a lower level, new primitive constraints can be defined with indexicals. In this case, they take part in the basic constraint solving algorithm and express custom designed rules for special cases of the overall local propagation scheme. Such constraints are called FD predicates; see Defining Primitive Constraints. They can optionally be reified.


Node:Enumeration Predicates, Next:, Previous:Available Constraints, Up:CLPFD

Enumeration Predicates

As is usually the case with finite domain constraint solvers, this solver is not complete. That is, it does not ensure that the set of posted constraints is satisfiable. One must resort to search (enumeration) to check satisfiability and get particular solutions.

The following predicates provide several variants of search:

indomain(?X)

where X is a domain variable with a bounded domain or an integer. Assigns, in increasing order via backtracking, a feasible value to X.

labeling(:Options, +Variables)

where Variables is a list of domain variables or integers and Options is a list of search options. The domain variables must all have bounded domains. True if an assignment of the variables can be found which satisfies the posted constraints.

first_bound(+BB0, -BB)

later_bound(+BB0, -BB)

Provides an auxiliary service for the value(Enum) option (see below).

minimize(:Goal,?X)
maximize(:Goal,?X)

Uses a branch-and-bound algorithm with restart to find an assignment that minimizes (maximizes) the domain variable X. Goal should be a Prolog goal that constrains X to become assigned, and could be a labeling/2 goal. The algorithm calls Goal repeatedly with a progressively tighter upper (lower) bound on X until a proof of optimality is obtained, at which time Goal and X are unified with values corresponding to the optimal solution.

The Options argument of labeling/2 controls the order in which variables are selected for assignment (variable choice heuristic), the way in which choices are made for the selected variable (value choice heuristic), and whether all solutions or a single, optimal solution should be found. The options are divided into four groups. One option may be selected per group. Also, the number of assumptions (choices) made during the search can be collected. Finally, a discrepancy limit can be imposed.

The following options control the order in which the next variable is selected for assignment.
leftmost
The leftmost variable is selected. This is the default.
min
The leftmost variable with the smallest lower bound is selected.
max
The leftmost variable with the greatest upper bound is selected.
ff
The first-fail principle is used: the leftmost variable with the smallest domain is selected.
ffc
The most constrained heuristic is used: a variable with the smallest domain is selected, breaking ties by (a) selecting the variable that has the most constraints suspended on it and (b) selecting the leftmost one.
variable(Sel)
Sel is a predicate to select the next variable. Given Vars, the variables that remain to label, it will be called as Sel(Vars,Selected,Rest).

Sel is expected to succeed deterministically, unifying Selected and Rest with the selected variable and the remaining list, respectively.

Sel should be a callable term, optionally with a module prefix, and the arguments Vars,Selected,Rest will be appended to it. For example, if Sel is mod:sel(Param), it will be called as mod:sel(Param,Vars,Selected,Rest).

The following options control the way in which choices are made for the selected variable X:

step
Makes a binary choice between X #= B and X #\= B, where B is the lower or upper bound of X. This is the default.
enum
Makes a multiple choice for X corresponding to the values in its domain.
bisect
Makes a binary choice between X #=< M and X #> M, where M is the midpoint of the domain of X. This strategy is also known as domain splitting.
value(Enum)
Enum is a predicate which should narrow the domain of X, possibly but not necessarily to a singleton. It will be called as Enum(X,Rest,BB0,BB) where Rest is the list of variables that need labeling except X, and BB0 and BB are parameters described below.

Enum is expected to succeed non-deterministically, narrowing the domain of X, and to backtrack one or more times, providing alternative narrowings. To ensure that branch-and-bound search works correctly, it must call the auxiliary predicate first_bound(BB0,BB) in its first solution. Similarly, it must call the auxiliary predicate later_bound(BB0,BB) in any alternative solution.

Enum should be a callable term, optionally with a module prefix, and the arguments X,Rest,BB will be appended to it. For example, if Enum is mod:enum(Param), it will be called as mod:enum(Param,X,Rest,BB).

The following options control the order in which the choices are made for the selected variable X. Not useful with the value(Enum) option:

up
The domain is explored in ascending order. This is the default.
down
The domain is explored in descending order.

The following options control whether all solutions should be enumerated by backtracking or whether a single solution that minimizes (maximizes) X is returned, if one exists.

all
All solutions are enumerated. This is the default.
minimize(X)
maximize(X)
Uses a branch-and-bound algorithm to find an assignment that minimizes (maximizes) the domain variable X. The labeling should constrain X to become assigned for all assignments of Variables.

Also, the following option counts the number of assumptions (choices) made during the search:

assumptions(K)
When a solution is found, K is unified with the number of choices made.

Finally, a limit on the discrepancy of the search can be imposed:

assumptions(D)
When a solution is found, in at most D choicepoints, a non-leftmost branch was taken.

For example, to enumerate solutions using a static variable ordering, use:

| ?- constraints(Variables),
     labeling([], Variables).
     %same as [leftmost,step,up,all]

To minimize a cost function using branch-and-bound search, a dynamic variable ordering using the first-fail principle, and domain splitting exploring the upper part of domains first, use:

| ?- constraints(Variables, Cost),
     labeling([ff,bisect,down,minimize(Cost)], Variables).

The file library('clpfd/examples/tsp.pl') contains an example of user-defined variable and value choice heuristics.

As opposed to the predicates above which search for consistent assignments to domain variables, the following predicate searches for a consistent ordering among tasks competing for an exclusive resource, without necessarily fixing their start times:

order_resource(+Options, +Resource)

where Options is a list of search options and Resource represents a resource as returned by serialized/3 (see Combinatorial Constraints) on which tasks must be serialized. True if a total ordering can be imposed on the tasks, enumerating all such orderings via backtracking.

The search options control the construction of the total ordering. It may contain at most one of the following atoms, selecting a strategy:

first
The ordering is built by repetitively selecting some task to be placed before all others.
last
The ordering is built by repetitively selecting some task to be placed after all others.

and at most one of the following atoms, controlling which task to select at each step. If first is chosen (the default), the task with the smallest value is selected; otherwise, the task with the greatest value is selected.

est
The tasks are ordered by earliest start time.
lst
The tasks are ordered by latest start time.
ect
The tasks are ordered by earliest completion time.
lct
The tasks are ordered by latest completion time.

[first,est] (the default) and [last,lct] can be good heuristics.


Node:Statistics Predicates, Next:, Previous:Enumeration Predicates, Up:CLPFD

Statistics Predicates

The following predicates can be used to get execution statistics.

fd_statistics(?Key, ?Value)

This allows a program to access execution statistics specific to this solver. General statistics about CPU time and memory consumption etc. is available from the built-in predicate statistics/2.

For each of the possible keys Key, Value is unified with the current value of a counter which is simultaneously zeroed. The following counters are maintained. See The Constraint System, for details of what they all mean:

resumptions
The number of times a constraint was resumed.
entailments
The number of times a (dis)entailment was detected by a constraint.
prunings
The number of times a domain was pruned.
backtracks
The number of times a contradiction was found by a domain being wiped out, or by a global constraint signalling failure. Other causes of backtracking, such as failed Prolog tests, are not covered by this counter.
constraints
The number of constraints created.

fd_statistics

Displays on the standard error stream a summary of the above statistics. All counters are zeroed.


Node:Answer Constraints, Next:, Previous:Statistics Predicates, Up:CLPFD

Answer Constraints

By default, the answer constraint only shows the projection of the store onto the variables that occur in the query, but not any constraints that may be attached to these variables, nor any domains or constraints attached to other variables. This is a conscious decision, as no efficient algorithm for projecting answer constraints onto the query variables is known for this constraint system.

It is possible, however, to get a complete answer constraint including all variables that took part in the computation and their domains and attached constraints. This is done by asserting a clause for the following predicate:

clpfd:full_answer [Hook]

If false (the default), the answer constraint, as well as constraints projected by clpfd:project_attributes/2, clpfd:attribute_goal/2 and their callers, only contain the domains of the query variables. If true, those constraints contain the domains and any attached constraints of all variables. Initially defined as a dynamic predicate with no clauses.


Node:The Constraint System, Next:, Previous:Answer Constraints, Up:CLPFD

The Constraint System


Node:Definitions, Next:, Previous:The Constraint System, Up:The Constraint System

Definitions

The constraint system is based on domain constraints and indexicals. A domain constraint is an expression X::I, where X is a domain variable and I is a nonempty set of integers.

A set S of domain constraints is called a store. D(X,S), the domain of X in S, is defined as the intersection of all I such that X::I belongs to S. The store is contradictory if the domain of some variable is empty; otherwise, it is consistent. A consistent store S' is an extension of a store S iff, for all variables X, D(X,S') is contained in D(X,S).

The following definitions, adapted from [Van Hentenryck et al. 95], define important notions of consistency and entailment of constraints wrt. stores.

A ground constraint is true if it holds and false otherwise.

A constraint C is domain-consistent wrt. S iff, for each variable Xi and value Vi in D(Xi,S), there exist values Vj in D(Xj,S), 1 =< j =< n, i\=j, such that C(V1,...,Vn) is true.

A constraint C is domain-entailed by S iff, for all values Vj in D(Xj,S), 1 =< j =< n, C(V1,...,Vn) is true.

Let D'(X,S) denote the interval min(D(X,S))..max(D(X,S)).

A constraint C is interval-consistent wrt. S iff, for each variable Xi there exist values Vj in D'(Xj,S), 1 =< j =< n, i\=j, such that C(V1,...,min(D(Xi,S)),...,Vn) and C(V1,...,max(D(Xi,S)),...,Vn) are both true.

A constraint C is interval-entailed by S iff, for all values Vj in D'(Xj,S), 1 =< j =< n, C(V1,...,Vn) is true.

Finally, a constraint is domain-disentailed (interval-disentailed) by S iff its negation is domain-entailed (interval-entailed) by S.


Node:Pitfalls of Interval Reasoning, Previous:Definitions, Up:The Constraint System

Pitfalls of Interval Reasoning

In most circumstances, arithmetic constraints only maintain interval-consistency and only detect interval-entailment and -disentailment. Note that there are cases where an interval-consistency maintaining constraint may detect a contradiction when the constraint is not yet interval-disentailed, as the following example illustrates. Note that X #\= Y maintains domain consistency if both arguments are constants or variables:

| ?- X+Y #= Z, X=1, Z=6, Y in 1..10, Y #\= 5.

no
| ?- X+Y #= Z #<=> B, X=1, Z=6, Y in 1..10, Y #\= 5.

X = 1,
Z = 6,
Y in(1..4)\/(6..10),
B in 0..1

Since 1+5#=6 holds, X+Y #= Z is not interval-disentailed, although any attempt to make it interval-consistent wrt. the store results in a contradictory store.


Node:Defining Global Constraints, Next:, Previous:The Constraint System, Up:CLPFD

Defining Global Constraints


Node:The Global Constraint Programming Interface, Next:, Previous:Defining Global Constraints, Up:Defining Global Constraints

The Global Constraint Programming Interface

This section describes a programming interface by means of which new constraints can be written. The interface consists of a set of predicates provided by this library module. Constraints defined in this way can take arbitrary arguments and may use any constraint solving algorithm, provided it makes sense. Reification cannot be expressed in this interface; instead, reification may be achieved by explicitly passing a 0/1-variable to the constraint in question.

Global constraints have state which may be updated each time the constraint is resumed. The state information may be used e.g. in incremental constraint solving.

The following two predicates are the principal entrypoints for defining and posting new global constraints:

clpfd:dispatch_global(+Constraint, +State0, -State, -Actions) [Hook]

Tells the solver how to solve constraints of the form Constraint. Defined as a dynamic, multifile predicate.

When defining a new constraint, a clause of this predicate must be added. Its body defines a constraint solving method and should always succeed deterministically. When a global constraint is called or resumed, the solver will call this predicate to deal with the constraint. NOTE: the constraint is identified by its principal functor; there is no provision for having two constraints with the same name in different modules.

State0 and State are the old and new state respectively.

The constraint solving method must not invoke the constraint solver recursively e.g. by binding variables or posting new constraints; instead, Actions should be unified with a list of requests to the solver. Each request should be of the following form:

exit
The constraint has become entailed, and ceases to exist.
fail
The constraint has become disentailed, causing the solver to backtrack.
X = V
The solver binds X to V.
X in R
The solver constrains X to be a member of the ConstantRange R (see Syntax of Indexicals).
X in_set S
The solver constrains X to be a member of the FD set S (see FD Set Operations).
call(Goal)
The solver calls the goal or constraint Goal, which should be module prefixed unless it is a built-in predicate or an exported predicate of the clpfd module.

Goal is executed as any Prolog goal, but in a context where some constraints may already be enqueued for execution, in which case those constraints will run after the completion of the call request.

The constraint solving method is assumed to be idempotent. That is, if the Actions were performed by the solver and the constraint resumed, it should not produce any further Actions. Thus the solver will not check for the resumption conditions for the given constraint, while performing its Actions.

fd_global(:Constraint, +State, +Susp)

where Constraint is a constraint goal, State is its initial state, and Susp is a term encoding how the constraint should wake up in response to domain changes. This posts the constraint.

Susp is a list of F(Var) terms where Var is a variable to suspend on and F is a functor encoding when to wake up:

dom(X)
wake up when the domain of X has changed
min(X)
wake up when the lower bound of X has changed
max(X)
wake up when the upper bound of X has changed
minmax(X)
wake up when the lower or upper of X has changed
val(X)
wake up when X has become ground

For an example of usage, see A Global Constraint Example.


Node:Reflection Predicates, Next:, Previous:The Global Constraint Programming Interface, Up:Defining Global Constraints

Reflection Predicates

The constraint solving method needs access to information about the current domains of variables. This is provided by the following predicates, which are all constant time operations.

fd_min(?X, ?Min)

where X is a domain variable (or an integer). Min is unified with the smallest value in the current domain of X, i.e. an integer or the atom inf denoting minus infinity.

fd_max(?X, ?Max)

where X is a domain variable (or an integer). Max is unified with the upper bound of the current domain of X, i.e. an integer or the atom sup denoting infinity.

fd_size(?X, ?Size)

where X is a domain variable (or an integer). Size is unified with the size of the current domain of X, if the domain is bounded, or the atom sup otherwise.

fd_set(?X, ?Set)

where X is a domain variable (or an integer). Set is unified with an FD set term denoting the internal representation of the current domain of X; see below.

fd_dom(?X, ?Range)

where X is a domain variable (or an integer). Range is unified with a ConstantRange (see Syntax of Indexicals) denoting the the current domain of X.

fd_degree(?X, ?Degree)

where X is a domain variable (or an integer). Degree is unified with the number of constraints that are attached to X. NOTE: this number may include some constraints that have been detected as entailed. Also, Degree is not the number of neighbors of X in the constraint network.

The following predicates can be used for computing the set of variables that are (transitively) connected via constraints to some given variable(s).

fd_neighbors(+Var, -Neighbors)

Given a domain variable Var, Neighbors is the set of variables that can be reached from Var via constraints posted so far.

fd_closure(+Vars, -Closure)

Given a list Vars of domain variables, Closure is the set of variables (including Vars) that can be transitively reached via constraints posted so far. Thus, fd_closure/2 is the transitive closure of fd_neighbors/2.

The following predicate can be used for computing a symbolic form of the constraints that are transitively attached to some term. This is useful e.g. in the context of asserting or copying terms, as these operations are not supported on terms containing domain variables:

fd_copy_term(+Term, -Template, -Body)

Given a term Term containing domain variables, Template is a copy of the same term with all variables renamed to new variables such that executing Body will post constraints equivalent to those that Term is attached to.

For example:

| ?- X in 0..1, Y in 10..11, X+5 #=< Y, fd_copy_term(f(X,Y), Template, Body).

Body = _A in_set[[0|1]],_B in_set[[10|11]],clpfd:'t>=u+c'(_B,_A,5),
Template = f(_A,_B),
X in 0..1,
Y in 10..11 ?


Node:FD Set Operations, Next:, Previous:Reflection Predicates, Up:Defining Global Constraints

FD Set Operations

The domains of variables are internally represented compactly as FD set terms. The details of this representation are subject to change and should not be relied on. Therefore, a number of operations on FD sets are provided, as such terms play an important role in the interface. The following operations are the primitive ones:

is_fdset(+Set)

Set is a valid FD set.

empty_fdset(?Set)

Set is the empty FD set.

fdset_parts(?Set, ?Min, ?Max, ?Rest)

Set is an FD set which is a union of the non-empty interval Min..Max and the FD set Rest, and all elements of Rest are greater than Max+1. Min and Max are both integers or the atoms inf and sup, denoting minus and plus infinity, respectively. Either Set or all the other arguments must be ground.

The following operations can all be defined in terms of the primitive ones, but in most cases, a more efficient implementation is used:

empty_interval(+Min, +Max)

Min..Max is an empty interval.

fdset_interval(?Set, ?Min, ?Max)

Set is an fdset which is the non-empty interval Min..Max.

fdset_singleton(?Set, ?Elt)

Set is an FD set containing Elt only. At least one of the arguments must be ground.

fdset_min(+Set, -Min)

Min is the lower bound of Set.

fdset_max(+Set, -Min)

Max is the upper bound of Set. This operation is linear in the number of intervals of Set.

fdset_size(+Set, -Size)

Size is the cardinality of Set, represented as sup if Set is infinite. This operation is linear in the number of intervals of Set.

list_to_fdset(+List, -Set)

Set is the FD set containing the elements of List. Slightly more efficient if List is ordered.

fdset_to_list(+Set, -List)

List is an ordered list of the elements of Set, which must be finite.

range_to_fdset(+Range, -Set)

Set is the FD set containing the elements of the ConstantRange (see Syntax of Indexicals) Range.

fdset_to_range(+Set, -Range)

Range is a constant interval, a singleton constant set, or a union of such, denoting the same set as Set.

fdset_add_element(+Set1, +Elt -Set2)

Set2 is Set1 with Elt inserted in it.

fdset_del_element(+Set1, +Elt, -Set2)

Set2 is like Set1 but with Elt removed.

fdset_disjoint(+Set1, +Set2)

The two FD sets have no elements in common.

fdset_intersect(+Set1, +Set2)

The two FD sets have at least one element in common.

fdset_intersection(+Set1, +Set2, -Intersection)

Intersection is the intersection between Set1 and Set2.

fdset_intersection(+Sets, -Intersection)

Intersection is the intersection of all the sets in Sets.

fdset_member(?Elt, +Set)

is true when Elt is a member of Set. If Elt is unbound, Set must be finite.

fdset_eq(+Set1, +Set2)

Is true when the two arguments represent the same set i.e. they are identical.

fdset_subset(+Set1, +Set2)

Every element of Set1 appears in Set2.

fdset_subtract(+Set1, +Set2, -Difference)

Difference contains all and only the elements of Set1 which are not also in Set2.

fdset_union(+Set1, +Set2, -Union)

Union is the union of Set1 and Set2.

fdset_union(+Sets, -Union)

Union is the union of all the sets in Sets.

fdset_complement(+Set, -Complement)

Complement is the complement of Set wrt. inf..sup.


Node:A Global Constraint Example, Previous:FD Set Operations, Up:Defining Global Constraints

A Global Constraint Example

The following example defines a new global constraint exactly(X,L,N) which is true if X occurs exactly N times in the list L of integers and domain variables. N must be an integer when the constraint is posted. A version without this restriction and defined in terms of reified equalities was presented earlier; see Reified Constraints.

This example illustrates the use of state information. The state has two components: the list of variables that could still be X, and the number of variables still required to be X.

The constraint is defined to wake up on any domain change.

/*
An implementation of exactly(I, X[1]...X[m], N):

Necessary condition: 0 =< N =< m.
Rewrite rules:

[1] |= X[i]=I  ==> exactly(I, X[1]...X[i-1],X[i+1]...X[m], N-1):
[2] |= X[i]\=I ==> exactly(I, X[1]...X[i-1],X[i+1]...X[m], N):
[3] |= N=0     ==> X[1]\=I ... X[m]\=I
[4] |= N=m     ==> X[1]=I  ... X[m]=I
*/
:- use_module(library(clpfd)).

% the entrypoint
exactly(I, Xs, N) :-
        dom_suspensions(Xs, Susp),
        fd_global(exactly(I,Xs,N), state(Xs,N), Susp).

dom_suspensions([], []).
dom_suspensions([X|Xs], [dom(X)|Susp]) :-
        dom_suspensions(Xs, Susp).

% the solver method
:- multifile clpfd:dispatch_global/4.
clpfd:dispatch_global(exactly(I,_,_), state(Xs0,N0), state(Xs,N), Actions) :-
        exactly_solver(I, Xs0, Xs, N0, N, Actions).

exactly_solver(I, Xs0, Xs, N0, N, Actions) :-
        ex_filter(Xs0, Xs, N0, N, I),
        length(Xs, M),
        (   N=:=0 -> Actions = [exit|Ps], ex_neq(Xs, I, Ps)
        ;   N=:=M -> Actions = [exit|Ps], ex_eq(Xs, I, Ps)
        ;   N>0, N<M -> Actions = []
        ;   Actions = [fail]
        ).

% rules [1,2]: filter the X's, decrementing N
ex_filter([], [], N, N, _).
ex_filter([X|Xs], Ys, L, N, I) :- X==I, !,
        M is L-1,
        ex_filter(Xs, Ys, M, N, I).
ex_filter([X|Xs], Ys0, L, N, I) :-
        fd_set(X, Set),
        fdset_member(I, Set), !,
        Ys0 = [X|Ys],
        ex_filter(Xs, Ys, L, N, I).
ex_filter([_|Xs], Ys, L, N, I) :-
        ex_filter(Xs, Ys, L, N, I).

% rule [3]: all must be neq I
ex_neq(Xs, I, Ps) :-
        fdset_singleton(Set0, I),
        fdset_complement(Set0, Set),
        eq_all(Xs, Set, Ps).

% rule [4]: all must be eq I
ex_eq(Xs, I, Ps) :-
        fdset_singleton(Set, I),
        eq_all(Xs, Set, Ps).

eq_all([], _, []).
eq_all([X|Xs], Set, [X in_set Set|Ps]) :-
        eq_all(Xs, Set, Ps).

end_of_file.

% sample queries:
| ?- exactly(5,[A,B,C],1), A=5.

A = 5,
B in(inf..4)\/(6..sup),
C in(inf..4)\/(6..sup)

| ?- exactly(5,[A,B,C],1), A in 1..2, B in 3..4.

C = 5,
A in 1..2,
B in 3..4


Node:Defining Primitive Constraints, Next:, Previous:Defining Global Constraints, Up:CLPFD

Defining Primitive Constraints

Indexicals are the principal means of defining constraints, but it is usually not necessary to resort to this level of programming--most commonly used constraints are available in a library and/or via macro-expansion. The key feature about indexicals is that they give the programmer precise control over aspects of the operational semantics of the constraints. Trade-offs can be made between the computational cost of the constraints and their pruning power. The indexical language provides many degrees of freedom for the user to select the level of consistency to be maintained depending on application-specific needs.


Node:Indexicals, Next:, Previous:Defining Primitive Constraints, Up:Defining Primitive Constraints

Indexicals

An indexical is a reactive functional rule of the form X in R, where R is a set valued range expression (see below). See Syntax of Indexicals, for a grammar defining indexicals and range expressions.

Indexicals can play one of two roles: propagating indexicals are used for constraint solving, and checking indexicals are used for entailment checking. When a propagating indexical fires, R is evaluated in the current store S, which is extended by adding the new domain constraint X::S(R) to the store, where S(R) denotes the value of R in S. When a checking indexical fires, it checks if D(X,S) is contained in S(R), and if so, the constraint corresponding to the indexical is detected as entailed.


Node:Range Expressions, Next:, Previous:Indexicals, Up:Defining Primitive Constraints

Range Expressions

A range expression has one of the following forms, where Ri denote range expressions, Ti denote integer valued term expressions, S(Ti) denotes the integer value of Ti in S, X denotes a variable, I denotes an integer, and S denotes the current store.

dom(X)
evaluates to D(X,S)
{T1,...,Tn}
evaluates to {S(T1),...,S(Tn)}. Any term expression containing a subexpression which is a variable that is not "quantified" by unionof/3 will only be evaluated when this variable has been assigned.
T1..T2
evaluates to the interval between S(T1) and S(T2).
R1/\R2
evaluates to the intersection of S(R1) and S(R2)
R1\/R2
evaluates to the union of S(R1) and S(R2)
\R2
evaluates to the complement of S(R2)
R1+R2
R1+T2
evaluates to S(R2) or S(T2) added pointwise to S(R1)
-R2
evaluates to S(R2) negated pointwise
R1-R2
R1-T2
T1-R2
evaluates to S(R2) or S(T2) subtracted pointwise from S(R1) or S(T1)
R1 mod R2
R1 mod T2
evaluates to S(R1) pointwise modulo S(R2) or S(T2)
R1 ? R2
evaluates to S(R2) if S(R1) is a non-empty set; otherwise, evaluates to the empty set. This expression is commonly used in the context (R1 ? (inf..sup) \/ R3), which evaluates to S(R3) if S(R1) is an empty set; otherwise, evaluates to inf..sup. As an optimization, R3 is not evaluated while the value of R1 is a non-empty set.
unionof(X,R1,R2)
evaluates to the union of S(Expr_1)...S(Expr_N), where each Expr_I has been formed by substituting K for X in R2, where K is the I:th element of S(R1). See N Queens, for an example of usage. N.B. If S(R1) is infinite, the evaluation of the indexical will be abandoned, and the indexical will simply suspend.
switch(T1,MapList)
evaluates to S(Expr) if S(T1) equals Key and MapList contains a pair Key-Expr. Otherwise, evaluates to the empty set.

When used in the body of an FD predicate (see Goal Expanded Constraints), a relation/3 expression expands to two indexicals, each consisting of a switch/2 expression nested inside a unionof/3 expression. Thus, the following constraints are equivalent:

p(X, Y) +: relation(X, [1-{1},2-{1,2},3-{1,2,3}], Y).

q(X, Y) +:
        X in unionof(B,dom(Y),switch(B,[1-{1,2,3},2-{2,3},3-{3}])),
        Y in unionof(B,dom(X),switch(B,[1-{1},2-{1,2},3-{1,2,3}])).


Node:Term Expressions, Next:, Previous:Range Expressions, Up:Defining Primitive Constraints

Term Expressions

A term expression has one of the following forms, where T1 and T2 denote term expressions, X denotes a variable, I denotes an integer, and S denotes the current store.

min(X)
evaluates to the minimum of D(X,S)
max(X)
evaluates to the maximum of D(X,S)
card(X)
evaluates to the size of D(X,S)
X
evaluates to the integer value of X. A subexpression of this form, not "quantified" by unionof/3, will cause the evaluation to suspend until the variable is assigned.
I
an integer
inf
minus infinity
sup
plus infinity
-T1
evaluates to S(T1) negated
T1+T2
evaluates to the sum of S(T1) and S(T2)
T1-T2
evaluates to the difference of S(T1) and S(T2)
T1*T2
evaluates to the product of S(T1) and S(T2), where S(T2) must not be negative
T1/>T2
evaluates to the quotient of S(T1) and S(T2), rounded up, where S(T2) must be positive
T1/<T2
evaluates to the quotient of S(T1) and S(T2), rounded down, where S(T2) must be positive
T1 mod T2
evaluates to the modulo of S(T1) and S(T2)


Node:Monotonicity of Indexicals, Next:, Previous:Term Expressions, Up:Defining Primitive Constraints

Monotonicity of Indexicals

A range R is monotone in S iff the value of R in S' is contained in the value of R in S, for every extension S' of S. A range R is anti-monotone in S iff the value of R in S is contained in the value of R in S', for every extension S' of S. By abuse of notation, we will say that X in R is (anti-)monotone iff R is (anti-)monotone.

The consistency or entailment of a constraint C expressed as indexicals X in R in a store S is checked by considering the relationship between D(X,S) and S(R), together with the (anti-)monotonicity of R in S. The details are given in Execution of Propagating Indexicals and Execution of Checking Indexicals.

The solver checks (anti-)monotonicity by requiring that certain variables occurring in the indexical be ground. This sufficient condition can sometimes be false for an (anti-)monotone indexical, but such situations are rare in practice.


Node:FD predicates, Next:, Previous:Monotonicity of Indexicals, Up:Defining Primitive Constraints

FD predicates

The following example defines the constraint X+Y=T as an FD predicate in terms of three indexicals. Each indexical is a rule responsible for removing values detected as incompatible from one particular constraint argument. Indexicals are not Prolog goals; thus, the example does not express a conjunction. However, an indexical may make the store contradictory, in which case backtracking is triggered:

plus(X,Y,T) +:
        X in min(T) - max(Y) .. max(T) - min(Y),
        Y in min(T) - max(X) .. max(T) - min(X),
        T in min(X) + min(Y) .. max(X) + max(Y).

The above definition contains a single clause used for constraint solving. The first indexical wakes up whenever the bounds of S(T) or S(Y) are updated, and removes from D(X,S) any values that are not compatible with the new bounds of T and Y. Note that in the event of "holes" in the domains of T or Y, D(X,S) may contain some values that are incompatible with X+Y=T but go undetected. Like most built-in arithmetic constraints, the above definition maintains interval-consistency, which is significantly cheaper to maintain than domain-consistency and suffices in most cases. The constraint could for example be used as follows:

| ?- X in 1..5, Y in 2..8, plus(X,Y,T).

X in 1..5,
Y in 2..8,
T in 3..13 ?

yes

Thus, when an FD predicate is called, the +: clause is activated.

The definition of a user constraint has to specify what domain constraints should be added to the constraint store when the constraint is posted. Therefore the FD predicate contains a set of indexicals, each representing a domain constraint to be added to the constraint store. The actual domain constraint depends on the constraint store itself. For example, the third indexical in the above FD predicate prescribes the domain constraint T :: 3..13 if the store contains X :: 1..5, Y :: 2..8. As the domain of some variables gets narrower, the indexical may enforce a new, stricter constraint on some other variables. Therefore such an indexical (called a propagating indexical) can be viewed as an agent reacting to the changes in the store by enforcing further changes in the store.

In general there are three stages in the lifetime of a propagating indexical. When it is posted it may not be evaluated immediately (e.g. has to wait until some variables are ground before being able to modify the store). Until the preconditions for the evaluation are satisfied, the agent does not enforce any constraints. When the indexical becomes evaluable the resulting domain constraint is added to the store. The agent then waits and reacts to changes in the domains of variables occurring in the indexical by re-evaluating it and adding the new, stricter constraint to the store. Eventually the computation reaches a phase when no further refinement of the store can result in a more precise constraint (the indexical is entailed by the store), and then the agent can cease to exist.

A necessary condition for the FD predicate to be correctly defined is the following: for any store mapping each variable to a singleton domain the execution of the indexicals should succeed without contradiction exactly when the predicate is intended to be true.

There can be several alternative definitions for the same user constraint with different strengths in propagation. For example, the definition of plusd below encodes the same X+Y=T constraint as the plus predicate above, but maintaining domain consistency:

plusd(X,Y,T) +:
        X in dom(T) - dom(Y),
        Y in dom(T) - dom(X),
        T in dom(X) + dom(Y).

| ?- X in {1}\/{3}, Y in {10}\/{20}, plusd(X, Y, T).

X in{1}\/{3},
Y in{10}\/{20},
T in{11}\/{13}\/{21}\/{23} ?

yes

This costs more in terms of execution time, but gives more precise results. For singleton domains plus and plusd behave in the same way.

In our design, general indexicals can only appear in the context of FD predicate definitions. The rationale for this restriction is the need for general indexicals to be able to suspend and resume, and this ability is only provided by the FD predicate mechanism.

If the program merely posts a constraint, it suffices for the definition to contain a single clause for solving the constraint. If a constraint is reified or occurs in a propositional formula, the definition must contain four clauses for solving and checking entailment of the constraint and its negation. The role of each clause is reflected in the "neck" operator. The following table summarizes the different forms of indexical clauses corresponding to a constraint C. In all cases, Head should be a compound term with all arguments being distinct variables:

Head +: Indexicals.
The clause consists of propagating indexicals for solving C.
Head -: Indexicals.
The clause consists of propagating indexicals for solving the negation of C.
Head +? Indexical.
The clause consists of a single checking indexical for testing entailment of C.
Head -? Indexical.
The clause consists of a single checking indexical for testing entailment of the negation of C.

When a constraint is reified, the solver spawns two reactive agents corresponding to detecting entailment and disentailment. Eventually, one of them will succeed in this and consequently will bind B to 0 or 1. A third agent is spawned, waiting for B to become assigned, at which time the constraint (or its negation) is posted. In the mean time, the constraint may have been detected as (dis)entailed, in which case the third agent is dismissed. The waiting is implemented by means of the coroutining facilities of SICStus Prolog.

As an example of a constraint with all methods defined, consider the following library constraint defining a disequation between two domain variables:

'x\\=y'(X,Y) +:
        X in \{Y},
        Y in \{X}.
'x\\=y'(X,Y) -:
        X in dom(Y),
        Y in dom(X).
'x\\=y'(X,Y) +?
        X in \dom(Y).
'x\\=y'(X,Y) -?
        X in {Y}.

The following sections provide more precise coding rules and operational details for indexicals. X in R denotes an indexical corresponding to a constraint C. S denotes the current store.


Node:Execution of Propagating Indexicals, Next:, Previous:FD predicates, Up:Defining Primitive Constraints

Execution of Propagating Indexicals

Consider the definition of a constraint C containing a propagating indexical X in R. Let TV(X,C,S) denote the set of values for X that can make C true in some ground extension of the store S. Then the indexical should obey the following coding rules:

If the coding rules are observed, S(R) can be proven to contain TV(X,C,S) for all stores in which R is monotone. Hence it is natural for the implementation to wait until R becomes monotone before admitting the propagating indexical for execution. The execution of X in R thus involves the following:

A propagating indexical is scheduled for execution as follows:


Node:Execution of Checking Indexicals, Next:, Previous:Execution of Propagating Indexicals, Up:Defining Primitive Constraints

Execution of Checking Indexicals

Consider the definition of a constraint C containing a checking indexical X in R. Let FV(X,C,S) denote the set of values for X that can make C false in some ground extension of the store S. Then the indexical should obey the following coding rules:

If the coding rules are observed, S(R) can be proven to exclude FV(X,C,S) for all stores in which R is anti-monotone. Hence it is natural for the implementation to wait until R becomes anti-monotone before admitting the checking indexical for execution. The execution of X in R thus involves the following:

A checking indexical is scheduled for execution as follows:


Node:Goal Expanded Constraints, Previous:Execution of Checking Indexicals, Up:Defining Primitive Constraints

Goal Expanded Constraints

The arithmetic, membership, and propositional constraints described earlier are transformed at compile time to conjunctions of goals of library constraints.

Sometimes it is necessary to postpone the expansion of a constraint until runtime, e.g. if the arguments are not instantiated enough. This can be achieved by wrapping call/1 around the constraint.

Although space economic (linear in the size of the source code), the expansion of a constraint to library goals can have an overhead compared to expressing the constraint in terms of indexicals. Temporary variables holding intermediate values may have to be introduced, and the grain size of the constraint solver invocations can be rather small. The translation of constraints to library goals has been greatly improved in the current version, so these problems have virtually disappeared. However, for backward compatibility, an implementation by compilation to indexicals of the same constraints is also provided. An FD predicate may be defined by a single clause:

    Head +: Constraint.

where Constraint is an arithmetic constraint or an element/3 or a relation/3 constraint. This translation is only available for +: clauses; thus, Head cannot be reified.

In the case of arithmetic constraints, the constraint must be over linear terms (see Syntax of Indexicals). The memory consumption of the FD predicate will be quadratic in the size of the source code. The alternative version of sum/8 in Send More Money illustrates this technique.

In the case of element(X,L,Y) or relation(X,L,Y), the memory consumption of the FD predicate will be linear in the size of the source code. The execution time of the initial evaluation of the FD predicate will be linear in the size of the initial domains for X and Y; if these domains are infinite, no propagation will take place.


Node:Example Programs, Next:, Previous:Defining Primitive Constraints, Up:CLPFD

Example Programs

This section contains a few example programs. The first two programs are included in a benchmark suite that comes with the distribution. The benchmark suite is run by typing:

| ?- compile(library('clpfd/examples/bench')).
| ?- bench.


Node:Send More Money, Next:, Previous:Example Programs, Up:Example Programs

Send More Money

Let us return briefly to the Send More Money problem (see A Constraint Satisfaction Problem). Its sum/8 predicate will expand to a space-efficient conjunction of library constraints. A faster but more memory consuming version is defined simply by changing the neck symbol of sum/8 from :- to +:, thus turning it into an FD predicate:

sum(S, E, N, D, M, O, R, Y) +:
                  1000*S + 100*E + 10*N + D
     +            1000*M + 100*O + 10*R + E
     #= 10000*M + 1000*O + 100*N + 10*E + Y.


Node:N Queens, Next:, Previous:Send More Money, Up:Example Programs

N Queens

The problem is to place N queens on an NxN chess board so that no queen is threatened by another queen.

The variables of this problem are the N queens. Each queen has a designated row. The problem is to select a column for it.

The main constraint of this problem is that no queen threaten another. This is encoded by the no_threat/3 constraint and holds between all pairs (X,Y) of queens. It could be defined as

no_threat(X, Y, I) :-
        X   #\= Y,
        X+I #\= Y,
        X-I #\= Y.

However, this formulation introduces new temporary domain variables and creates twelve fine-grained indexicals. Worse, the arithmetic constraints are only guaranteed to maintain interval-consistency and so may miss some opportunities for pruning elements in the middle of domains.

A better idea is to formulate no_threat/3 as an FD predicate with two indexicals, as shown in the program below. This constraint will not fire until one of the queens has been assigned (the corresponding indexical does not become monotone until then). Hence, the constraint is still not as strong as it could be.

For example, if the domain of one queen is (2..3), then it will threaten any queen placed in column 2 or 3 on an adjacent row, no matter which of the two open positions is chosen for the first queen. The commented out formulation of the constraint captures this reasoning, and illustrates the use of the unionof/3 operator. This stronger version of the constraint indeed gives less backtracking, but is computationally more expensive and does not pay off in terms of execution time, except possibly for very large chess boards.

It is clear that no_threat/3 cannot detect any incompatible values for a queen with domain of size greater than three. This observation is exploited in the third version of the constraint.

The first-fail principle is appropriate in the enumeration part of this problem.

:- use_module(library(clpfd)).

queens(N, L, LabelingType) :-
     length(L, N),
     domain(L, 1, N),
     constrain_all(L),
     labeling(LabelingType, L).

constrain_all([]).
constrain_all([X|Xs]) :-
     constrain_between(X, Xs, 1),
     constrain_all(Xs).

constrain_between(_X, [], _N).
constrain_between(X, [Y|Ys], N) :-
     no_threat(X, Y, N),
     N1 is N+1,
     constrain_between(X, Ys, N1).


% version 1: weak but efficient
no_threat(X, Y, I) +:
     X in \({Y} \/ {Y+I} \/ {Y-I}),
     Y in \({X} \/ {X+I} \/ {X-I}).

/*
% version 2: strong but very inefficient version
no_threat(X, Y, I) +:
    X in unionof(B,dom(Y),\({B} \/ {B+I} \/ {B-I})),
    Y in unionof(B,dom(X),\({B} \/ {B+I} \/ {B-I})).

% version 3: strong but somewhat inefficient version
no_threat(X, Y, I) +:
    X in (4..card(Y)) ? (inf..sup) \/
          unionof(B,dom(Y),\({B} \/ {B+I} \/ {B-I})),
    Y in (4..card(X)) ? (inf..sup) \/
          unionof(B,dom(X),\({B} \/ {B+I} \/ {B-I})).
*/

| ?- queens(8, L, [ff]).

L = [1,5,8,6,3,7,2,4] ?


Node:Cumulative Scheduling, Previous:N Queens, Up:Example Programs

Cumulative Scheduling

This example is a very small scheduling problem. We consider seven tasks where each task has a fixed duration and a fixed amount of used resource:

TASK    DURATION        RESOURCE
====    ========        ========
t1            16               2
t2             6               9
t3            13               3
t4             7               7
t5             5              10
t6            18               1
t7             4              11

The goal is to find a schedule that minimizes the completion time for the schedule while not exceeding the capacity 13 of the resource. The resource constraint is succinctly captured by a cumulative/4 constraint. Branch-and-bound search is used to find the minimal completion time.

This example was adapted from [Beldiceanu & Contejean 94].

:- use_module(library(clpfd)).
:- use_module(library(lists), [append/3]).

schedule(Ss, End) :-
        length(Ss, 7),
        Ds = [16, 6,13, 7, 5,18, 4],
        Rs = [ 2, 9, 3, 7,10, 1,11],
        domain(Ss, 1, 30),
        domain([End], 1, 50),
        after(Ss, Ds, End),
        cumulative(Ss, Ds, Rs, 13),
        append(Ss, [End], Vars),
        labeling([minimize(End)], Vars). % label End last

after([], [], _).
after([S|Ss], [D|Ds], E) :- E #>= S+D, after(Ss, Ds, E).

%% End of file

| ?- schedule(Ss, End).

Ss = [1,17,10,10,5,5,1],
End = 23 ?


Node:Syntax Summary, Previous:Example Programs, Up:CLPFD

Syntax Summary


Node:Syntax of Indexicals, Next:, Previous:Syntax Summary, Up:Syntax Summary

Syntax of Indexicals

X --> variable                { domain variable }

Constant --> integer
  |   inf                         { minus infinity }
  |   sup                         { plus infinity }

Term --> Constant
  |   X                     { suspend until assigned }
  |   min(X)                { min. of domain of X }
  |   max(X)                { max. of domain of X }
  |   card(X)               { size of domain of X }
  |   - Term
  |   Term + Term
  |   Term - Term
  |   Term * Term
  |   Term /> Term               { division rounded up }
  |   Term /< Term               { division rounded down }
  |   Term mod Term

TermSet --> {Term,...,Term}

Range --> TermSet
  |   dom(X)                          { domain of X }
  |   Term..Term                      { interval }
  |   Range/\Range                     { intersection }
  |   Range\/Range                     { union }
  |   \Range                          { complement }
  |   - Range                         { pointwise negation }
  |   Range + Range                   { pointwise addition }
  |   Range - Range                   { pointwise subtraction }
  |   Range mod Range                 { pointwise modulo }
  |   Range + Term                    { pointwise addition }
  |   Range - Term                    { pointwise subtraction }
  |   Term - Range                    { pointwise subtraction }
  |   Range mod Term                  { pointwise modulo }
  |   Range ? Range
  |   unionof(X,Range,Range)
  |   switch(Term,MapList)

ConstantSet --> {integer,...,integer}

ConstantRange --> ConstantSet
  |   Constant..Constant
  |   ConstantRange/\ConstantRange
  |   ConstantRange\/ConstantRange
  |   \ConstantRange

MapList --> []
  |   [integer-ConstantRange|MapList]

CList --> []
  |   [integer|CList]

Indexical --> X in Range

Indexicals --> Indexical
  |   Indexical, Indexicals

ConstraintBody --> Indexicals
   |  LinExpr RelOp LinExpr
   |  element(X,CList,X)
   |  relation(X,MapList,X)

Head --> term  { a compound term with unique variable args }

TellPos --> Head +: ConstraintBody.
TellNeg --> Head -: ConstraintBody.
AskPos --> Head +? Indexical.
AskNeg --> Head -? Indexical.

ConstraintDef -->
      TellPos. [TellNeg.] [AskPos.] [AskNeg.]


Node:Syntax of Arithmetic Expressions, Next:, Previous:Syntax of Indexicals, Up:Syntax Summary

Syntax of Arithmetic Expressions

X --> variable                { domain variable }

N --> integer

LinExpr --> N                { linear expression }
  |   X
  |   N * X
  |   N * N
  |   LinExpr + LinExpr
  |   LinExpr - LinExpr

Expr --> LinExpr
  |   Expr + Expr
  |   Expr - Expr
  |   Expr * Expr
  |   Expr / Expr                { integer division }
  |   Expr mod Expr
  |   min(Expr,Expr)
  |   max(Expr,Expr)
  |   abs(Expr)

RelOp --> #= | #\= | #< | #=< | #> | #>=


Node:Operator Declarations, Previous:Syntax of Arithmetic Expressions, Up:Syntax Summary

Operator Declarations

:- op(1200, xfx, [+:,-:,+?,-?]).
:- op(760,  yfx, #<=>).
:- op(750,  xfy, #=>).
:- op(750,  yfx, #<=).
:- op(740,  yfx, #\/).
:- op(730,  yfx, #\).
:- op(720,  yfx, #/\).
:- op(710,   fy, #\).
:- op(700,  xfx, [in,in_set]).
:- op(700,  xfx, [#=,#\=,#<,#=<,#>,#>=]).
:- op(550,  xfx, ..).
:- op(500,   fy, \).
:- op(490,  yfx, ?).
:- op(400,  yfx, [/>,/<]).


Node:CHR, Next:, Previous:CLPFD, Up:Top

Constraint Handling Rules


Node:CHR Copyright, Next:, Previous:CHR, Up:CHR

Copyright

This chapter is Copyright © 1996-98 LMU

LMU (Ludwig-Maximilians-University)
Munich, Germany

Permission is granted to make and distribute verbatim copies of this chapter provided the copyright notice and this permission notice are preserved on all copies.

Permission is granted to copy and distribute modified versions of this chapter under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one.

Permission is granted to copy and distribute translations of this chapter into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by LMU.


Node:CHR Introduction, Next:, Previous:CHR Copyright, Up:CHR

Introduction

Experience from real-life applications using constraint-based programming has shown that typically, one is confronted with a heterogeneous mix of different types of constraints. To be able to express constraints as they appear in the application and to write and combine constraint systems, a special purpose language for writing constraint systems called constraint handling rules (CHR) was developed. CHR have been used to encode a wide range of constraint handlers (solvers), including new domains such as terminological and temporal reasoning. Several CHR libraries exist in declarative languages such as Prolog and LISP, worldwide more than 20 projects use CHR. You can find more information about CHR in [Fruehwirth 98] or at URL: http://www.pst.informatik.uni-muenchen.de/personen/fruehwir/chr-intro.html

The high-level CHR are an excellent tool for rapid prototyping and implementation of constraint handlers. The usual abstract formalism to describe a constraint system, i.e. inference rules, rewrite rules, sequents, formulas expressing axioms and theorems, can be written as CHR in a straightforward way. Starting from this executable specification, the rules can be refined and adapted to the specifics of the application.

The CHR library includes a compiler, which translates CHR programs into Prolog programs on the fly, and a runtime system, which includes a stepper for debugging. Many constraint handlers are provided in the example directory of the library.

CHR are essentially a committed-choice language consisting of guarded rules that rewrite constraints into simpler ones until they are solved. CHR define both simplification of and propagation over constraints. Simplification replaces constraints by simpler constraints while preserving logical equivalence (e.g. X>Y,Y>X <=> fail). Propagation adds new constraints which are logically redundant but may cause further simplification (e.g. X>Y,Y>Z ==> X>Z). Repeatedly applying CHR incrementally simplifies and finally solves constraints (e.g. A>B,B>C,C>A) leads to fail.

With multiple heads and propagation rules, CHR provide two features which are essential for non-trivial constraint handling. The declarative reading of CHR as formulas of first order logic allows one to reason about their correctness. On the other hand, regarding CHR as a rewrite system on logical formulas allows one to reason about their termination and confluence.

In case the implementation of CHR disagrees with your expectations based on this chapter, drop a line to the current maintainer: christian@ai.univie.ac.at (Christian Holzbaur).


Node:CHR Introductory Examples, Next:, Previous:CHR Introduction, Up:CHR

Introductory Examples

We define a CHR constraint for less-than-or-equal, leq, that can handle variable arguments. This handler can be found in the library as the file leq.pl. (The code works regardless of options switched on or off.)

:- use_module(library(chr)).

handler leq.
constraints leq/2.
:- op(500, xfx, leq).

reflexivity  @ X leq Y <=> X=Y | true.
antisymmetry @ X leq Y , Y leq X <=> X=Y.
idempotence  @ X leq Y \ X leq Y <=> true.
transitivity @ X leq Y , Y leq Z ==> X leq Z.

The CHR specify how leq simplifies and propagates as a constraint. They implement reflexivity, idempotence, antisymmetry and transitivity in a straightforward way. CHR reflexivity states that X leq Y simplifies to true, provided it is the case that X=Y. This test forms the (optional) guard of a rule, a precondition on the applicability of the rule. Hence, whenever we see a constraint of the form A leq A we can simplify it to true.

The rule antisymmetry means that if we find X leq Y as well as Y leq X in the constraint store, we can replace it by the logically equivalent X=Y. Note the different use of X=Y in the two rules: In the reflexivity rule the equality is a precondition (test) on the rule, while in the antisymmetry rule it is enforced when the rule fires. (The reflexivity rule could also have been written as reflexivity X leq X <=> true.)

The rules reflexivity and antisymmetry are simplification CHR. In such rules, the constraints found are removed when the rule applies and fires. The rule idempotence is a simpagation CHR, only the constraints right of '\' will be removed. The rule says that if we find X leq Y and another X leq Y in the constraint store, we can remove one.

Finally, the rule transitivity states that the conjunction X leq Y, Y leq Z implies X leq Z. Operationally, we add X leq Z as (redundant) constraint, without removing the constraints X leq Y, Y leq Z. This kind of CHR is called propagation CHR.

Propagation CHR are useful, as the query A leq B,C leq A,B leq C illustrates: The first two constraints cause CHR transitivity to fire and add C leq B to the query. This new constraint together with B leq C matches the head of CHR antisymmetry, X leq Y, Y leq X. So the two constraints are replaced by B=C. Since B=C makes B and C equivalent, CHR antisymmetry applies to the constraints A leq B, C leq A, resulting in A=B. The query contains no more CHR constraints, the simplification stops. The constraint handler we built has solved A leq B, C leq A, B leq C and produced the answer A=B, B=C:

A leq B,C leq A,B leq C.
% C leq A, A leq B propagates C leq B by transitivity.
% C leq B, B leq C simplifies to B=C by antisymmetry.
% A leq B, C leq A simplifies to A=B by antisymmetry since B=C.
A=B,B=C.

Note that multiple heads of rules are essential in solving these constraints. Also note that this handler implements a (partial) order constraint over any constraint domain, this generality is only possible with CHR.

As another example, we can implement the sieve of Eratosthenes to compute primes simply as (for variations see the handler primes.pl):

:- use_module(library(chr)).
handler eratosthenes.
constraints primes/1,prime/1.

primes(1) <=> true.
primes(N) <=> N>1 | M is N-1,prime(N),primes(M). % generate candidates

absorb(J) @ prime(I) \ prime(J) <=> J mod I =:= 0 | true.

The constraint primes(N) generates candidates for prime numbers, prime(M), where M is between 1 and N. The candidates react with each other such that each number absorbs multiples of itself. In the end, only prime numbers remain.

Looking at the two rules defining primes/1, note that head matching is used in CHR, so the first rule will only apply to primes(1). The test N>1 is a guard (precondition) on the second rule. A call with a free variable, like primes(X), will delay (suspend). The third, multi-headed rule absorb(J) reads as follows: If there is a constraint prime(I) and some other constraint prime(J) such that J mod I =:= 0 holds, i.e. J is a multiple of I, then keep prime(I) but remove prime(J) and execute the body of the rule, true.


Node:CHR Library, Next:, Previous:CHR Introductory Examples, Up:CHR

CHR Library

CHR extend the Prolog syntax by a few constructs introduced in the next sections. Technically, the extension is achieved through the user:term_expansion/2 mechanism. A file that contains a constraint handler may also contain arbitrary Prolog code. Constraint handling rules can be scattered across a file. Declarations and options should precede rules. There can only be at most one constraint handler per module.


Node:CHR Loading the Library, Next:, Previous:CHR Library, Up:CHR Library

Loading the Library

Before you can load or compile any file containing a constraint handler (solver) written in CHR, the chr library module has to be imported:

| ?- use_module(library(chr)).
It is recommended to include the corresponding directive at the start of your files containing handlers:
  :- use_module(library(chr)).


Node:CHR Declarations, Next:, Previous:CHR Loading the Library, Up:CHR Library

Declarations

Declarations in files containing CHR affect the compilation and thus the behavior of the rules at runtime.

The mandatory handler declaration precedes any other CHR specific code. Example:

handler minmax.
A handler name must be a valid Prolog atom. Per module, only one constraint handler can be defined.

The constraints must be declared before they are used by rules. With this mandatory declaration one lists the constraints the rules will later talk about. The declaration can be used more than once per handler. Example:

constraints  leq/2, minimum/3, maximum/3.

The following optional declaration allows for conditional rule compilation. Only the rules mentioned get compiled. Rules are referred to by their names (see CHR Syntax). The latest occurrence takes precedence if used more than once per handler. Although it can be put anywhere in the handler file, it makes sense, as with other declarations, to use it early. Example:

rules antisymmetry, transitivity.

To simplify the handling of operator declarations, in particular during fcompile/1, operator/3 declarations with the same denotation as op/3, but taking effect during compilation and loading, are helpful. Example:

operator(700, xfx, ::).
operator(600, xfx, :).


Node:CHR Syntax, Next:, Previous:CHR Declarations, Up:CHR Library

Constraint Handling Rules, Syntax

A constraint handling rule has one or more heads, an optional guard, a body and an optional name. A Head is a Constraint. A constraint is a callable Prolog term, whose functor is a declared constraint. The Guard is a Prolog goal. The Body of a rule is a Prolog goal (including constraints). A rule can be named with a Name which can be any Prolog term (including variables from the rule).

There are three kinds of constraint handling rules:

Rule           --> [Name @]
                     (Simplification | Propagation | Simpagation)
                        [pragma Pragma].

Simplification --> Heads         <=> [Guard '|'] Body
Propagation    --> Heads         ==> [Guard '|'] Body
Simpagation    --> Heads \ Heads <=> [Guard '|'] Body

Heads          --> Head | Head, Heads
Head           --> Constraint | Constraint # Id
Constraint     --> a callable term declared as constraint
Id             --> a unique variable

Guard          --> Ask | Ask & Tell
Ask            --> Goal
Tell           --> Goal
Goal           --> a callable term, including conjunction and disjunction etc.

Body           --> Goal

Pragma         --> a conjunction of terms usually referring to
                   one or more heads identified via #/2

The symbol | separates the guard (if present) from the body of a rule. Since | is read as ; (disjunction) by the reader, care has to be taken when using disjunction in the guard or body of the rule. The top-level disjunction will always be interpreted as guard-body separator |, so proper bracketing has to be used, e.g. a <=> (b;c) | (d;e) instead of a <=> b;c | d;e and a <=> true | (d;e) instead of a <=> (d;e).

In simpagation rules, \ separates the heads of the rule into two parts.

Individual head constraints may be tagged with variables via #, which may be used as identifiers in pragma declarations, for example. Constraint identifiers must be distinct variables, not occurring elsewhere in the heads.

Guards test the applicability of a rule. Guards come in two parts, tell and ask, separated by &. If the & operator is not present, the whole guard is assumed to be of the ask type.

Declaratively, a rule relates heads and body provided the guard is true. A simplification rule means that the heads are true if and only if the body is true. A propagation rule means that the body is true if the heads are true. A simpagation rule combines a simplification and a propagation rule. The rule Heads1 \ Heads2 <=> Body is equivalent to the simplification rule Heads1, Heads2 <=> Heads1, Body. However, the simpagation rule is more compact to write, more efficient to execute and has better termination behavior than the corresponding simplification rule, since the constraints comprising Heads1 will not be removed and inserted again.


Node:How CHR work, Next:, Previous:CHR Syntax, Up:CHR Library

How CHR work

Each CHR constraint is associated with all rules in whose heads it occurs by the CHR compiler. Every time a CHR constraint is executed (called) or woken and reconsidered, it checks itself the applicability of its associated CHR by trying each CHR. By default, the rules are tried in textual order, i.e. in the order they occur in the defining file. To try a CHR, one of its heads is matched against the constraint. Matching succeeds if the constraint is an instance of the head. If a CHR has more than one head, the constraint store is searched for partner constraints that match the other heads. Heads are tried from left to right, except that in simpagation rules, the heads to be removed are tried before the head constraints to be kept (this is done for efficiency reasons). If the matching succeeds, the guard is executed. Otherwise the next rule is tried.

The guard either succeeds or fails. A guard succeeds if the execution of its Ask and Tell parts succeeds and in the ask part no variable that occurs also in the heads was touched or the cause of an instantiation error. The ask guard will fail otherwise. A variable is touched if it is unified with a term (including other variables from other constraints) different from itself. Tell guards, on the contrary, are trusted and not checked for that property. If the guard succeeds, the rule applies. Otherwise the next rule is tried.

If the firing CHR is a simplification rule, the matched constraints are removed from the store and the body of the CHR is executed. Similarly for a firing simpagation rule, except that the constraints that matched the heads preceding \ are kept. If the firing CHR is a propagation rule the body of the CHR is executed without removing any constraints. It is remembered that the propagation rule fired, so it will not fire again with the same constraints if the constraint is woken and reconsidered. If the currently active constraint has not been removed, the next rule is tried.

If the current constraint has not been removed and all rules have been tried, it delays until a variable occurring in the constraint is touched. Delaying means that the constraint is inserted into the constraint store. When a constraint is woken, all its rules are tried again. (This process can be watched and inspected with the CHR debugger, see below.)


Node:CHR Pragmas, Next:, Previous:How CHR work, Up:CHR Library

Pragmas

Pragmas are annotations to rules and constraints that enable the compiler to generate more specific, more optimized code. A pragma can be a conjunction of the following terms:


already_in_heads
The intention of simplification and simpagation rules is often to combine the heads into a stronger version of one of them. Depending on the strength of the guard, the new constraint may be identical to one of the heads to removed by the rule. This removal followed by addition is inefficient and may even cause termination problems. If the pragma is used, this situation is detected and the corresponding problems are avoided. The pragma applies to all constraints removed by the rule.
already_in_head(Id)
Shares the intention of the previous pragma, but affects only the constraint indicated via Id. Note that one can use more than one pragma per rule.
passive(Id)
No code will be generated for the specified constraint in the particular head position. This means that the constraint will not see the rule, it is passive in that rule. This changes the behavior of the CHR system, because normally, a rule can be entered starting from each head constraint. Usually this pragma will improve the efficiency of the constraint handler, but care has to be taken in order not to lose completeness.

For example, in the handler leq, any pair of constraints, say A leq B, B leq A, that matches the head X leq Y , Y leq X of the antisymmetry rule, will also match it when the constraints are exchanged, B leq A, A leq B. Therefore it is enough if a currently active constraint enters this rule in the first head only, the second head can be declared to be passive. Similarly for the idempotence rule. For this rule, it is more efficient to declare the first head passive, so that the currently active constraint will be removed when the rule fires (instead of removing the older constraint and redoing all the propagation with the currently active constraint). Note that the compiler itself detects the symmetry of the two head constraints in the simplification rule antisymmetry, thus it is automatically declared passive and the compiler outputs CHR eliminated code for head 2 in antisymmetry.

antisymmetry  X leq Y , Y leq X # Id <=> X=Y pragma passive(Id).
idempotence   X leq Y # Id \ X leq Y <=> true pragma passive(Id).
transitivity  X leq Y # Id , Y leq Z ==> X leq Z pragma passive(Id).
Declaring the first head of rule transitivity passive changes the behavior of the handler. It will propagate less depending on the order in which the constraints arrive:
?- X leq Y, Y leq Z.
X leq Y,
Y leq Z,
X leq Z ?

?- Y leq Z, X leq Y.
Y leq Z,
X leq Y ?

?- Y leq Z, X leq Y, Z leq X.
Y = X,
Z = X ?
The last query shows that the handler is still complete in the sense that all circular chains of leq-relations are collapsed into equalities.


Node:CHR Options, Next:, Previous:CHR Pragmas, Up:CHR Library

Options

Options parametrise the rule compilation process. Thus they should precede the rule definitions. Example:

option(check_guard_bindings, off).

The format below lists the names of the recognized options together with the acceptable values. The first entry in the lists is the default value.


option(debug_compile, [off,on]).
Instruments the generated code such that the execution of the rules may be traced (see CHR Debugging).
option(check_guard_bindings, [on,off]).
Per default, for guards of type ask the CHR runtime system makes sure that no variables are touched or the cause of an instantiation error. These checks may be turned off with this option, i.e. all guards are treated as if they were of the tell variety. The option was kept for backward compatibility. Tell and ask guards offer better granularity.
option(already_in_store, [off,on]).
If this option is on, the CHR runtime system checks for the presence of an identical constraint upon the insertion into the store. If present, the attempted insertion has no effect. Since checking for duplicates for all constraints costs, duplicate removal specific to individual constraints, using a few simpagation rules of the following form instead, may be a better solution.
Constraint \ Constraint <=> true.

option(already_in_heads, [off,on]).
The intention of simplification and simpagation rules is often to combine the heads into a stronger version of one of them. Depending on the strength of the guard, the new constraint may be identical to one of the heads removed by the rule. This removal followed by addition is inefficient and may even cause termination problems. If the option is enabled, this situation is detected and the corresponding problems are avoided. This option applies to all constraints and is provided mainly for backward compatibility. Better grained control can be achieved with corresponding pragmas. (see CHR Pragmas).

The remaining options are meant for CHR implementors only:

option(flatten, [on,off]).
option(rule_ordering, [canonical,heuristic]).
option(simpagation_scheme, [single,multi]).
option(revive_scheme, [new,old]).
option(dead_code_elimination, [on,off]).


Node:CHR Built-In Predicates, Next:, Previous:CHR Options, Up:CHR Library

Built-In Predicates

This table lists the predicates made available by the CHR library. They are meant for advanced users, who want to tailor the CHR system towards their specific needs.

current_handler(?Handler, ?Module)

Non-deterministically enumerates the defined handlers with the module they are defined in.

current_constraint(?Handler, ?Constraint)

Non-deterministically enumerates the defined constraints in the form Functor/Arity and the handlers they are defined in.

insert_constraint(+Constraint, -Id)

Inserts Constraint into the constraint store without executing any rules. The constraint will be woken and reconsidered when one of the variables in Constraint is touched. Id is unified with an internal object representing the constraint. This predicate only gets defined when a handler and constraints are declared (see CHR Declarations).

insert_constraint(+Constraint, -Id, ?Term)

Inserts Constraint into the constraint store without executing any rules. The constraint will be woken and reconsidered when one of the variables in Term is touched. Id is unified with an internal object representing the constraint. This predicate only gets defined when a handler and constraints are declared (see CHR Declarations).

find_constraint(?Pattern, -Id)

Non-deterministically enumerates constraints from the constraint store that match Pattern, i.e. which are instances of Pattern. Id is unified with an internal object representing the constraint.

find_constraint(-Var, ?Pattern, -Id)

Non-deterministically enumerates constraints from the constraint store that delay on Var and match Pattern, i.e. which are instances of Pattern. The identifier Id can be used to refer to the constraint later, e.g. for removal.

findall_constraints(?Pattern, ?List)

Unifies List with a list of Constraint # Id pairs from the constraint store that match Pattern.

findall_constraints(-Var, ?Pattern, ?List)

Unifies List with a list of Constraint # Id pairs from the constraint store that delay on Var and match Pattern.

remove_constraint(+Id)

Removes the constraint Id, obtained with one of the previous predicates, from the constraint store.

unconstrained(?Var)

Succeeds if no CHR constraint delays on Var. Defined as:

unconstrained(X) :-
    find_constraint(X, _, _), !, fail.
unconstrained(_).

notify_constrained(?Var)

Leads to the reconsideration of the constraints associated with Var. This mechanism allows solvers to communicate reductions on the set of possible values of variables prior to making bindings.


Node:CHR Consulting and Compiling, Next:, Previous:CHR Built-In Predicates, Up:CHR Library

Consulting and Compiling Constraint Handlers

The CHR compilation process has been made as transparent as possible. The user deals with files containing CHR just as with files containing ordinary Prolog predicates. Thus CHR may be consulted, compiled with various compilation modes, and compiled to file (see Load Intro).


Node:CHR Compiler-generated Predicates, Next:, Previous:CHR Consulting and Compiling, Up:CHR Library

Compiler-generated Predicates

Besides predicates for the defined constraints, the CHR compiler generates some support predicates in the module containing the handler. To avoid naming conflicts, the following predicates must not be defined or referred to by user code in the same module:

verify_attributes/3
attribute_goal/2
attach_increment/2
'attach_F/A'/2
for every defined constraint F/A.
'F/A_N_M_...'/Arity
for every defined constraint F/A. N,M is are integers, Arity > A.

For the prime number example that is:

        attach_increment/2
        attach_prime/1/2
        attach_primes/1/2
        attribute_goal/2
        goal_expansion/3
        prime/1
        prime/1_1/2
        prime/1_1_0/3
        prime/1_2/2
        primes/1
        primes/1_1/2
        verify_attributes/3

If an author of a handler wants to avoid naming conflicts with the code that uses the handler, it is easy to encapsulate the handler. The module declaration below puts the handler into module primes, which exports only selected predicates - the constraints in our example.

        :- module(primes, [primes/1,prime/1]).

        :- use_module(library(chr)).

        handler eratosthenes.
        constraints primes/1,prime/1.
        ...


Node:CHR Operator Declarations, Next:, Previous:CHR Compiler-generated Predicates, Up:CHR Library

Operator Declarations

This table lists the operators as used by the CHR library:

:- op(1200, xfx, @).
:- op(1190, xfx, pragma).
:- op(1180, xfx, [==>,<=>]).
:- op(1180, fy,  chr_spy).
:- op(1180, fy,  chr_nospy).
:- op(1150, fx,  handler).
:- op(1150, fx,  constraints).
:- op(1150, fx,  rules).
:- op(1100, xfx, '|').
:- op(1100, xfx, \ ).
:- op(1050, xfx, &).
:- op( 500, yfx, #).


Node:CHR Exceptions, Previous:CHR Operator Declarations, Up:CHR Library

Exceptions

The CHR runtime system reports instantiation and type errors for the predicates:

find_constraint/2
findall_constraints/3
insert_constraint/2
remove_constraint/1
notify_constrained/1

The only other CHR specific runtime error is:

{CHR ERROR: registering <New>, module <Module> already hosts <Old>}
An attempt to load a second handler New into module <Module> already hosting handler <Old> was made.

The following exceptional conditions are detected by the CHR compiler:

{CHR Compiler ERROR: syntax rule <N>: <Term>}
If the N-th <Term> in the file being loaded violates the CHR syntax (see CHR Syntax).
{CHR Compiler ERROR: too many general heads in <Name>}
Unspecific heads in definitions like C \ C <=> true must not be combined with other heads in rule <Name>.
{CHR Compiler ERROR: bad pragma <Pragma> in <Name>}
The pragma <Pragma> used in rule <Name> does not qualify. Currently this only happens if <Pragma> is unbound.
{CHR Compiler ERROR: found head <F/A> in <Name>, expected one of: <F/A list>}
Rule <Name> has a head of given F/A which is not among the defined constraints.
{CHR Compiler ERROR: head identifiers in <Name> are not unique variables}
The identifiers to refer to individual constraints (heads) via # in rule <Name> do not meet the indicated requirements.
{CHR Compiler ERROR: no handler defined}
CHR specific language elements, declarations or rules for example, are used before a handler was defined. This error is usually reported a couple of times, i.e. as often as there are CHR forms in the file expecting the missing definition.
{CHR Compiler ERROR: compilation failed}
Not your fault. Send us a bug report.


Node:CHR Debugging, Next:, Previous:CHR Library, Up:CHR

Debugging CHR Programs

Use option(debug_compile,on) preceding any rules in the file containing the handler to enable CHR debugging. The CHR debugging mechanism works by instrumenting the code generated by the CHR compiler. Basically, the CHR debugger works like the Prolog debugger. The main differences are: there are extra ports specific to CHR, and the CHR debugger provides no means for the user to change the flow of control, i.e. there are currently no retry and fail options available.


Node:CHR Control Flow Model, Next:, Previous:CHR Debugging, Up:CHR Debugging

Control Flow Model

The entities reflected by the CHR debugger are constraints and rules. Constraints are treated like ordinary Prolog goals with the usual ports: [call,exit,redo,fail]. In addition, constraints may get inserted into or removed from the constraint store (ports: insert,remove), and stored constraints containing variables will be woken and reconsidered (port: wake) when variables are touched.

The execution of a constraint consists of trying to apply the rules mentioning the constraint in their heads. Two ports for rules reflect this process: At a try port the active constraint matches one of the heads of the rule, and matching constraints for the remaining heads of the rule, if any, have been found as well. The transition from a try port to an apply port takes place when the guard has been successfully evaluated, i.e. when the rule commits. At the apply port, the body of the rule is just about to be executed. The body is a Prolog goal transparent to the CHR debugger. If the rule body contains CHR constraints, the CHR debugger will track them again. If the rules were consulted, the Prolog debugger can be used to study the evaluations of the other predicates in the body.


Node:CHR Debugging Predicates, Next:, Previous:CHR Control Flow Model, Up:CHR Debugging

CHR Debugging Predicates

The following predicates control the operation of the CHR debugger:

chr_trace

Switches the CHR debugger on and ensures that the next time control enters a CHR port, a message will be produced and you will be asked to interact.

At this point you have a number of options. See CHR Debugging Options. In particular, you can just type <cr> (Return) to creep (or single-step) into your program. You will notice that the CHR debugger stops at many ports. If this is not what you want, the predicate chr_leash gives full control over the ports at which you are prompted.

chr_debug

Switches the CHR debugger on and ensures that the next time control enters a CHR port with a spypoint set, a message will be produced and you will be asked to interact.

chr_nodebug

Switches the CHR debugger off. If there are any spypoints set then they will be kept.

chr_notrace

Equivalent to chr_nodebug.

chr_debugging

Prints onto the standard error stream information about the current CHR debugging state. This will show:

  1. Whether the CHR debugger is switched on.
  2. What spypoints have been set (see below).
  3. What mode of leashing is in force (see below).

chr_leash(+Mode)

The leashing mode is set to Mode. It determines the CHR ports at which you are to be prompted when you creep through your program. At unleashed ports a tracing message is still output, but program execution does not stop to allow user interaction. Note that the ports of spypoints are always leashed (and cannot be unleashed). Mode is a list containing none, one or more of the following port names:

call
Prompt when a constraint is executed for the first time.
exit
Prompt when the constraint is successfully processed, i.e. the applicable rules have applied.
redo
Prompt at subsequent exits generated by nondeterminate rule bodies.
fail
Prompt when a constraint fails.
wake
Prompt when a constraint from the constraint store is woken and reconsidered because one of its variables has been touched.
try
Prompt just before the guard evaluation of a rule, after constraints matching the heads have been found.
apply
Prompt upon the application of a rule, after the successful guard evaluation, when the rule commits and fires, just before evaluating the body.
insert
Prompt when a constraint gets inserted into the constraint store, i.e. after all rules have been tried.
remove
Prompt when a constraint gets removed from the constraint store, e.g. when a simplification rule applies.

The initial value of the CHR leashing mode is [call,exit,fail,wake,apply]. Predefined shortcuts are:

chr_leash(none), chr_leash(off)
To turn leashing off.
chr_leash(all)
To prompt at every port.
chr_leash(default)
Same as chr_leash([call,exit,fail,wake,apply]).
chr_leash(call)
No need to use a list if only a singular port is to be leashed.


Node:CHR spypoints, Next:, Previous:CHR Debugging Predicates, Up:CHR Debugging

CHR spypoints

For CHR programs of any size, it is clearly impractical to creep through the entire program. Spypoints make it possible to stop the program upon an event of interest. Once there, one can set further spypoints in order to catch the control flow a bit further on, or one can start creeping.

Setting a spypoint on a constraint or a rule indicates that you wish to see all control flow through the various ports involved, except during skips. When control passes through any port with a spypoint set on it, a message is output and the user is asked to interact. Note that the current mode of leashing does not affect spypoints: user interaction is requested on every port.

Spypoints are set and removed by the following predicates, which are declared as prefix operators:

chr_spy Spec

Sets spypoints on constraints and rules given by Spec, which is is of the form:

_ (variable)
denoting all constraints and rules, or:
constraints Cs
where Cs is one of

_ (variable)
denoting all constraints
C,...,C
denoting a list of constraints C
Name
denoting all constraints with this functor, regardless of arity
Name/Arity
denoting the constraint of that name and arity

rules Rs
where Rs is one of:

_ (variable)
denoting all rules
R,...,R
denoting a list of rules R
Name
where Name is the name of a rule in any handler.
already_in_store
The name of a rule implicitly defined by the system when the option already_in_store is in effect.
already_in_heads
The name of a rule implicitly defined by the system when the option already_in_heads or the corresponding pragmas are in effect.
Handler:Name
where Handler is the name of a constraint handler and Name is the name of a rule in that handler

Examples:

| ?- chr_spy rules rule(3), transitivity, already_in_store.
| ?- chr_spy constraints prime/1.

If you set spypoints, the CHR debugger will be switched on.

chr_nospy Spec

Removes spypoints on constraints and rules given by Spec, where Spec is of the form as described for chr_spy Spec. There is no chr_nospyall/0. To remove all CHR spypoints use chr_nospy _.

The options available when you arrive at a spypoint are described later. See CHR Debugging Options.


Node:CHR Debugging Messages, Next:, Previous:CHR spypoints, Up:CHR Debugging

CHR Debugging Messages

All trace messages are output to the standard error stream. This allows you to trace programs while they are performing file I/O. The basic format is as follows:

S 3   1 try     eratosthenes:absorb(10) @ prime(9)#<c4>, prime(10)#<c2> ?

S is a spypoint indicator. It is printed as if there is no spypoint, as r, indicating that there is a spypoint on this rule, or as c if one of the involved constraints has a spypoint.

The first number indicates the current depth of the execution; i.e. the number of direct ancestors the currently active constraint has.

The second number indicates the head position of the currently active constraint at rule ports.

The next item tells you which port is currently traced.

A constraint or a matching rule are printed next. Constraints print as Term#Id, where Id is a unique identifier pointing into the constraint store. Rules are printed as Handler:Name @, followed by the constraints matching the heads.

The final ? is the prompt indicating that you should type in one of the debug options (see CHR Debugging Options).


Node:CHR Debugging Options, Previous:CHR Debugging Messages, Up:CHR Debugging

CHR Debugging Options

This section describes the options available when the system prompts you after printing out a debugging message. Most of them you know from the standard Prolog debugger. All the options are one letter mnemonics, some of which can be optionally followed by a decimal integer. They are read from the standard input stream up to the end of the line (Return, <<cr>>). Blanks will be ignored.

The only option which you really have to remember is h. This provides help in the form of the following list of available options.

CHR debugging options:
   <cr>   creep            c      creep
    l     leap
    s     skip             s <i>  skip (ancestor i)
    g     ancestors
    &     constraints      & <i>  constraints (details)
    n     nodebug          =      debugging
    +     spy this
    -     nospy this       .      show rule
    <     reset printdepth < <n>  set printdepth
    a     abort            b      break
    ?     help             h      help
c
<<cr>>
creep causes the debugger to single-step to the very next port and print a message. Then if the port is leashed, the user is prompted for further interaction. Otherwise, it continues creeping. If leashing is off, creep is the same as leap (see below) except that a complete trace is printed on the standard error stream.
l
leap causes the debugger to resume running your program, only stopping when a spypoint is reached (or when the program terminates). Leaping can thus be used to follow the execution at a higher level than exhaustive tracing.
s
s i
skip over the entire execution of the constraint. That is, you will not see anything until control comes back to this constraint (at either the exit port or the fail port). This includes ports with spypoints set; they will be masked out during the skip. The command can be used with a numeric argument to skip the execution up to and including the ancestor indicated by the argument. Example:
      ...
      4   - exit    prime(8)#<c6> ? g
Ancestors:
      1   1 apply   eratosthenes:rule(2) @ primes(10)#<c1>
      2   1 apply   eratosthenes:rule(2) @ primes(9)#<c3>
      3   1 apply   eratosthenes:rule(2) @ primes(8)#<c5>
      4   - call    prime(8)#<c6>

      4   - exit    prime(8)#<c6> ? s 2
      2   - exit    primes(9)#<c3> ?

g
print ancestors provides you with a list of ancestors to the currently active constraint, i.e. all constraints not yet exited that led to the current constraint in the derivation sequence. The format is the same as with trace messages. Constraints start with call entries in the stack. The subsequent application of a rule replaces the call entry in the stack with an apply entry. Later the constraint shows again as redo or fail entry. Example:
      0   - call    primes(10)#<c1> ?
      1   1 try     eratosthenes:rule(2) @ primes(10)#<c1> ? g

Ancestors:
      1   - call    primes(10)#<c1>

      1   1 try     eratosthenes:rule(2) @ primes(10)#<c1> ?
      1   1 apply   eratosthenes:rule(2) @ primes(10)#<c1> ?
      1   - call    prime(10)#<c2> ?
      2   - insert  prime(10)#<c2>
      2   - exit    prime(10)#<c2> ? g

Ancestors:
      1   1 apply   eratosthenes:rule(2) @ primes(10)#<c1>
      2   - call    prime(10)#<c2>

&
print constraints prints a list of the constraints in the constraint store. With a numeric argument, details relevant primarily to CHR implementors are shown.
n
nodebug switches the CHR debugger off.
=
debugging outputs information concerning the status of the CHR debugger as via chr_debugging/0
+
spy this sets a spypoint on the current constraint or rule.
-
nospy this removes the spypoint from the current constraint or rule, if it exists.
.
show rule prints the current rule instantiated by the matched constraints. Example:
 8   1 apply   era:absorb(8) @ prime(4)#<c14> \ prime(8)#<c6> ? .

 absorb(8) @
  prime(4)#<c14> \
    prime(8)#<c6> <=>

    8 mod 4=:=0
    |
    true.

<
< n
While in the debugger, a printdepth is in effect for limiting the subterm nesting level when printing rules and constraints. The limit is initially 10. This command, without arguments, resets the limit to 10. With an argument of n, the limit is set to n, treating 0 as infinity.
a
abort calls the built-in predicate abort/0.
b
break calls the built-in predicate break/0, thus putting you at a recursive top-level. When you end the break (entering ^D) you will be re-prompted at the port at which you broke. The CHR debugger is temporarily switched off as you call the break and will be switched on again when you finish the break and go back to the old execution. Any changes to the CHR leashing or to spypoints during the break will remain in effect.
?
h
help displays the table of options given above.


Node:CHR Programming Hints, Next:, Previous:CHR Debugging, Up:CHR

Programming Hints

This section gives you some programming hints for CHR. For maximum efficiency of your constraint handler, see also the previous subsections on declarations and options.

Constraint handling rules for a given constraint system can often be derived from its definition in formalisms such as inference rules, rewrite rules, sequents, formulas expressing axioms and theorems. CHR can also be found by first considering special cases of each constraint and then looking at interactions of pairs of constraints sharing a variable. Cases that do not occur in the application can be ignored.

It is important to find the right granularity of the constraints. Assume one wants to express that n variables are different from each other. It is more efficient to have a single constraint all_different(List_of_n_Vars) than n*n inequality constraints between each pair of different variables. However, the extreme case of having a single constraint modeling the whole constraint store will usually be inefficient.

Starting from an executable specification, the rules can then be refined and adapted to the specifics of the application. Efficiency can be improved by weakening the guards to perform simplification as early as needed and by strengthening the guards to do the just right amount of propagation. Propagation rules can be expensive, because no constraints are removed.

The more heads a rule has, the more expensive it is. Rules with several heads are more efficient, if the heads of the rule share a variable (which is usually the case). Then the search for a partner constraint has to consider less candidates. In the current implementation, constraints are indexed by their functors, so that the search is only performed among the constraints containing the shared variable. Moreover, two rules with identical (or sufficiently similar) heads can be merged into one rule so that the search for a partner constraint is only performed once instead of twice.

As guards are tried frequently, they should be simple tests not involving side-effects. Head matching is more efficient than explicitly checking equalities in the ask-part of the guard. In the tell part of a guard, it should be made sure that variables from the head are never touched (e.g. by using nonvar or ground if necessary). For efficiency and clarity reasons, one should also avoid using constraints in guards. Besides conjunctions, disjunctions are allowed in the guard, but they should be used with care. The use of other control built-in predicates in the guard is discouraged. Negation and if-then-else in the ask part of a guard can give wrong results, since e.g. failure of the negated goal may be due to touching its variables.

Several handlers can be used simultaneously if they do not share constraints with the same name. The implementation will not work correctly if the same constraint is defined in rules of different handlers that have been compiled separately. In such a case, the handlers must be merged by hand. This means that the source code has to be edited so that the rules for the shared constraint are together (in one module). Changes may be necessary (like strengthening guards) to avoid divergence or loops in the computation.


Node:CHR Constraint Handlers, Next:, Previous:CHR Programming Hints, Up:CHR

Constraint Handlers

The CHR library comes with plenty of constraint handlers written in CHR. The most recent versions of these are maintained at:

http://www.pst.informatik.uni-muenchen.de/~fruehwir/chr-solver.html

arc.pl
classical arc-consistency over finite domains
bool.pl
simple Boolean constraints
cft.pl
feature term constraints according to the CFT theory
domain.pl
finite domains over arbitrary ground terms and interval domains over integers and reals, but without arithmetic functions
gcd.pl
elegant two-liner for the greatest common divisor
interval.pl
straightforward interval domains over integers and reals, with arithmetic functions
kl-one.pl
terminological reasoning similar to KL-ONE or feature trees
leq.pl
standard introductory CHR example handler for less-than-or-equal
list.pl
equality constraints over concatenations of lists (or strings)
listdom.pl
a straightforward finite enumeration list domains over integers, similar to interval.pl
math-elim.pl
solves linear polynomial equations and inequations using variable elimination, several variations possible
math-fougau.pl
solves linear polynomial equations and inequations by combining variable elimination for equations with Fourier's algorithm for inequations, several variations possible
math-fourier.pl
a straightforward Fouriers algorithm to solve polynomial inequations over the real or rational numbers
math-gauss.pl
a straightforward, elegant implementation of variable elimination for equations in one rule
minmax.pl
simple less-than and less-than-or-equal ordering constraints together with minimum and maximum constraints
modelgenerator.pl
example of how to use CHR for model generation in theorem proving
monkey.pl
classical monkey and banana problem, illustrates how CHR can be used as a fairly efficient production rule system
osf.pl
constraints over order sorted feature terms according to the OSF theory
oztype.pl
rational trees with disequality and OZ type constraint with intersection
pathc.pl
the most simple example of a handler for path consistency - two rules
primes.pl
elegant implementations of the sieve of Eratosthenes reminiscent of the chemical abstract machine model, also illustrates use of CHR as a general purpose concurrent constraint language
scheduling.pl
simple classical constraint logic programming scheduling example on building a house
tarski.pl
most of Tarski's axiomatization of geometry as constraint system
term.pl
Prolog term manipulation built-in predicates functor/3, arg/3, =../2 as constraints
time-pc.pl
grand generic handler for path-consistency over arbitrary constraints, load via time.pl to get a powerful solver for temporal constraints based on Meiri's unifying framework. time-rnd.pl contains a generator for random test problems.
time-point.pl
quantitative temporal constraints over time points using path-consistency
tree.pl
equality and disequality over finite and infinite trees (terms)
type.pl
equalities and type constraints over finite and infinite trees (terms)

You can consult or compile a constraint handler from the CHR library using e.g.:

?- [library('chr/examples/gcd')].
?- compile(library('chr/examples/gcd')).
If you want to learn more about the handlers, look at their documented source code.

In addition, there are files with example queries for some handlers, their file name starts with examples- and the file extension indicates the handler, e.g. .bool:

examples-adder.bool
examples-benchmark.math
examples-deussen.bool
examples-diaz.bool
examples-fourier.math
examples-holzbaur.math
examples-lim1.math
examples-lim2.math
examples-lim3.math
examples-puzzle.bool
examples-queens.bool
examples-queens.domain
examples-stuckey.math
examples-thom.math


Node:CHR Backward Compatibility, Previous:CHR Constraint Handlers, Up:CHR

Backward Compatibility

In this section, we discuss backward compatibility with the CHR library of Eclipse Prolog.

  1. The restriction on at most two heads in a rule has been abandoned. A rule can have as many heads as you like. Note however, that searching for partner constraints can be expensive.
  2. By default, rules are compiled in textual order. This gives the programmer more control over the constraint handling process. In the Eclipse library of CHR, the compiler was optimizing the order of rules. Therefore, when porting a handler, rules may have to be reordered. A good heuristic is to prefer simplification to simpagation and propagation and to prefer rules with single heads to rules with several heads. Instead of manually rearranging an old handler one may also use the following combination of options to get the corresponding effect:
    option(rule_ordering,heuristic).
    option(revive_scheme,old).
    
  3. For backward compatibility, the already_in_store, already_in_head and guard_bindings options are still around, but there are CHR syntax extensions: CHR Syntax and pragmas CHR Pragmas offering better grained control.
  4. The Eclipse library of CHR provided automatic built-in labeling through the label_with declaration. Since it was not widely used and can be easily simulated, built-in labeling was dropped. The same effect can be achieved by replacing the declaration label_with Constraint if Guard by the simplification rule chr_labeling, Constraint <=> Guard | Constraint', chr_labeling and by renaming the head in each clause Constraint :- Body into Constraint' :- Body where Constraint' is a new predicate. Efficiency can be improved by declaring Constraint to be passive: chr_labeling, Constraint#Id <=> Guard | Constraint', chr_labeling pragma passive(Id). This translation will not work if option(already_in_heads,on). In that case use e.g. chr_labeling(_), Constraint <=> Guard | Constraint', chr_labeling(_) to make the new call to chr_labeling differ from the head occurrence.
  5. The set of built-in predicates for advanced CHR users is now larger and better designed. Also the debugger has been improved. The Opium debugging environment is not available in SICStus Prolog.


Node:FDBG, Next:, Previous:CHR, Up:Top

Finite Domain Constraint Debugger


Node:FDBG Introduction, Next:, Up:FDBG

Introduction

FDBG is a CLP(FD) debugger for SICStus Prolog. Its main purpose is to enable the CLP programmer to trace the changes of domains of variables.

To load the package, enter the query

| ?- use_module(library(fdbg)).

FDBG defines the following prefix operator:

:- op(400, fy, #).

The presence of FDBG affects the translation and execution, but not the semantics, of subsequently loaded arithmetic constraints.


Node:FDBG Concepts, Next:, Previous:FDBG Introduction, Up:FDBG

Concepts

In this section, several concepts and terms are defined. These terms will later be heavily used in the documentation; therefore, it is important that you understand them well.


Node:FDBG Events, Next:, Previous:FDBG Concepts, Up:FDBG Concepts

Events

An FDBG event can (currently) belong to one of the two following major classes:

constraint event
A global constraint is woken.
labeling event
Three events belong to this class, namely:

These events are intercepted by the FDBG core. When any of them occurs, the appropriate visualizer (see FDBG Visualizers) gets called with a representation of the event (a Prolog term) as extra arguments.

Note that it is not possible to debug indexicals with FDBG. What's more, any domain narrowings done by indexicals happen unnoticed, making FDBG output harder to follow. On the other hand, arithmetical constraints (like X #> 0) are translated to global constraints instead of indexicals after consulting library(fdbg), and therefore don't lead to any misunderstandings. For this latter reason it is advisable to load library(fdbg) before any user programs.


Node:FDBG Labeling Levels, Next:, Previous:FDBG Events, Up:FDBG Concepts

Labeling Levels

In this subsection we give three definitions regarding the labeling procedure.

labeling session
This term denotes the whole labeling procedure that starts with the call of labeling/2 or an equivalent predicate and finishes by exiting this predicate. Normally, there is at most one labeling session per run.
labeling attempt
One choicepoint of a labeling session. Exactly one variable is associated with a labeling attempt, although this is not necessarily true vice versa. For example in enum mode labeling, a single labeling attempt tries every possible value, but in step mode labeling, several binary choicepoints are created.
labeling step
The event of somehow constraining the domain of a variable. This usually means either setting the variable to a specific value or limiting it with a lower or an upper bound.

As you can see there is a hierarchical relation among these definitions: a labeling session consists of several labeling attempts, which, in turn, might consist of several labeling steps.

A labeling event, on the other hand, can either be a labeling step, or the start of a labeling attempt, or the failure of the same. See FDBG Events.


Node:FDBG Visualizers, Next:, Previous:FDBG Labeling Levels, Up:FDBG Concepts

Visualizers

A visualizer is a Prolog predicate reacting to FDBG events (see FDBG Events). It is called directly by the FDBG core when any FDBG event occurs. It is called visualizer, because usually it should present the events to the user, but in general it can do any kind of processing, like checking invariants, etc.

For all major event classes, a different visualizer type is used. The set of visualizers you would like to use for a session is specified in the option list of fdbg_on/1 (see FDBG Options), when FDBG is switched on.

A specific visualizer can have several arguments, some are supplied by the FDBG core, the rest (if any) should be specified when FDBG is switched on. Note that the obligatory arguments will be appended to the end of the user defined argument list.

The set of built-in visualizers installed by default (see FDBG Options) is the following:

For details on built-in visualizers, see FDBG Built-In Visualizers.


Node:FDBG Names of Terms, Next:, Previous:FDBG Visualizers, Up:FDBG Concepts

Names of Terms

FDBG provides a service to assign names to Prolog terms for later reference. A name is an atom and it is usually associated with a compound term containing constraint variables, or with a single variable. In the former case, each variable appearing in the compound term is also assigned a name automatically by FDBG. This auto-assigned name is derived from the name of the term; see FDBG Name Auto-Generation.

Perhaps the most useful utilization of names is annotation, another service of FDBG. Here, each variable appearing in a Prolog term is replaced with a compound term describing it (i.e. containing its name, the variable itself, and some data regarding its domain). During annotation, unnamed constraint variables are also given a unique "anonymous" name automatically, these names begin with a fdvar prefix. See FDBG Writing Visualizers.

The names will be used by the built-in visualizers when referring to constraint variables, and they can also be used to retrieve the terms assigned to them in user defined visualizers. See FDBG Visualizers.


Node:FDBG Selectors, Next:, Previous:FDBG Names of Terms, Up:FDBG Concepts

Selectors

A selector is a Prolog term denoting a (path to a) subterm of a given term T. Let subterm(T,S) denote the subterm of T wrt. a selector S, and let N denote an integer. A selector then takes one of the following forms:

S subterm(T,S)
[] T
[...,N] Nth argument of the compound term subterm(T,[...])
[...,#N] Nth element of the list subterm(T,[...])


Node:FDBG Name Auto-Generation, Next:, Previous:FDBG Selectors, Up:FDBG Concepts

Name Auto-Generation

There are two cases when a name is automatically generated.

  1. When a name is assigned to a compound term by the user, each variable appearing in it is assigned a so called derived name, which is created by appending a variant of the selector of the variable to the original name. For example, the call:
    fdbg_assign_name(bar(A, [B, C], foobar(D, E)), foo)
    
    will create the following name/term entries:

    Name Term/Variable Selector
    foo bar(A, [B, C], foobar(D, E)) []
    foo_1 A [1]
    foo_2_1 B [2,#1]
    foo_2_2 C [2,#2]
    foo_3_1 D [3,1]
    foo_3_2 E [3,2]

    See FDBG Naming Terms.

  2. If, during the annotation of a term (see FDBG Annotation) an unnamed constraint variable is found, it is assigned a unique "anonymous" name. This name consists of the prefix fdvar, an underscore character, and an integer. The integer is automatically incremented when necessary.


Node:FDBG Legend, Next:, Previous:FDBG Name Auto-Generation, Up:FDBG Concepts

Legend

The legend is a list of variables and their domains, usually appearing after a description of the current constraint. This is necessary because the usual visual representation of a constraint contains only the names of the variables in it (see FDBG Annotation), and doesn't show anything about their domain. The legend links these names to the corresponding domains. The legend also shows the changes of the domains made by the constraint. Finally, the legend may contain some conclusions regarding the behavior of the constraint, like failure or side effects.

The format of the legend is somewhat customizable by defining a hook function; see FDBG Customizing Output. The default format of the legend is the following:

list_2 = 0..3
list_3 = 0..3
list_4 = 0..3
fdvar_2 = 0..3 -> 1..3

Here, we see four variables, with initial domains 0..3, but the domain of the (previously unnamed) variable fdvar_2 is narrowed by the constraint (not shown here) to 1..3.

A legend is automatically printed by the built-in visualizer fdbg_show, but it can be easily printed from user defined visualizers too.


Node:FDBG The fdbg_output Stream, Previous:FDBG Legend, Up:FDBG Concepts

The fdbg_output Stream

The fdbg_output is a stream alias created when FDBG is switched on and removed when it is switched off. All built-in visualizers write to this stream, and the user defined visualizers should do the same.


Node:FDBG Basics, Next:, Previous:FDBG Concepts, Up:FDBG

Basics

Here, we describe the set of FDBG services and commands necessary to do a simple debugging session. No major modification of your CLP(FD) program is necessary to use FDBG this way. Debugging more complicated programs, on the other hand, might also require user written extensions to FDBG, since the wallpaper trace produced by the built-in visualizer fdbg_show could be too detailed and therefore hard to analyze. See FDBG Advanced Usage.


Node:FDBG Options, Next:, Previous:FDBG Basics, Up:FDBG Basics

FDBG Options

FDBG is switched on and off with the predicates:


fdbg_on
fdbg_on(:Options)
Turns on FDBG by putting advice points on several predicates of the CLP(FD) module. Options is a single option or a list of options; see FDBG Options. The empty list is the default value.

fdbg_on/[0,1] can be called safely several times consecutively; only the first call will have an effect.

fdbg_off
Turns the debugger off by removing the previously installed advice points.

fdbg_on/1 accepts the following options:

file(Filename, Mode)
Tells FDBG to attach the stream alias fdbg_output to the file called Filename opened in mode Mode. Mode can either be write or append. The file specified is opened on a call to fdbg_on/1 and is closed on a call to fdbg_off/0.
socket(Host, Port)
Tells FDBG to attach the stream alias fdbg_output to the socket connected to Host on port Port. The specified socket is created on a call to fdbg_on/1 and is closed on a call to fdbg_off/0.
stream(Stream)
Tells FDBG to attach the stream alias fdbg_output to the stream Stream. The specified stream remains open after calling fdbg_off/0.

If none of the above three options is used, the stream alias fdbg_output is attached to the current output stream.


constraint_hook(Goal)
Tells FDBG to extend Goal with two (further) arguments and call it on the exit port of the global constraint dispatcher (dispatch_global_fast/4).
no_constraint_hook
Tells FDBG not to use any constraint hook.

If none of the above two options is used, the default is constraint_hook(fdbg:fdbg_show).


labeling_hook(Goal)
Tells FDBG to extend Goal with three (further) arguments and call it on any of the three labeling events.
no_labeling_hook
Tells FDBG not to use any labeling hook.

If none of the above two options is used, the default is labeling_hook(fdbg:fdbg_label_show).

For both constraint_hook and labeling_hook, Goal should be a visualizer, either built-in (see FDBG Built-In Visualizers) or user defined. More of these two options may appear in the option list, in which case they will be called in their order of occurrence.

See FDBG Writing Visualizers, for more details on these two options.


Node:FDBG Naming Terms, Next:, Previous:FDBG Options, Up:FDBG Basics

Naming Terms

Naming is a procedure of associating names with terms and variables; see FDBG Names of Terms. Three predicates are provided to assign and retrieve names, these are the following:


fdbg_assign_name(+Term, ?Name)
Assigns the atom Name to Term, and a derived name to each variable appearing in Term. If Name is a variable, then use a default (generated) name, and return it in Name. See FDBG Name Auto-Generation.
fdbg_current_name(?Term, ?Name)
Retrieves Term associated with Name, or enumerates all term-name pairs.
fdbg_get_name(+Term, -Name)
Returns the name associated to Term in Name, if it exists. Otherwise, silently fails.


Node:FDBG Built-In Visualizers, Next:, Previous:FDBG Naming Terms, Up:FDBG Basics

Built-In Visualizers

The default visualizers are generic predicates to display FDBG events (see FDBG Events) in a well readable form. These visualizers naturally don't exploit any problem specific information--to have more "fancy" output, you have to write your own visualizers; see FDBG Writing Visualizers. To use these visualizers, pass them in the appropriate argument to fdbg_on/1; see FDBG Options, or call them directly from user defined visualizers.


fdbg_show(+Constraint, +Actions)
This visualizer produces a trace output of all woken global constraints, in which a line showing the constraint is followed by a legend (see FDBG Legend) of all the variables appearing in it, and finally an empty line to separate events from each other. The usual output will look like this:
<fdvar_1>#=0
    fdvar_1 = {0}
    Constraint exited.

Here, we can see an arithmetical constraint being woken. It narrows fdvar_1 to a domain consisting of the singleton value 0, and since this is the narrowest domain possible, the constraint doesn't have anything more to do: it exits.

Please note that when you pass fdbg_show/2 as an option, you should omit the two arguments, like in

fdbg_on([..., constraint_hook(fdbg_show), ...]).

fdbg_label_show(+Event, +LabelID, +Variable)
This visualizer produces a wallpaper trace output of all labeling events. It is best used together with fdbg_show/2. Each labeling event produces a single line of output, some of them are followed by an empty line, some others are always followed by another labeling action and therefore the empty line is omitted. Here is a sample output of fdbg_label_show/3:
Labeling [9, <list_1>]: starting in range 0..3.
Labeling [9, <list_1>]: step: <list_1> = 0

What we see here is the following:

Please note that when you pass fdbg_label_show/3 as an option, you should omit the three arguments, like in

fdbg_on([..., labeling_hook(fdbg_label_show), ...]).


Node:FDBG Debugger Commands, Next:, Previous:FDBG Built-In Visualizers, Up:FDBG Basics

New Debugger Commands

The Prolog debugger is extended by FDBG. The & debugger is modified, and two new commands are added:

&
& N
This debugger command is extended so that the annotated form of domain variables is also printed when listing the variables with blocked goals.
A
A Selector
Annotates and prints the current goal and a legend of the variables appearing in it. If a selector is specified, then the subterm specified by it is assumed to be an action list, and is taken into account when displaying the legend. For example:
23      2 Exit: clpfd:dispatch_global_fast(no_threat(2,_1001,1),0,0,
                                            [exit,_1001 in_set[[3|3]]]) ? A [2,4]

clpfd:dispatch_global_fast(no_threat(2,<board_2>,1),0,0,
                           [exit,<board_2> in_set[[3|3]]])
    board_2 = 1..4 -> {3}
    Constraint exited.

W Name=Selector
Assigns the atom Name to the variable specified by the Selector. For example:
7      15 Call: bar(4, [_101,_102,_103]) ? W foo=[2,#2]

This would assign the name foo to _102, being the second element of the second argument of the current goal.


Node:FDBG Annotation, Next:, Previous:FDBG Debugger Commands, Up:FDBG Basics

Annotating Programs

In order to use FDBG efficiently, you have to make some changes to your CLP(FD) program. Fortunately the calls you have to add are not numerous, and when FDBG is turned off they don't decrease efficiency significantly or modify the behavior of your program. On the other hand, they are necessary to make FDBG output easier to understand.

Assign names to the more important and more frequently occurring variables by inserting fdbg_assign_name/2 calls at the beginning of your program. It is advisable to assign names to variables in larger batches (i.e. as lists or compound terms) with a single call.

Use pre-defined labeling predicates if possible. If you define your own labeling predicates and you want to use them even in the debugging session, then you should follow these guidelines:

  1. Add a call to clpfd:fdbg_start_labeling(+Var) at the beginning of the predicate doing a labeling attempt, and pass the currently labeled variable as an argument to the call.
  2. Call clpfd:fdbg_labeling_step(+Var, +Step) before each labeling step. Step should be a compound term describing the labeling step, this will be
    1. printed "as is" by the built-in visualizer as the mode of the labeling step (see FDBG Built-In Visualizers)--you can use portray/1 to determine how it should be printed;
    2. passed as step(Step) to the user defined labeling visualizers in their Event argument; see FDBG Writing Visualizers.

This way FDBG can inform you about the labeling events created by your labeling predicates exactly like it would do in the case of internal labeling. If you ignore these rules FDBG won't be able to distinguish labeling events from other FDBG events any more.


Node:FDBG An Example Session, Previous:FDBG Annotation, Up:FDBG Basics

An Example Session

The problem of magic sequences is a well known constraint problem. A magic sequence is a list, where the i-th item of the list is equal to the number of occurrences of the number i in the list, starting from zero. For example, the following is a magic sequence:

[1,2,1,0]

The CLP(FD) solution can be found in library('clpfd/examples/magicseq'), which provides a couple of different solutions, one of which uses the global_cardinality/2 constraint. We'll use this solution to demonstrate a simple session with FDBG.

First, the debugger is imported into the user module:

| ?- use_module(fdbg).
% loading /home/matsc/sicstus3/Utils/x86-linux-glibc2.2/lib/sicstus-3.9.0beta1/library/fdbg.po...
% module fdbg imported into user

[...]

% loaded /home/matsc/sicstus3/Utils/x86-linux-glibc2.2/lib/sicstus-3.9.0beta1/library/fdbg.po in module fdbg, 220 msec 453936 bytes

yes

Then, the magic sequence solver is loaded:

| ?- [library('clpfd/examples/magicseq')].
% consulting /home/matsc/sicstus3/Utils/x86-linux-glibc2.2/lib/sicstus-3.9.0beta1/library/clpfd/examples/magicseq.pl...
%  module magic imported into user
%  module clpfd imported into magic
% consulted /home/matsc/sicstus3/Utils/x86-linux-glibc2.2/lib/sicstus-3.9.0beta1/library/clpfd/examples/magicseq.pl in module magic, 30 msec 9440 bytes

yes

Now we turn on the debugger, telling it to save the trace in fdbg.log.

| ?- fdbg_on([file('fdbg.log',write)]).
% The clp(fd) debugger is switched on

yes

To produce a well readable trace output, a name has to be assigned to the list representing the magic sequence. To avoid any modifications to the source code, the name is assigned by a separate call before calling the magic sequence finder predicate:

| ?- length(L,4), fdbg_assign_name(L,list), magic_gcc(4,L,[enum]).
L = [1,2,1,0] ? ;
L = [2,0,2,0] ? ;

no

(NOTE: the call to length/2 is necessary; otherwise, L would be a single variable instead of a list of four variables when the name is assigned.)

Finally we turn the debugger off:

| ?- fdbg_off.
% The clp(fd) debugger is switched off

yes

The output of the sample run can be found in fdbg.log. Here, we show selected parts of the trace. In each block, the woken constraint appears on the first line, followed by the corresponding legend.

In the first displayed block, scalar_product/4 removes infeasible domain values from list_3 and list_4, thus adjusting their upper bounds. The legend shows the domains before and after pruning. Note also that the constraint is rewritten to a more readable form:

<list_2>+2*<list_3>+3*<list_4>#=4
    list_2 = 0..3
    list_3 = 0..3 -> 0..2
    list_4 = 0..3 -> 0..1

The following block shows the initial labeling events, trying the value 0 for list_1:

Labeling [22, <list_1>]: starting in range 0..3.
Labeling [22, <list_1>]: indomain_up: <list_1> = 0

This immediately leads to a dead end:

global_cardinality([0,<list_2>,<list_3>,<list_4>],
                   [0-0,1-<list_2>,2-<list_3>,3-<list_4>])
    list_2 = 0..3
    list_3 = 0..2
    list_4 = 0..1
    Constraint failed.

We backtrack on list_1, trying instead the value 1. This leads to the following propagation steps:

Labeling [22, <list_1>]: indomain_up: <list_1> = 1

global_cardinality([1,<list_2>,<list_3>,<list_4>],
                   [0-1,1-<list_2>,2-<list_3>,3-<list_4>])
    list_2 = 0..3 -> 1..3
    list_3 = 0..2
    list_4 = 0..1

<list_2>+2*<list_3>+3*<list_4>#=4
    list_2 = 1..3
    list_3 = 0..2 -> 0..1
    list_4 = 0..1

However, we do not yet have a solution, so we try the first feasible value for list_2, which is 2. This is in fact enough to solve the goal. In the last two propagation steps, the constraint exits, which means that it holds no matter what value any remaining variable takes (in this example, there are none):

Labeling [29, <list_2>]: indomain_up: <list_2> = 2

global_cardinality([1,2,<list_3>,<list_4>],[0-1,1-2,2-<list_3>,3-<list_4>])
    list_3 = 0..1 -> {1}
    list_4 = 0..1 -> {0}

global_cardinality([1,2,1,0],[0-1,1-2,2-1,3-0])
    Constraint exited.

0#=0
    Constraint exited.


Node:FDBG Advanced Usage, Previous:FDBG Basics, Up:FDBG

Advanced Usage

Sometimes the output of the built-in visualizer is inadequate. There might be cases when only minor changes are necessary to produce a more readable output; in other cases, the trace output should be completely reorganized. FDBG provides two ways of changing the appearance of the output by defining hook predicates. In this section, these predicates will be described in detail.


Node:FDBG Customizing Output, Next:, Previous:FDBG Advanced Usage, Up:FDBG Advanced Usage

Customizing Output

The printing of variable names is customized by defining the following hook predicate.


fdbg:fdvar_portray(Name, Var, FDSet) [Hook]
This hook predicate is called whenever an annotated constraint variable (see FDBG Annotation) is printed. Name is the assigned name of the variable Var, whose domain will be FDSet as soon as the narrowings of the current constraint take effect. The current domain is not stored in this compoun, but it can be easily determined with a call to fd_set/2. (Although these two sets may be the same if the constraint didn't narrow it.)

If fdbg:fdvar_portray/3 is undefined or fails the default representation is printed, which is Name between angle brackets.

The printing of legend lines is customized by defining the following hook predicate.


fdbg:legend_portray(Name, Var, FDSet) [Hook]
This hook is called for each line of the legend by the built-in legend printer. The arguments are the same as in the case of fdbg:fdvar_portray/3. Note that a prefix of four spaces and a closing newline character is always printed by FDBG.

If fdbg:fdvar_portray/3 is undefined or fails the default representation is printed, which is

Name = RangeNow [ -> RangeAfter ]

The arrow and RangeAfter are only printed if the constraint narrowed the domain of Var.

The following example will print a list of all possible values instead of the range for each variable in the legend:

:- multifile fdbg:legend_portray/3.
fdbg:legend_portray(Name, Var, Set) :-
        fd_set(Var, Set0),
        fdset_to_list(Set0, L0),
        fdset_to_list(Set, L),
        (   L0 == L
        ->  format('~p = ~p', [Name, L])
        ;   format('~p = ~p -> ~p', [Name, L0, L])
        ).


Node:FDBG Writing Visualizers, Next:, Previous:FDBG Customizing Output, Up:FDBG Advanced Usage

Writing Visualizers

For more complicated problems you might want to change the output more drastically. In this case you have to write and use your own visualizers which could naturally be problem specific, not like fdbg_show/2 and fdbg_label_show/3. As we described earlier, currently there are two types of visualizers:

constraint visualizer
MyGlobalVisualizer([+Arg1, +Arg2, ...] +Constraint, +Actions)

This visualizer is passed in the constraint_hook option. It must have at least two arguments, these are the following:

Constraint
the constraint that was handled by the dispatcher
Actions
the action list returned by the dispatcher

Other arguments can be used for any purpose, for example to select the verbosity level of the visualizer. This way you don't have to modify your code if you would like to see less or more information. Note however, that the two obligatory arguments must appear at the end of the argument list.

When passing as an option to fdbg_on/1, only the optional arguments have to be specified; the two mandatory arguments should be omitted. See FDBG Debugging Global Constraints, for an example.

labeling visualizer
MyLabelingVisualizer([+Arg1, +Arg2, ...] +Event, +ID, +Var)

This visualizer is passed in the labeling_hook option. It must have at least three arguments, these are the following:

Event
a term representing the labeling event, can be one of the following:
start
labeling has just started for a variable
fail
labeling has just failed for a variable
step(Step)
variable has been constrained in a labeling step described by the compound term Step, which is either created by built-in labeling predicates (in this case, simply print it--FDBG will know how to handle it) or by you; see FDBG Annotation.

ID
identifies the labeling session, i.e. binds step and fail events to the corresponding start event
Var
the variable being the subject of labeling

The failure of a visualizer is ignored and multiple choices are cut by FDBG. Exceptions, on the other hand, are not caught.

FDBG provides several predicates to ease the work of the visualizer writers. These predicates are the following:


fdbg_annotate(+Term0, -Term, -Variables)
fdbg_annotate(+Term0, +Actions, -Term, -Variables)
Replaces each constraint variable in Term0 by a compound term describing it and returns the result in Term. Also, collects these compound terms into the list Variables. These compound terms have the following form:
fdvar(Name, Var, FDSet)
Name
is the name of the variable (auto-generated, if necessary; see FDBG Name Auto-Generation)
Var
is the variable itself
FDSet
is the domain of the variable after narrowing with Actions, if specified; otherwise, it is the current domain of the variable

fdbg_legend(+Vars)
Prints a legend of Vars, which is a list of fdvar/3 compound terms returned by fdbg_annotate/[3,4].
fdbg_legend(+Vars, +Actions)
Prints a legend of Vars followed by some conclusions regarding the constraint (exiting, failing, etc.) based on Actions.


Node:FDBG Writing Legend Printers, Next:, Previous:FDBG Writing Visualizers, Up:FDBG Advanced Usage

Writing Legend Printers

When you write your own visualizers, you might not be satisfied with the default format of the legend. Therefore you might want to write your own legend printer, replacing fdbg_legend/[1,2]. This should be quite straightforward based on the variable list returned by fdbg_annotate/[3,4]. Processing the rest of the action list and writing conclusions about the constraint behavior is not that easy though. To help your work, FDBG provides a predicate to transform the raw action list to a more readable form:


fdbg_transform_actions(+Actions, +Vars, -TransformedActions)
This will do the following transformations to Actions, returning the result in TransformedActions:

  1. remove all actions concerning variables in Vars (the list returned by fdbg_annotate/[3,4]);
  2. remove multiple exit and/or fail commands;
  3. remove all ground actions, translating those that will cause failure into fail(Action);
  4. substitute all other narrowings with an fdvar/3 compound term per variable.

The transformed action list may contain the following terms:

exit
the constraint exits
fail
the constraint fails due to a fail action
fail(Action)
the constraint fails because of Action
call(Goal)
Actions originally contained this action. FDBG can't do anything with that but to inform the user about it.
fdvar(Name, Var, FDSet)
Actions also narrowed some variables that didn't appear in the Vars list, this is one of them. The meaning of the arguments is the usual, described in FDBG Writing Visualizers. This should normally not happen.
AnythingElse
Actions contained unrecognized actions too, these are copied unmodified. This shouldn't happen!


Node:FDBG Showing Selected Constraints (simple version), Next:, Previous:FDBG Writing Legend Printers, Up:FDBG Advanced Usage

Showing Selected Constraints (simple version)

Sometimes the programmer is not interested in every global constraint, only some selected ones. Such a filter can be easily implemented with a user-defined visualizer. Suppose that you are interested in the constraints all_different/1 and all_distinct/1 only:

%% spec_filter(+Constraint, +Actions):  Call fdbg_show for all constraints
%%   for which intresting_event(Constraint) succeeds.
%%
%%   Use this filter by giving the constraint_hook(spec_filter) option to
%%   fdbg_on.
spec_filter(Constraint, Actions) :-
        interesting_event(Constraint),
        fdbg_show(Constraint, Actions).

interesting_event(all_different(_)).
interesting_event(all_distinct(_)).

Here is a session using the visualizer. Note that the initialization part (domain/3 events), are filtered out, leaving only the all_different/1 constraints:

| ?- [library('clpfd/examples/suudoku')].
[...]
| ?- fdbg_on(constraint_hook(spec_filter)).
% The clp(fd) debugger is switched on
yes
% advice
| ?- suudoku([], 1, P).
all_different([1,<fdvar_1>,<fdvar_2>,8,<fdvar_3>,
               4,<fdvar_4>,<fdvar_5>,<fdvar_6>])
    fdvar_1 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_2 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_3 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_4 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_5 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_6 = 1..9 -> (2..3)\/(5..7)\/{9}

[...]

all_different([7,6,2,5,8,4,1,3,9])
    Constraint exited.

P = [...] ;
no
% advice
| ?- fdbg_off.
% The clp(fd) debugger is switched off

Note that the failure of spec_filter/2 doesn't cause any unwanted output.


Node:FDBG Showing Selected Constraints (advanced version), Next:, Previous:FDBG Showing Selected Constraints (simple version), Up:FDBG Advanced Usage

Showing Selected Constraints (advanced version)

Suppose that you want to give the constraints that you are interested in as an argument to the visualizer, instead of defining them in a table. The following visualizer implements this.

:- use_module(library(lists), [append/3]).

%% filter_events(+CtrSpecs, +Constraint, +Actions):  This predicate will
%%   only show constraint events if they match an element in the list CtrSpecs,
%%   or if CtrSpecs is wrapped in -/1, then all the non-matching events will
%%   be shown.
%%   CtrSpecs can contain the following types of elements:
%%     ctr_name             - matches all constraints of the given name
%%     ctr_name/arity       - matches constraints with the given name and arity
%%     ctr_name(...args...) - matches constraints unifyable with the given term
%%
%%   For the selected events fdbg_show(Constraint, Actions) is called.
%%
%%   This visualizer can be specified when turning fdbg on, e.g.:
%%     fdbg_on([constraint_hook(filter_events([count/4]))]).
%%   or
%%     fdbg_on([constraint_hook(filter_events(-[in_set]))]).
filter_events(CtrSpecs, Constraint, Actions) :-
        filter_events(CtrSpecs, fdbg_show, Constraint, Actions).

%% filter_events(+CtrSpecs, +Visualizer, +Constraint, +Actions):  Same as
%%   the above predicate, but the extra argument Visualizer specifies the
%%   predicate to be called for the selected events (in the same form as
%%   in the constraint_hook option, i.e. without the last two arguments).
%%
%%   For example:
%%     fdbg_on([constraint_hook(filter_events([count/4],my_show))]).
filter_events(-CtrSpecs, Visualizer, Constraint, Actions) :- !,
        \+ show_constraint(CtrSpecs, Constraint),
        add_args(Visualizer, [Constraint, Actions], Goal),
        call(Goal).
filter_events(CtrSpecs, Visualizer, Constraint, Actions) :-
        show_constraint(CtrSpecs, Constraint),
        add_args(Visualizer, [Constraint, Actions], Goal),
        call(Goal).

show_constraint([C|_], Constraint) :-
        matches(C, Constraint), !.
show_constraint([_|Cs], Constraint) :-
        show_constraint(Cs, Constraint).

matches(Name/Arity, Constraint) :- !,
        functor(Constraint, Name, Arity).
matches(Name, Constraint) :-
        atom(Name), !,
        functor(Constraint, Name, _).
matches(C, Constraint) :-
        C = Constraint.

add_args(Goal0, NewArgs, Goal) :-
        Goal0 =.. [F|Args0],
        append(Args0, NewArgs, Args),
        Goal =.. [F|Args].

Here is a session using the visualizer, filtering out everything but all_different/1 constraints:

| ?- [library('clpfd/examples/suudoku')].
[...]
| ?- fdbg_on(constraint_hook(filter_events([all_different/1]))).
% The clp(fd) debugger is switched on
yes
% advice
| ?- suudoku([], 1, P).
all_different([1,<fdvar_1>,<fdvar_2>,8,<fdvar_3>,
               4,<fdvar_4>,<fdvar_5>,<fdvar_6>])
    fdvar_1 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_2 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_3 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_4 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_5 = 1..9 -> (2..3)\/(5..7)\/{9}
    fdvar_6 = 1..9 -> (2..3)\/(5..7)\/{9}

[...]

all_different([7,6,2,5,8,4,1,3,9])
    Constraint exited.

P = [...] ;
no
% advice
| ?- fdbg_off.
% The clp(fd) debugger is switched off
yes

In the next session, all constraints named all_different are ignored, irrespective of arity. Also, we explicitly specified the visualizer to be called for the events which are kept (here, we have written the default, fdbg_show, so the actual behavior is not changed).

| ?- [library('clpfd/examples/suudoku')].
[...]
| ?- fdbg_on(constraint_hook(filter_events(-[all_different],fdbg_show))).
% The clp(fd) debugger is switched on
yes
% advice
| ?- suudoku([], 1, P).
domain([1,<fdvar_1>,<fdvar_2>,8,<fdvar_3>,
        4,<fdvar_4>,<fdvar_5>,<fdvar_6>],1,9)
    fdvar_1 = inf..sup -> 1..9
    fdvar_2 = inf..sup -> 1..9
    fdvar_3 = inf..sup -> 1..9
    fdvar_4 = inf..sup -> 1..9
    fdvar_5 = inf..sup -> 1..9
    fdvar_6 = inf..sup -> 1..9
    Constraint exited.
    Constraint exited.

[...]

domain([2,<fdvar_46>,5,<fdvar_47>,<fdvar_48>,
       <fdvar_49>,<fdvar_50>,<fdvar_51>,9],1,9)
    fdvar_46 = inf..sup -> 1..9
    fdvar_47 = inf..sup -> 1..9
    fdvar_48 = inf..sup -> 1..9
    fdvar_49 = inf..sup -> 1..9
    fdvar_50 = inf..sup -> 1..9
    fdvar_51 = inf..sup -> 1..9
    Constraint exited.

P = [...] ;
no
% advice
| ?- fdbg_off.
% The clp(fd) debugger is switched off
yes

In the last session, we specify a list of constraints to ignore, using a pattern to select the appropriate constraints. Since all constraints in the example match one of the items in the given list, no events are printed.

| ?- [library('clpfd/examples/suudoku')].
[...]
| ?- fdbg_on(constraint_hook(filter_events(-[domain(_,1,9),all_different(_)]))).
% The clp(fd) debugger is switched on
yes
% advice
| ?- suudoku([], 1, P).
P = [...] ;
no
% advice
| ?- fdbg_off.
% The clp(fd) debugger is switched off


Node:FDBG Debugging Global Constraints, Next:, Previous:FDBG Showing Selected Constraints (advanced version), Up:FDBG Advanced Usage

Debugging Global Constraints

Missing pruning and excessive pruning are the two major classes of bugs in the implementation of global constraints. Since CLP(FD) is an incomplete constraint solver, missing pruning is mainly an efficiency concern (but ground instances for which the constraint does not hold should be rejected). Excessive pruning, however, means that some valid combinations of values are pruned away, leading to missing solutions. The following exported predicate helps spotting excessive pruning in user-defined global constraints:


fdbg_guard(:Goal, +Constraint, +Actions)
A constraint visualizer which does no output, but notifies the user by calling Goal if a solution is lost through domain narrowings. Naturally you have to inform fdbg_guard/3 about the solution in question--stating which variables should have which values. To use fdbg_guard/3, first:

  1. Set it up as a visualizer by calling:
    fdbg_on([..., constraint_hook(fdbg_guard(Goal)), ...])
    

    As usual, the two other arguments will be supplied by the FDBG core when calling fdbg_guard/3.

  2. At the beginning of your program, form a pair of lists Xs-Vs where Xs is the list of variables and Vs is the list of values in question. This pair should then be assigned the name fdbg_guard using ?- fdbg_assign_name(Xs-Vs, fdbg_guard).

When these steps have been taken, fdbg_guard/3 will watch the domain changes of Xs done by each global constraint C. Whenever Vs is in the domains of Xs at entry to C, but not at exit from C, Goal is called with three more arguments:

Variable List
a list of Variable-Value terms for which Value was removed from the domain of Variable
Constraint
the constraint that was handled by the dispatcher
Actions
the action list returned by the dispatcher

We will now show an example using fdbg_guard/3. First, we will need a few extra lines of code:

%% print_and_trace(MissValues, Constraint, Actions):  To be used as a Goal for
%%   fdbg_guard to call when the given solution was removed from the domains
%%   of the variables.
%%
%%   MissValues is a list of Var-Value pairs, where Value is the value that
%%   should appear in the domain of Var, but has been removed.  Constraint is
%%   the current constraint and Actions is the list of actions returned by it.
%%
%%   This predicate prints MissValues in a textual form, then shows the current
%%   (culprit) constraint (as done by fdbg_show/2), then turns on the Prolog
%%   tracer.

print_and_trace(MissValues, Constraint, Actions) :-
        print(fdbg_output, '\nFDBG Guard:\n'),
        display_missing_values(MissValues),
        print(fdbg_output, '\nCulprit constraint:\n\n'),
        fdbg_show(Constraint, Actions),
        trace.

display_missing_values([]).
display_missing_values([Var-Val|MissVals]) :-
        fdbg_annotate(Var,AVar,_),
        format(fdbg_output, '  ~d was removed from ~p~n', [Val,AVar]),
        display_missing_values(MissVals).

Suppose that we have written the following N Queens program, using a global constraint no_threat/3 with a bug in it:

:- use_module(library(clpfd)).
:- use_module(library(fdbg)).

queens(L, N) :-
        length(L, N),
        domain(L, 1, N),
        constrain_all(L),
        labeling([ff,enum], L).

constrain_all([]).
constrain_all([X|Xs]):-
        constrain_between(X,Xs,1),
        constrain_all(Xs).

constrain_between(_X,[],_N).
constrain_between(X,[Y|Ys],N) :-
        no_threat(X,Y,N),
        N1 is N+1,
        constrain_between(X,Ys,N1).

no_threat(X,Y,I) :-
        fd_global(no_threat(X,Y,I), 0, [val(X),val(Y)]).

:- multifile clpfd:dispatch_global/4.
clpfd:dispatch_global(no_threat(X,Y,I), S, S, Actions) :-
        ground(X), !,
        remove_threat(Y, X, I, NewYSet),
        Actions = [exit, Y in_set NewYSet].
clpfd:dispatch_global(no_threat(X,Y,I), S, S, Actions) :-
        ground(Y), !,
        remove_threat(X, Y, I, NewXSet),
        Actions = [exit, X in_set NewXSet].
clpfd:dispatch_global(no_threat(_,_,_), S, S, []).

remove_threat(X, V, I, Set) :-
        Vp is V+I+1,   % Bug introduced here
%       Vp is V+I,     % Good code
        Vn is V-I,
        fd_set(X, Set0),
        list_to_fdset([Vn, V, Vp], VSet),
        fdset_subtract(Set0, VSet, Set).

missing(L, Tuple) :-
     length(Tuple, N),
     length(L, N),
     fdbg_assign_name(L-Tuple, fdbg_guard),
     fdbg_assign_name(L, board),
     fdbg_on(constraint_hook(fdbg_guard(print_and_trace))),
     queens(L, N).

We will now use print_and_trace/3 as an argument to the fdbg_guard visualizer to handle the case when a solution has been removed by a constraint. The bug shown above causes three invalid solutions to be found instead of the two correct solutions. FDBG is told to watch for the disappearance of the first correct solution, [2,4,1,3]. First, we get two incorrect solutions before FDBG wakes up, because in these cases the given good solution was made impossible by a labeling event. The second branch of labeling does not by itself remove the solution, but at some point on that branch the bad constraint does remove it, so fdbg_guard/3 calls the given predicate. This prints the cause of waking (the value which should not have been removed by the constraint), prints the constraint itself, then switches the Prolog debugger to trace mode. At this point, we use the A debugger command (see FDBG Debugger Commands) to print the annotated form of the goal containing the culprit constraint.

For clarity, the labeling events were not turned off in the session below.

This information can be used to track down why the buggy no_threat/3 performed the invalid pruning.

| ?- missing(L, [2,4,1,3]).
% The clp(fd) debugger is switched on
Labeling [8, <board_1>]: starting in range 1..4.
Labeling [8, <board_1>]: indomain_up: <board_1> = 1

Labeling [13, <board_2>]: starting in range {2}\/{4}.
Labeling [13, <board_2>]: dual: <board_2> = 2

L = [1,2,3,4] ? ;
Labeling [13, <board_2>]: dual: <board_2> = 4

L = [1,4,2,3] ? ;
Labeling [13, <board_2>]: failed.

Labeling [8, <board_1>]: indomain_up: <board_1> = 2


FDBG Guard:
  4 was removed from <board_2>

Culprit constraint:

no_threat(2,<board_2>,1)
    board_2 = 1..4 -> {3}
    Constraint exited.

% The debugger will first creep -- showing everything (trace)
23      2 Exit: clpfd:dispatch_global_fast(no_threat(2,_1001,1),0,0,
                                           [exit,_1001 in_set[[3|3]]]) ? A

clpfd:dispatch_global_fast(no_threat(2,<board_2>,1),0,0,
                           [exit,<board_2> in_set[[3|3]]])
    board_2 = 1..4

23      2 Exit: clpfd:dispatch_global_fast(no_threat(2,_1001,1),0,0,
                                            [exit,_1001 in_set[[3|3]]]) ? A [2,4]

clpfd:dispatch_global_fast(no_threat(2,<board_2>,1),0,0,
                           [exit,<board_2> in_set[[3|3]]])
    board_2 = 1..4 -> {3}
    Constraint exited.

23      2 Exit: clpfd:dispatch_global_fast(no_threat(2,_1001,1),0,0,
                                           [exit,_1001 in_set[[3|3]]]) ? a
% Execution aborted
% advice,source_info
| ?- fdbg_off.
% The clp(fd) debugger is switched off


Node:FDBG Code of the Built-In Visualizers, Previous:FDBG Debugging Global Constraints, Up:FDBG Advanced Usage

Code of the Built-In Visualizers

Now that you know everything about writing visualizers, it might be worth having a look at the code of the built-in visualizers, fdbg_show/2 and fdbg_label_show/3.

fdbg_show(Constraint, Actions) :-
        fdbg_annotate(Constraint, Actions, AnnotC, CVars),
        print(fdbg_output, AnnotC),
        nl(fdbg_output),
        fdbg_legend(CVars, Actions),
        nl(fdbg_output).

fdbg_label_show(start, I, Var) :-
        fdbg_annotate(Var, AVar, _),
        (   AVar = fdvar(Name, _, Set)
        ->  fdset_to_range(Set, Range),
            format(fdbg_output, 'Labeling [~p, <~p>]: starting in range ~p.~n',
                   [I,Name,Range])
        ;   format(fdbg_output, 'Labeling [~p, <>]: starting.~n', [I])
        ).
fdbg_label_show(fail, I, Var) :-
        (   var(Var)
        ->  lookup_or_set_name(Var, Name),
            format(fdbg_output, 'Labeling [~p, <~p>]: failed.~n~n', [I,Name])
        ;   format(fdbg_output, 'Labeling [~p, <>]: failed.~n~n', [I])
        ).
fdbg_label_show(step(Step), I, Var) :-
        (   var(Var)
        ->  lookup_or_set_name(Var, Name),
            format(fdbg_output, 'Labeling [~p, <~p>]: ~p~n~n', [I,Name,Step])
        ;   format(fdbg_output, 'Labeling [~p, <>]: ~p~n~n', [I,Step])
        ).

lookup_or_set_name(Term, Name) :-
        fdbg_get_name(Term, Name), !.
lookup_or_set_name(Term, Name) :-
        fdbg_assign_name(Term, Name).

As you can see, they are quite simple, thanks to the extensive set of support predicates also available to the user.


Node:Obj Intro, Next:, Previous:FDBG, Up:Top

SICStus Objects

SICStus Objects is an extension to SICStus Prolog for flexible structuring, sharing and reuse of knowledge in large logic programming applications. It enhances Prolog with an expressive and efficient object-oriented programming component.

SICStus Objects is based on the notion of prototypes. In object-oriented programming a prototype is an object that represents a typical behavior of a certain concept. A prototype can be used as is or as a model to construct other objects that share some of the characteristics of the prototypical object. These specialized objects can themselves become prototypes used to construct other objects and so forth. The basic mechanism for sharing is by inheritance and delegation. Inheritance is known for most readers. By using the delegation mechanism an object can forward a message to another object to invoke a method defined by the recipient but interpreted in the context of the sender.

In SICStus Objects, an object is a named collection of predicate definitions. In this sense an object is similar to a Prolog module. The object system can be seen as an extension of SICStus Prolog's module system. In addition an object may have attributes that are modifiable. Predicate definitions belonging to an object are called methods. So, an object is conceptually a named collection of methods and attributes. Some of the methods defined for an object need not be stored explicitly within the object, but are rather shared with other objects by the inheritance mechanism.

The Object system allows objects to be defined in a file, or dynamically created during the execution of a program. Objects defined in a file are integrated into SICStus Prolog in a way similar to definite clause grammars. That is to say, objects have a specific syntax as Prolog terms, and can be loaded and expanded into Prolog code. When an object is created, during load-time, or run-time, it inherits the methods and attributes of its prototypical object(s). Objects defined in a file can be either static or dynamic. Also, methods can be either dynamic or static. these properties are inherited by sub-objects. Objects created during execution are dynamic.

The inheritance mechanism is implemented using the importation mechanism of the module system. The default inheritance is an inheritance by overriding mechanism, which means that if a method is defined locally, and the same method is defined in a super-object, then the clauses of the super-method are not part of the definition of the local one. As usual in Prolog, methods can be nondeterminately defined, and alternative answers can be retrieved through backtracking. Using the delegation mechanism, other methods for knowledge sharing can be implemented by the user. In SICStus Objects, there is an initial prototypical proto-object called object, from which other objects may be constructed, directly or indirectly.


Node:Obj Getting Started, Next:, Previous:Obj Intro, Up:Obj Intro

Getting Started

To load the SICStus Objects library, enter the query:

| ?- use_module(library(objects)).

SICStus Objects defines some new infix and prefix operators, and redefines some of the built-in ones. The following operators become installed:

:- op(1200, xfy, [ & ]).
:- op(1198, xfx, [ :- ]).
:- op(1198,  fx, [ :- ]).
:- op(550,  xfx, [ ::, <: ]).
:- op(550,   fx, [ ::, <: ]).


Node:Obj Declared Objects, Next:, Previous:Obj Getting Started, Up:Obj Intro

Declared Objects

Declared objects are created when the files defining them are loaded into the system.


Node:Object Declaration, Next:, Previous:Obj Declared Objects, Up:Obj Declared Objects

Object Declaration

An object object-identifier is declared by writing it in the following form:

object-identifier :: {
        sentence-1 &
        sentence-2 &
        :
        sentence-n
        }.

where object-identifier is a Prolog term that is either an atom or a compound term of the form functor(V1,...,Vn), where V1,...,Vn are distinct variables. The object body consists of a number of sentences, possibly none, surrounded by braces, where each sentence is either a method-directive, to be executed when the object is created, or a method-clause. A method is a number of method-clauses with the same principal functor. A method-clause has a clausal syntax similar to that of Prolog, but instead of usual predicate calls in the body of a clause there are method-calls. Ordinary Prolog goals are also allowed in a prefixed form, using : as a prefix. A method-directive is a directive which contains method-calls.

All sentences are subject to term expansion (see Definite, built-in expand_term/2) before further processing, so in particular definite clause grammar syntax can be used in method-clauses. In addition, before expand_term/2, sentences are expanded by the predicate user:method_expansion/3.

method_expansion(+Term1,+ObjectIdentifier,?Term2) [Hook]
user:method_expansion(+Term1,+ObjectIdentifier,?Term2)

Defines transformations on methods similarly as user:term_expansion/[2,4]. At the end of an object definition, user:method_expansion/3 is called with end_of_object.


Node:Method Declarations, Next:, Previous:Object Declaration, Up:Obj Declared Objects

Method Declarations

Method-clauses are declared similarly to Prolog clauses. Thus a method-clause can be either a unit-clause or a rule. We also allow a default catch-all method-clause as the last clause in an object body. The catch-all clause has as its head a Prolog variable, in order to match messages that are not previously defined or inherited in the object. It can be used to implement alternative inheritance mechanisms.

Goals in the body of a rule have the normal control structures of Prolog:

:P, :Q
Conjunction
:P; :Q
Disjunction
!
Cut
\+ :P
Negation
:P -> :Q
:P -> :Q; :R
if(:P, :Q, :R)
If-then[-else]
?A = ?B
Unification

Atomic goals in the body of a method-clause may be one of the following:

:goal
to call the Prolog predicate goal in the source module.
m:goal
to call the Prolog predicate goal in module m.
goal
to send the message goal to the object Self.
::goal
to send the message goal to a method that may be defined locally or inherited by the object.
<:goal
to delegate the message goal to a method that may be defined locally or inherited by the object.
object::goal
to send the message goal to object object.
object<:goal
to delegate the message goal to object object.

Message sending and delegation will be explained later (see Obj Self).

The following is a definition for the object list_object. It is constructed from three methods: append/3, member/2, and length/2. Note that the calls to append/3 and length/2 are to the local definition, whereas the member/2 call is to the predicate imported from the Prolog library module lists.

list_object :: {
        :- :use_module(library(lists), [append/3,member/2]) &

        append([], L, L) &
        append([X|L1], L2, [X|L3]) :-
                :: append(L1, L2, L3) &

        member(X, L) :-
                :member(X,L) &

        length([], 0) &
        length([_|L], N) :-
                :: length(L, N1),
                :(N is N1+1)
        }.

The following object apt_1 could be part of a larger database about free apartments in a real-estate agency:

apt_1 :: {
        super(apartment) &

        street_name('York') &
        street_number(100) &
        wall_color(white) &
        floor_surface(wood)
        }.

Another way to define apt_1 is by using attributes. These can be retrieved and modified efficiently by the methods get/1 and set/1 respectively.

apt_1 :: {
        super(apartment) &

        attributes([
               street_name('York'),
               street_number(100),
               wall_color(white),
               floor_surface(wood)])
        }.


Node:Generic Objects for Easy Reuse, Previous:Method Declarations, Up:Obj Declared Objects

Generic Objects for Easy Reuse

Defining objects for easy reuse is a very important property for reducing the cost of large projects. One important technique is to define prototypes in a parameterized way, so that various instantiations of a prototype correspond to different uses. Parameterized or generic objects have been used for this purpose in other object-oriented systems. An object-identifier can be a compound term. The arguments of the term are parameters that are visible in the object-body. Here we show one example. Other examples and techniques that use this facility has been investigated extensively in [McCabe 92].

The following is an object sort that sorts lists of different types. sort has a parameter that defines the type of the elements of the list. Notice that Type is visible to all methods in the body of sort, and is used in the method partition/4. In the query, we use sort(rat) to sort a list of terms denoting rational numbers. We must therefore define a rat object and its < method also:

rat :: {
        (P/Q < R/S) :- :(P*S < Q*R)
        }.

sort(Type) :: {
        :- :use_module(library(lists), [append/3]) &

        qsort([], []) &
        qsort([P|L], S) :-
                partition(L, P, Small, Large),
                qsort(Small, S0),
                qsort(Large, S1),
                :append(S0, [P|S1], S) &

        partition([], _P, [], []) &
        partition([X|L1], P, Small, Large) :-
                (   Type :: (X < P) ->
                    Small = [X|Small1], Large = Large1
                ;   Small = Small1, Large = [X|Large1]
                ),
                partition(L1, P, Small1, Large1)
        }.

| ?- sort(rat) :: qsort([23/3, 34/11, 45/17], L).

L = [45/17,34/11,23/3]

Parameterized objects are interesting in their own right in Prolog even if one is not interested in the object-oriented paradigm. They provide global context variables in a Prolog program without having to add such variables as additional context arguments to each clause that potentially uses the context.


Node:Obj Self, Next:, Previous:Obj Declared Objects, Up:Obj Intro

Self, Message Sending, and Message Delegation

In SICStus Objects, each method is executed in the context of an object. This object may not be the static object where the method is declared. The current contextual object is used to determine dynamically which attributes are accessed, and which methods are called. This leads to a mechanism known as dynamic binding. This object can be retrieved using the universal method self(S), where S will be bound to the current contextual object.

When a message is sent to an object, the corresponding method will be executed in the context of the target object. A message delegated to an object will invoke a method that is executed in the context of the message-delegation operation.

object :: message
:: message

Message sending. Sends message to object, setting Self of the recipient to the recipient, i.e. object. If object is omitted, the recipient is the object in which the goal textually appears.

object <: message
<: message

Message delegation. Sends message to object, setting Self of the recipient to Self of the sender. If object is omitted, the recipient is the object in which the goal textually appears. Delegation preserves Self.

The following objects physical_object, a, and b are written using the default notations for sending and delegation, hiding the contextual variable Self:

physical_object :: {
        volume(50) &
        density(100) &
        weight(X) :-
                volume(V),
                density(D),
                :(X is V*D)
        }.

a :: {
        volume(5) &
        density(10) &

        Method :-
                physical_object <: Method
        }.

b :: {
        volume(5) &
        density(10) &

        Method :-
                physical_object :: Method
        }.

Notice that the difference between the objects a and b is that a delegates any message except volume(_) and density(_) to physical_object while b sends the message to physical_object. We may now ask

| ?- a :: weight(X), b :: weight(Y).

X = 50
Y = 5000

To get hold of the current contextual object, the universal method self(S) is provided. Another way to send a message to Self is to use the constant self. So the following two alternative definition of physical_object are equivalent to the previous one:

physical_object :: {
        volume(50) &
        density(100) &
        weight(X) :-
                self(S),
                S::volume(V),
                S::density(D),
                :(X is V*D)
        }.

physical_object :: {
        volume(50) &
        density(100) &
        weight(X) :-
                self::volume(V),
                self::density(D),
                :(X is V*D)
        }.


Node:Obj Hierarchies, Next:, Previous:Obj Self, Up:Obj Intro

Object Hierarchies, Inheritance, and Modules

The SICStus Objects system implements a default inheritance mechanism. By declaring within an object which objects are super-objects, the hierarchy of objects are maintained. The system also maintains for each object its immediate sub-objects (i.e. immediate children). Each object may also call Prolog predicates. At the top of the hierarchy, the proto-object object provides various services for other objects. If object is not used at the top of the hierarchy many services will not be available for other objects (check what methods are available in object by sending the message method/1 to object).


Node:Inheritance, Next:, Previous:Obj Hierarchies, Up:Obj Hierarchies

Inheritance

Immediate super-objects are declared by defining the method super/2 within the object. (Any definition super(Super) is transformed to super(Super,[])). The objects declared by super/2 are the immediate objects from which a method is inherited if not defined within the object. This implies that the inheritance mechanism is an overriding one. One could possibly have a union inheritance, whereby all clauses defining a method are collected from the super hierarchy and executed in a Prolog fashion. This can easily be programmed in SICStus Objects, using delegation to super objects.

The following example shows some objects used for animal classification.

animal :: {}.

bird :: {
        super(animal) &
        skin(feather) &
        habitat(tree) &
        motions(fly)
        }.

penguin :: {
        super(bird) &
        habitat(land) &
        motions(walk) &
        motions(swim) &
        size(medium)
        }.

| ?- penguin :: motions(M).
M = walk ;
M = swim ;
no

| ?- penguin :: skin(S).
S = feather ;
no

The following is an example of multiple inheritance: an object john is both a sportsman and a professor:

john :: {
        super(sportsman) &
        super(professor) &
        :
        }.

Inheritance will give priority to the super-objects by the order defined in the super/2 method. Therefore in the above example John's characteristics of being a sportsman will dominate those of being professor. Other kinds of hierarchy traversal can be programmed explicitly using the delegation mechanism.


Node:Differential Inheritance, Next:, Previous:Inheritance, Up:Obj Hierarchies

Differential Inheritance

It is possible to be selective about what is inherited by using the method super/2. Its first argument is the super object, and its second is a list of the methods that will not be inherited from the super object.


Node:Use of Modules, Next:, Previous:Differential Inheritance, Up:Obj Hierarchies

Use of Modules

In SICStus Objects, the visible predicates of the source module (context) for the object definition may be called in the body of a method. (The : prefix is used to distinguish such calls from method calls.) Any (: prefixed) directives occurring among the method-clauses are also executed in the same source module. For example, to import into the source module and call the public predicates of a module, the built-in predicate use_module/2 and its variants may be used:

some_object :: {
        :- :use_module(library(lists), [append/3]) &
        double_list(X, XX) :- :append(X,X,XX)
        }.


Node:Super and Sub, Next:, Previous:Use of Modules, Up:Obj Hierarchies

Super and Sub

Two methods provided by the initial object object are super/1 and sub/1. (Note that any definition of super/1, except the one in object, is transformed to super/2). super/1 if sent to an object will return the immediate parents of the object. sub/1 will return the immediate children of the object if any. It is important to note that this service is provided only for objects that have object as their initial ancestor.

| ?- john :: super(S), S :: sub(john).
S = sportsman ;
S = professor ;
no

The sub/1 property allows programs to traverse object hierarchies from a root object object down to the leaves.


Node:The Keyword Super, Next:, Previous:Super and Sub, Up:Obj Hierarchies

The Keyword Super

To be able to send or delegate messages to the super-objects in a convenient way while following the inheritance protocol, the keyword super is provided. The calls:

        super :: method, or
        super <: method

mean: send or delegate (respectively) method to the super-objects according to the inheritance protocol. A simple example illustrates this concept: assume that john in the above example has three id-cards, one stored in his sportsman prototype identifying the club he is member of, one stored in his professor prototype identifying the university he works in, and finally one stored locally identifying his social-security number. Given the following methods in the object john:

m1(X) :-
        super <: id_card(X) &
m2(X) :-
        super(S), S <: id_card(X) &

one may ask the following:

| ?- john :: m1(X).
     % will follow the default inheritance and returns:
X = johns_club ;

| ?- john :: m2(X).
     % will backtrack through the possible supers returning:
X = johns_club ;
X = johns_university ;


Node:Semantic Links to Other Objects, Next:, Previous:The Keyword Super, Up:Obj Hierarchies

Semantic Links to Other Objects

Some object-oriented languages have syntactic constructs for redirecting the inheritance chain for certain methods to completely other objects which are not defined in the object's inheritance hierarchy. This is not needed in SICStus Objects due to delegation. Assume that the method m/n is linked to object some_object, we just add a method for this:

        m(X1, ..., Xn) :- some_object <: m(X1, ..., Xn) &


Node:Dynamically Declared Objects, Next:, Previous:Semantic Links to Other Objects, Up:Obj Hierarchies

Dynamically Declared Objects

When an object is declared and compiled into SICStus Objects, its methods cannot be changed during execution. Such an object is said to be static. To be able to update any method in an object, the object has to be declared dynamic. There is one exception, the inheritance hierarchy declared by super/[1,2] cannot be changed. By including the fact dynamic as part of the object body, the object becomes dynamic:

dynamic_object :: {
        dynamic &
        :
        }.


Node:Dynamic Methods, Next:, Previous:Dynamically Declared Objects, Up:Obj Hierarchies

Dynamic Methods

To be able to change a method with functor F/N in a static object, the method has to be declared dynamic by storing the following fact in the object:

some_object :: {
        dynamic F/N &
        :
        }.

Each book in a library can be represented as an object, in which the name of the book is stored, the authors, and a borrowing history indicating when a book is borrowed and when it is returned. A history item may have the form history_item(Person,Status,Date) where Status is either borrowed or returned, and Date has the form YY-MM-DD, for YY year, MM month, DD day.

A typical book book_12 could have the following status. Note that history_item/3 is dynamic:

book_12 :: {
        super(book) &

        title('The Art of Prolog') &
        authors(['Leon Sterling', 'Ehud Shapiro']) &

        dynamic history_item/3 &

        history_item('Dan Sahlin', returned, 92-01-10) &
        history_item('Dan Sahlin', borrowed, 91-06-10) &
        :
        }.

Dynamic methods that are stored in an object can be updated, as in usual Prolog programs, by sending assert and retract messages directly to the object.

For example, to borrow a book the following method could be defined in the object book. We assume that the top most history_item fact is the latest transaction, and there is an object date from which we can get the current date.

borrow(Person) :-
        history_item(_Person0, Status, _Date0), !,
        (   Status = returned ->
            date::current(Date),
            asserta(history_item(Person, borrowed, Date))
        ;   :display('book not available'), :ttynl
        ) &


Node:Inheritance of Dynamic Behavior, Previous:Dynamic Methods, Up:Obj Hierarchies

Inheritance of Dynamic Behavior

When an object is created, it will inherit from its parents their dynamic behavior. Methods that are declared dynamic in a parent, will be copied into the object, and its dynamic behavior preserved.

a:: {
        super(object) &
        dynamic p/1 &
        p(1) &
        p(2)
     }

b :: {
        super(a)
     }

| ?- b::p(X).
X = 1 ? ;
X = 2 ? ;
no
| ?- b::asserta(p(3)).
yes
| ?- b::p(X).
X = 3 ? ;
X = 1 ? ;
X = 2 ? ;
no

Notice that by redeclaring a method to be dynamic in a sub-object, amounts to redefining the method, and overriding of the parent definition will take effect.

c :: {
        super(a) &
        dynamic p/1
     }

| ?- c::p(X).
no


Node:Obj Dynamic, Next:, Previous:Obj Hierarchies, Up:Obj Intro

Creating Objects Dynamically

As with dynamically declared objects, the full flexibility of SICStus Objects is achieved when objects are created at runtime. Anything, except the inheritance hierarchy, can be changed: methods can be added or deleted. The services for object creation, destruction, and method modification are defined in the proto-object object.


Node:Object Creation, Next:, Previous:Obj Dynamic, Up:Obj Dynamic

Object Creation


+SomeObject :: new(?NewObject)
NewObject is created with SomeObject as super. NewObject could be an atom, variable, or compound term whose arguments are distinct variables.
+SomeObject :: new(?NewObject,+Supers)
NewObject is created with Supers specifying the super objects (prototypes). Supers is a list containing super specifications. A super specification is either an object identifier or a pair Object-NotInheritList where NotInheritList specifies methods not to inherit from Object. NewObject could be an atom, variable, or compound term whose arguments are distinct variables.

The object vehicle is created having the proto-object object as super, followed by creating moving_van with vehicle as super, followed by creating truck.

| ?- object :: new(vehicle),
     vehicle :: new(moving_van),
     moving_van :: new(truck).
yes

| ?- truck :: super(X), vehicle :: sub(X).
X = moving_van ;
no


Node:Method Additions, Next:, Previous:Object Creation, Up:Obj Dynamic

Method Additions


+SomeObject :: asserta(+SomeMethod)
+SomeObject :: assertz(+SomeMethod)
+SomeObject :: assert(+SomeMethod)
Asserts SomeMethod in SomeObject with normal Prolog semantics.

Add some facts to vehicle and truck with initial value equal to [].

| ?- vehicle :: assert(fuel_level([])),
     vehicle :: assert(oil_level([])),
     vehicle :: assert(location([])),
     truck :: assert(capacity([])),
     truck :: assert(total_weight([])).
yes


Node:Parameter Passing to New Objects, Previous:Method Additions, Up:Obj Dynamic

Parameter Passing to New Objects

When new objects are created, it is possible to pass parameters. The following example shows:

In the previous examples one could pass parameters to an object as follows, using the method augment/1.

| ?- vehicle :: augment({
        new_attrs(Instance, Attribute_list) :-
                self :: new(Instance),
                :: assign_list(Attribute_list, Instance) &

        assign_list([], Instance) &
        assign_list([Att|List], Instance) :-
                :: assign(Att, Instance),
                :: assign_list(List, Instance) &

        assign(P, Instance) :-
                Instance :: assert(P)
        }).
yes

% create a new 'truck'
| ?- vehicle :: new_attrs(truck, [capacity([]),total_weight([])]).
yes


Node:Obj Daemons, Next:, Previous:Obj Dynamic, Up:Obj Intro

Access Driven Programming--Daemons

Access based programming is a paradigm where certain actions are performed, or some constraints are checked, when "access operations" are invoked. Access operations for updates (i.e. assert, retract) can be redefined in an object by redefining these operations and delegating the same operation to super. Notice that without a delegation mechanism this would not be possible, since the Self would have changed. So assume that we want to print on the screen "p is augmented" whenever the fact p(X) is asserted in an object foo, we just redefine assert/1:

foo :: {
        super(object) &

        dynamic p/1 &

        p(0) &
        p(1) &

        assert(p(X)) :- !,   /* assert/1 is redefined for p(X) */
                super <: assert(p(X)),
                :display('p is augmented'), :ttynl &
        assert(M) :-         /* delegating assert(_) messages */
                super <: assert(M) &
        :
        }.


Node:Instances, Next:, Previous:Obj Daemons, Up:Obj Intro

Instances

Objects are relatively heavy weight. To be able to create efficiently light weight objects, we introduce the notion of instances. An instance is an object with restricted capability. It is created from an object that is considered its class. It gets a copy of the attributes of its class. These can be modified by get/1 and set/1. An instance cannot be a class for other instances. Instances are in general very efficient, both in space and access/modification time. The attribute '$class'/1 will store the identity of the class of the instance including parameters.


Node:Obj Built-In, Next:, Previous:Instances, Up:Obj Intro

Built-In Objects and Methods


Node:Universal Methods, Next:, Previous:Obj Built-In, Up:Obj Built-In

Universal Methods

The following methods are "universal", i.e. they are defined locally, if appropriate, for every object:


super(?Object,?NotInheritList)
Object is a parent (a super-object) of Self. NotInheritList specifies methods of Object explicitly not inherited by Self. The definition super(Object) is translated to super(Object,[]).
attributes(+Attributes)
Attributes is a list of compound terms specifying the local attributes of Self and the initial values.


Node:Inlined Methods, Next:, Previous:Universal Methods, Up:Obj Built-In

Inlined Methods

The following methods are compiled inline i.e. calls are replaced by definitions. This implies (in the current implementation) that they have a fixed semantics an can not be redefined. There are also definitions for these methods in object covering the cases of unexpanded calls.


self(?Self)
Unifies Self with "self".
get(+Attribute)
Gets the attribute value(s) of the attribute specified by the principal functor of Attribute. The value(s) are unified with the argument(s) of Attribute.
set(+Attribute)
Sets the attribute value(s) of the attribute specified by the principal functor of Attribute. The value(s) are taken from the argument(s) of Attribute.


Node:The Proto-Object, Next:, Previous:Inlined Methods, Up:Obj Built-In

The Proto-Object "object"

The proto-object object provides basic methods that are available to all other objects by delegation:


super(?Object)
Object is a parent (a super-object) of Self. Note that any other definition of super(Object) are translated to the universal method super/2.
sub(?Object)
Object is a child (a sub-object) of Self.
self(?Self)
Unifies Self with "self". NOTE: this method is inlined when possible.
object(?Object)

One of the defined objects in the system is Object.

dynamic

Self is a dynamic object.

static

Self is a static object.

dynamic ?Name/?Arity

Name/Arity is a dynamic method of Self.

static ?Name/?Arity

Name/Arity is a static method of Self.

new(?Object)

Creates a new dynamic Object. Self will be the prototype of Object. Object can be a compound term, an atom, or a variable. In the last case the method generates a unique name for Object.

+SomeObject :: new(?NewObject,+Supers)

NewObject is created with Supers specifying the super objects (prototypes). Supers is a list containing super specifications. A super specification is either an object identifier or a pair Object-NotInheritList where NotInheritList specifies methods not to inherit from Object. NewObject could be an atom, variable, or compound term whose arguments are distinct variables.

instance(?Instance)

Creates a new instance Instance. Self will be the class of Instance. Instance can be a compound term, an atom, or a variable. In the last case the method generates a unique name for Instance.

has_instance(?Instance)

Self has the instance Instance.

has_attribute(?AttributeSpec)

Self has the attribute AttributeSpec, locally defined or inherited. AttributeSpec is on the format Name/Arity.

get(+Attribute)
Gets the attribute value(s) of the attribute specified by the principal functor of Attribute. The value(s) are unified with the argument(s) of Attribute. NOTE: this method is inlined when possible.
set(+Attribute)
Sets the attribute value(s) of the attribute specified by the principal functor of Attribute. The value(s) are taken from the argument(s) of Attribute. NOTE: this method is inlined when possible.
assert(+Fact)
assert(+Fact, -Ref)
asserta(+Fact)
asserta(+Fact, -Ref)
assertz(+Fact)
assertz(+Fact, -Ref)

Asserts a new Fact in Self. If Self is static, the name and arity of Fact must be declared as a dynamic method. asserta places Fact before any old facts. The other forms place it after any old facts. A pointer to the asserted fact is returned in the optional argument Ref, and can be used by the Prolog built-in predicates erase/1 and instance/2.

retract(+Fact)

Retracts a Fact from Self. If Self is static, the name and arity of Fact must be declared as a dynamic method.

update(+Fact)

Replaces the first fact with the same name and arity as Fact in Self by Fact. If Self is static, the name and arity of Fact must be declared as a dynamic method.

retractall(?Head)

Removes facts from Self that unify with Head. If Self is static, the name and arity of Fact must be declared as a dynamic method.

abolish

Abolishes Self if dynamic.

augment(?ObjectBody)
augmenta(?ObjectBody)
augmentz(?ObjectBody)

ObjectBody, having the form { sentence-1 & ... & sentence-n }, is added to Self. augmenta places the new clauses before any old clauses. The other forms place it after any old clauses.


Node:The Utility Object, Previous:The Proto-Object, Up:Obj Built-In

The built-in object "utility"

The base object utility provides methods that could be used in user programs. utility has object as its super-object.

subs(?Objects)

Gives a list of all the children of Self.

supers(?Objects)

Gives a list of all parents of Self.

objects(?Objects)

Gives a list of all objects.

dynamic_objects(?Objects)

Gives a list of all dynamic objects.

static_objects(?Objects)

Gives a list of all static objects.

methods(?Methods)

Gives a list of all the methods of Self.

dynamic_methods(?Methods)

Gives a list of all dynamic methods of Self.

static_methods(?Methods)

Gives a list of all static methods of Self.

descendant(?Object)

One of the descendants of Self is Object.

descendant(?Object, ?Level)

Object a descendant at depth Level of Self. A child of Self is at level 1.

descendants(?Objects)

The list of all descendants of Self is Objects.

descendants(?Objects, ?Level)

Objects is the list of descendants at depth Level of Self.

ancestor(?Object)

One of the ancestors of Self is Object.

ancestor(?Object, ?Level)

Object is an ancestor of Self at height Level. A super-object of Self has level 1.

ancestors(?Object)

The list of all ancestors of Self is Objects.

ancestors(?Object, ?Level)

Objects is the list of ancestors at height Level of Self.

restart

Removes all dynamic objects. Note that dynamic methods added to static objects are not removed.

and_cast(+Objects, ?Message)

Sends the same message Message to all objects in the list Objects.

or_cast(+Objects, ?Message)

Sends the same message Message to one of the objects in the list Objects, backtracking through the alternative objects.


Node:Obj Expand, Next:, Previous:Obj Built-In, Up:Obj Intro

Expansion to Prolog Code

As already mentioned, object definitions are expanded to Prolog clauses much as definite clause grammars. This expansion is usually transparent to the user. While debugging a SICStus Objects program, however, the expanded representation may become exposed. This section will explain in detail the source expansion, so as to give the user the possibility to relate back to the source code during a debugging session. The inheritance mechanism, based on module importation, is also described.

First of all, every statically defined object will translate to several Prolog clauses belonging to a unique object module with the same identity as the object-identifier. Object modules are significantly cheaper to create than ordinary modules, as they do not import the built-in Prolog predicates.

The module will contain predicates implementing an object declaration, the method code, imported methods and parameter transfer predicates. These predicates will be described in detail below, using the notational convention that variable names in italics are syntactic variables that will be replaced by something else in the translation process.


Node:The Inheritance Mechanism, Next:, Previous:Obj Expand, Up:Obj Expand

The Inheritance Mechanism

The inheritance mechanism is based on the importation mechanism of the Prolog module system. When an object is created, whether loaded from file or at runtime by new/[1,2], the method predicates (i.e. predicates implementing the methods) visible in the immediate supers are collected. After subtracting from this set the method predicates which are locally defined, and those that are specified in the don't-inherit-list , the resulting set is made visible in the module of the inheriting object by means of importation. This implies that inherited methods are shared, expect dynamic methods.

Dynamic methods are inherited in a similar way with the big difference that they are not imported but copied. Even dynamic declarations (methods without clauses) are inherited.

Inheritance from dynamic objects differs in one aspect: Static predicates visible in a dynamic object are not imported directly from the dynamic object but from the static object from where it was imported to the dynamic object. This makes an inheriting object independent of any dynamic ancestor object after its creation.


Node:Object Attributes, Next:, Previous:The Inheritance Mechanism, Up:Obj Expand

Object Attributes

Attributes are based on an efficient term storage associated to modules. The attributes for an object is collected from its ancestors and itself at compile time and used for initialization at load time. The methods for accessing attributes, get/1 and set/1, are inlined to primitive calls whenever possible. They should hence not be redefined.


Node:Object Instances, Next:, Previous:Object Attributes, Up:Obj Expand

Object Instances

Instances are different from other objects in that they do not inherit. Instead they share the predicate name space with its class object. They do however have their own attributes. At creation, an instance gets a copy of its class objects attributes. The reserved attribute '$class'/1, which is present in any object, is used for an instance to hold its class object identifier. The purpose of this is mainly to store the parameters of the class object when the instance is created.


Node:The Object Declaration, Next:, Previous:Object Instances, Up:Obj Expand

The Object Declaration

The object declaration is only used by certain meta-programming operations. It consists of a fact

'$so_type'(Object, Type).

where Object is the object-identifier, and Type is either static or dynamic. If the type is static, the other generated predicates will be static; otherwise, they will be dynamic.


Node:The Method Code, Next:, Previous:The Object Declaration, Up:Obj Expand

The Method Code

Each method clause translates to a Prolog clause with two extra arguments: Self (a variable) and Myself. The latter argument is needed to cater for passing object parameters to the method body which is desribed further in next section.

The method body is translated to a Prolog-clause body as follows. The code is traversed, and the goals are transformed according to the following transformation patterns and rules. In the transformation rules, the notation Msg(X,Y) denotes the term produced by augmenting Msg by the two arguments X and Y:

Goal
where Goal is a variable, is translated to
objects:call_from_body(Goal,Self,Myself,Src) where Src is the source module. objects:call_from_body/4 will meta-interpret Goal at runtime.
:: Msg
is translated to Myself:Msg(Myself,Myself) if Msg is a non variable. Otherwise, it is translated to objects:call_object(Myself, Msg, Myself).
<: Msg
is translated to Myself:Msg(Self,Myself) if Msg is a non variable. Otherwise, it is translated to objects:call_object(Myself, Msg, Self).
super :: Msg is translated to
objects:call_super_exp(Myself,Msg(Super,Myself),Super) if Msg is a non variable. call_super_exp/3 searches the supers of Myself. Super is bound to the super object where the method is found. If Msg is a variable, the goal is translated to objects:call_super(Myself,Msg,Super,Super) which expands Msg and performs otherwise the same actions as call_super_exp/3.
super <: Msg
is translated to objects:call_super_exp(Myself,Msg(Self,Myself),Super) if Msg is a non variable. call_super_exp/3 searches the supers of Myself. Super is bound to the super object where the method is found. If Msg is a variable, the goal is translated to objects:call_super(Myself,Msg,Self,Super) which expands Msg and performs otherwise the same actions as call_super_exp/3.
Obj :: Msg

Obj <: Msg

self <: Msg
self :: Msg
Msg
are all translated like Self :: Msg.
Module:Goal
is translated to Module:Goal.
:Goal
is translated to Src:Goal where Src is the source module.

To illustrate the expansion, consider the object history_point directives, all executed in the history_point module:

:-objects:create_object(history_point,
  [point-[]],
  [attributes/3,display/3,move/4,new/4,print_history/3,super/4],
  [],
  [y(0),x(0),history([])],
  tree(history_point,[tree(point,[tree(object,[])])])).

history_point:super(point, [], _, history_point).

history_point:attributes([history([])], _, _).

history_point:display(A, B, _) :-
        objects:call_super_exp(history_point, display(A,B,C), C),
        history_point:print_history(A, B, history_point).

history_point:'$so_type'(history_point, static).

history_point:move(A, B, C, _) :-
        objects:call_super_exp(history_point, move(A,B,C,E), E),
        prolog:'$get_module_data'(C, history, D),
        prolog:'$set_module_data'(C, history, [(A,B)|D]).

history_point:print_history(A, B, _) :-
        prolog:'$get_module_data'(B, history, C),
        A:format('with location history ~w~n', [C], A, A).

history_point:new(A, xy(D,E), B, _) :-
        objects:call_super_exp(history_point, new(A,xy(D,E),B,C), C),
        prolog:'$set_module_data'(A, history, [(D,E)]).

The directive create_object/6 creates the object, performs the inheritance by importation, and initializes attributes. The last argument is a tree representing the ancestor hierarchy during compilation. It is used to check that the load time and compile time environments are consistent.


Node:Parameter Transfer, Previous:The Method Code, Up:Obj Expand

Parameter Transfer

As can be seen in the expanded methods above, the second additional argument is simply ignored if the object has no parameter. In contrast regard the following objects:

ellipse(RX,RY,Color) :: {
        color(Color) &
        area(A) :-
                :(A is RX*RY*3.14159265)
                        }.

circle(R,Color) :: {
        super(ellipse(R,R,Color))
                   }.

red_circle(R) :: {
        super(circle(R,red))
                 }.

... and their expansions:

ellipse(_, _, _):'$so_type'(ellipse(_,_,_), static).

ellipse(_, _, _):area(A, _, B) :-
        B:'$fix_param'(ellipse(C,D,_), B),
        user:(A is C*D*3.14159265).

ellipse(_, _, _):color(A, _, B) :-
        B:'$fix_param'(ellipse(_,_,A), B).

ellipse(_, _, _):'$fix_param'(ellipse(B,C,D), A) :-
        objects:object_class(ellipse(B,C,D), A).

circle(_, _):'$so_type'(circle(_,_), static).

circle(_, _):super(ellipse(A,A,B), [], _, circle(A,B)).

circle(_, _):'$fix_param'(circle(B,C), A) :-
        objects:object_class(circle(B,C), A).
circle(_, _):'$fix_param'(ellipse(B,B,C), A) :-
        objects:object_class(circle(B,C), A).

red_circle(_):'$so_type'(red_circle(_), static).

red_circle(_):super(circle(A,red), [], _, red_circle(A)).

red_circle(_):'$fix_param'(red_circle(B), A) :-
        objects:object_class(red_circle(B), A).
red_circle(_):'$fix_param'(circle(B,red), A) :-
        objects:object_class(red_circle(B), A).
red_circle(_):'$fix_param'(ellipse(B,B,red), A) :-
        objects:object_class(red_circle(B), A).

The second additional argument contains the receiver of a method call. If the method makes use of any parameter of the object where it is defined, it places a call to the reserved predicate $fix_param/2 in the module of the receiver. The purpose of this call is to bind the parameters used in the method to appropriate values given by the receiver. The receiver may be the object where the method is defined or any of its subs. In order to service these calls, a clause of $fix_param/2 is generated for each ancestor having parameters. Such a clause may be regarded as the collapsed chain of super/[1,2] definitions leading up to the ancestor.

The call objects:object_class(Class,Object) serves to pick up the '$class'/1 attribute if Object is an instance; otherwise, Class is unified with Object.

The following trace illustrates how parameters are transfered:

| ?- red_circle(2.5)::area(A).
1  1  Call: red_circle(2.5)::area(_A) ?
2  2  Call: ellipse(_,_,_):area(_A,red_circle(2.5),red_circle(2.5)) ?
3  3  Call: red_circle(_):$fix_param(ellipse(_B,_,_),red_circle(2.5)) ?
4  4  Call: objects:object_class(red_circle(_B),red_circle(2.5)) ?
4  4  Exit: objects:object_class(red_circle(2.5),red_circle(2.5)) ?
3  3  Exit: red_circle(_):$fix_param(ellipse(2.5,2.5,red),red_circle(2.5)) ?
5  3  Call: _A is 2.5*2.5*3.14159265 ?
5  3  Exit: 19.6349540625 is 2.5*2.5*3.14159265 ?
2  2  Exit: ellipse(_,_,_):area(19.6349540625,red_circle(2.5),red_circle(2.5)) ?
1  1  Exit: red_circle(2.5)::area(19.6349540625) ?

A = 19.6349540625 ?


Node:Obj Examples, Previous:Obj Expand, Up:Obj Intro

Examples


Node:Classification of Birds, Next:, Previous:Obj Examples, Up:Obj Examples

Classification of Birds

This example illustrates how Prolog object can be used in classification of certain concepts. This style is common in expert system application for describing its domain.

animal :: {
        super(object) &
        relative_size(S) :-
                size(Obj_size),
                super(Obj_prototype),
                Obj_prototype :: size(Prototype_size),
                :(S is Obj_size/Prototype_size * 100)
                }.

bird :: {
        super(animal) &
        moving_method(fly) &
        active_at(daylight)
        }.

albatross :: {
        super(bird) &
        color(black_and_white) &
        size(115)
        }.

kiwi :: {
        super(bird) &
        moving_method(walk) &
        active_at(night) &
        size(40) &
        color(brown)
        }.

albert :: {
        super(albatross) &
        size(120)
        }.

ross :: {
        super(albatross) &
        size(40)
        }.

| ?- ross :: relative_size(R).

R = 34.78


Node:Inheritance and Delegation, Next:, Previous:Classification of Birds, Up:Obj Examples

Inheritance and Delegation

The following example illustrates a number of concepts. Firstly, how to use SICStus Objects for defining traditional classes a la Smalltalk, or other traditional object oriented languages. Secondly, how to create instances of these classes. Finally, how to access instance variables.

The concept of instance variables is readily available as the variables belonging to the instances created dynamically and not to the class of the instances. For example, each instance of the class point will have two instance variables, x and y, represented by the attributes x/1 and y/1. The traditional class variables are easily available by accessing the same attributes in the associated class.

Another issue is the pattern used to create new instances. For example, to create an instance of the class history_point, the following code is used:

        new(Instance, xy(IX,IY)) :-
                super <: new(Instance, xy(IX,IY)),
                Instance :: set(history([(IX,IY)])) &

Note that the delegation of new/2 to super is necessary in order to create an object whose super is history_point and not point.

The example shows how delegation can be effective as a tool for flexible sharing of concepts in multiple inheritance. Four prototypes are defined: point, history_point, bounded_point, and bh_point. The latter is a bounded history point.

An instance of the point class is a point that moves in 2-D space and that can be displayed. An instance of the history_point class is similar to an instance of the point class but also keeps a history of all the moves made so far. An instance of bounded_point is similar to an instance of point but moves only in a region of the 2-D space. Finally an instance of bh_point inherits most of the features of a bounded_point and a history_point.

The default inheritance does not work for the methods display/1 and move/2 in bh_point. Inheritance by delegating messages to both supers of bh_point results in redundant actions, (moving and displaying the point twice). Selective delegation solves the problem. Taken from [Elshiewy 90].

point :: {
        super(object) &

        attributes([x(0),y(0)]) &

        xy(X, Y) :- get(x(X)), get(y(Y)) &

        new(Instance, xy(IX,IY)) :-
                super <: instance(Instance),
                Instance :: set(x(IX)),
                Instance :: set(y(IY)) &

        location((X,Y)) :- <: xy(X,Y) &

        move_horizontal(X) :-
                set(x(X)) &

        move_vertical(Y) :-
                set(y(Y)) &

        move(X, Y) :-
                <: move_horizontal(X),
                <: move_vertical(Y) &

        display(Terminal) :-
                <: xy(X, Y),
                Terminal :: format('point at (~d,~d)~n',[X,Y])
        }.

history_point :: {
        super(point) &

        attributes([history([])]) &

        new(Instance, xy(IX,IY)) :-
                super <: new(Instance, xy(IX,IY)),
                Instance :: set(history([(IX,IY)])) &

        move(X, Y) :-
                super <: move(X, Y),
                get(history(History)),
                set(history([(X,Y)|History])) &

        display(Terminal) :-
                super <: display(Terminal),
                <: print_history(Terminal) &

        print_history(Terminal) :-
                get(history(History)),
                Terminal :: format('with location history ~w~n',
                                   [History])
        }.

bounded_point :: {
        super(point) &

        attributes([bounds(0,0,0,0)]) &

        new(Instance, Coords, Bounds) :-
                super <: new(Instance, Coords),
                Instance :: set_bounds(Bounds) &

        set_bounds(Bounds) :-
                set(Bounds) &

        move(X, Y) :-
                <: bound_constraint(X, Y), !,
                super <: move(X, Y) &
        move(_, _) &

        bound_constraint(X, Y) :-
                get(bounds(X0, X1, Y0, Y1)),
                :(X >= X0),
                :(X =< X1),
                :(Y >= Y0),
                :(Y =< Y1) &

        display(Terminal) :-
                super <: display(Terminal),
                <: print_bounds(Terminal) &

        print_bounds(Terminal) :-
                get(bounds(X0, X1, Y0, Y1)),
                Terminal :: format('xbounds=(~d,~d), \c
                                    ybounds=(~d,~d)~n',
                                   [X0,X1,Y0,Y1])
        }.

bh_point :: {
        super(history_point) &
        super(bounded_point) &

        new(Instance, Coords, Bounds) :-
                history_point <: new(Instance, Coords),
                Instance :: set_bounds(Bounds) &

        move(X, Y) :-
                bounded_point <: bound_constraint(X, Y), !,
                history_point <: move(X, Y) &
        move(_, _) &

        display(Terminal) :-
                bounded_point <: display(Terminal),
                history_point <: print_history(Terminal)
        }.

tty :: {
        format(X, Y) :- :format(X, Y)
       }.

point at (8,12)
xbounds=(5,15), ybounds=(5,15)
with location history [(8,12),(9,11)]


Node:PrologPlusPlus Pgms, Previous:Inheritance and Delegation, Up:Obj Examples

Prolog++ programs

Prolog++ is a product by LPA Associates for object-oriented programming extensions of LPA Prolog. Most Prolog++ programs can be easily converted into SICStus Objects programs. The following is a translation of a program for fault diagnosis in LPA's Prolog++ manual, page 83. The program illustrates a top-down diagnosis method starting from general objects to more specific objects. The problem is fault diagnosis for car maintenance. The objects have the following structure:

- faults
        - electrical
        |       - lights
        |       - starting
        |               - starter_motor
        |               - sparking
        |                       - plugs
        |                       - distributer
        - fuel_system
        - mechanical

The general diagnosis method is defined in the object faults, whereas the cause-effect relationships are defined in the specific objects e.g. the object distributor.

This program heavily uses the sub/1 method. We have tried to be as close as possible to the original formulation.

faults :: {

        super(utility) &
        dynamic(told/2) &

        /* no fault is the default */
        fault(_, _) :- :fail &

        findall :-
                <: restart,
                :: sub(Sub),
                Sub :: find(Where, Fault),
                <: print(Where, Fault),
                :fail &
        findall &

        print(Where, Fault) :-
                :writeseqnl('Location       : ', [Where]),
                :writeseqnl('Possible Fault : ', [Fault]),
                :nl &

        find(Where, Fault) :-
                self(Where),
                fault(FaultNum, Fault),
                \+ (effect(FaultNum, S),
                    contrary(S, S1),
                    exhibited(S1)
                   ),
                \+ (effect(FaultNum, SymptomNum),
                    \+ exhibited(SymptomNum)) &

        find(Where, Fault) :-
                sub(Sub),
                Sub :: find(Where, Fault) &

        exhibited(S) :-
                :: told(S, R), !,
                R = yes &
        exhibited(S) :-
                symptom(S,Text),
                (   :yesno([Text]) -> R = yes
                ;   R = no
                ),
                :: asserta(told(S,R)),
                R = yes &

        restart :-
                :: retractall(told(_,_))

        }.

electrical :: {
        super(faults)
        }.

fuel_system :: {
        super(faults)
        }.

mechanical :: {
        super(faults)
        }.

lights :: {
        super(electrical)
        }.

sparking :: {
        super(electrical)
        }.

starting :: {
        super(electrical)
        }.

starter_motor :: {
        super(electrical)
        }.

plugs :: {
        super(sparking)
        }.

engine :: {
        super(mechanical)
        }.

cylinders :: {
        super(engine)
        }.

distributor :: {
        super(sparking) &

        /* faults */
        fault('F1001', 'Condensation in distributor cap') &
        fault('F1002', 'Faulty distributor arm') &
        fault('F1003', 'Worn distributor brushes') &

        /* symptoms */
        symptom('S1001', 'Starter turns, but engine does not fire') &
        symptom('S1002', 'Engine has difficulty starting') &
        symptom('S1003', 'Engine cuts out shortly after starting') &
        symptom('S1004', 'Engine cuts out at speed') &

        /* symptoms contrary to each other */
        contrary('S1002', 'S1001') &
        contrary('S1003', 'S1001') &

        /* causal-effect relationship */
        effect('F1001', 'S1001') &
        effect('F1002', 'S1001') &
        effect('F1002', 'S1004') &
        effect('F1003', 'S1002') &
        effect('F1003', 'S1003')

        }.


yesno(Value) :- write(Value), nl, read(yes).

writeseqnl(Prompt, L) :- write(Prompt), write_seq(L).

write_seq([]).
write_seq([X|L]) :- write(X), write(' '), write_seq(L), nl.

faults :- faults :: findall.


| ?- faults.
[Starter turns, but engine does not fire]
|: yes.
Location       : distributor
Possible Fault : Condensation in distributor cap

[Engine cuts out at speed]
|: yes.
Location       : distributor
Possible Fault : Faulty distributor arm


yes
| ?- faults.
[Starter turns, but engine does not fire]
|: no.
[Engine has difficulty starting]
|: yes.
[Engine cuts out shortly after starting]
|: yes.
Location       : distributor
Possible Fault : Worn distributor brushes


Node:PiLLoW, Next:, Previous:Obj Intro, Up:Top

The PiLLoW Web Programming Library

The PiLLoW library ("Programming in Logic Languages on the Web") is a free Internet/WWW programming library for Logic Programming Systems which simplifies the process of writing applications for such environment. The library provides facilities for generating HTML or XML structured documents by handling them as Prolog terms, producing HTML forms, writing form handlers, processing HTML templates, accessing and parsing WWW documents (either HTML or XML), accessing code posted at HTTP addresses, etc.

PiLLoW is documented in its own reference manual, located in http://www.clip.dia.fi.upm.es/Software/pillow/pillow_doc_html/pillow_doc_toc.html (HTML) or http://www.clip.dia.fi.upm.es/Software/pillow/pillow_doc.ps (Postscript). The following points are worth noting wrt. the PiLLoW reference manual:

Further information can be found at the PiLLoW home page, http://clip.dia.fi.upm.es/Software/pillow/pillow.html.


Node:Tcl/Tk library, Next:, Previous:PiLLoW, Up:Top

Tcl/Tk library


Node:Introduction (Tcl), Next:, Previous:Tcl/Tk library, Up:Tcl/Tk library

Introduction

This is a basic tutorial for those SICStus Prolog users who would like to add Tcl/Tk user interfaces to their Prolog applications. The tutorial assumes no prior knowledge of Tcl/Tk but, of course, does assume the reader is proficient in Prolog.

Aware that the reader may not have heard of Tcl/Tk, we will start by answering three questions: what is Tcl/Tk? what is it good for? what relationship does it have to Prolog?


Node:What is Tcl/Tk?, Next:, Previous:Introduction (Tcl), Up:Introduction (Tcl)

What is Tcl/Tk?

Tcl/Tk, as its title suggests, is actually two software packages: Tcl and Tk. Tcl, pronounced tickle, stands for tool command language and is a scripting language that provides a programming environment and programming facilities such as variables, loops, and procedures. It is designed to be easily extensible.

Tk, pronounced tee-kay, is just such an extension to Tcl which is a toolkit for windowing systems. In other words, Tk adds facilities to Tcl for creating and manipulating user interfaces based on windows and widgets within those windows.


Node:What is Tcl/Tk good for?, Next:, Previous:What is Tcl/Tk?, Up:Introduction (Tcl)

What is Tcl/Tk good for?

In combination the Tcl and Tk packages (we will call the combination simply Tcl/Tk) are useful for creating graphical user interfaces (GUIs) to applications. The GUI is described in terms of instances of Tk widgets, created through calls in Tcl, and Tcl scripts that form the glue that bind together the GUI and the application. (If you are a little lost at this point, all will be clear in a moment with a simple example.)

There are lots of systems out there for adding GUIs to applications so why choose Tcl/Tk? Tcl/Tk has several advantages that make it attractive for this kind of work. Firstly, it is good for rapid prototyping of GUIs. Tcl is an interpreted scripting language. The scripts can be modified and executed quickly, with no compilation phase, so speeding up the development loop.

Secondly, it is easier to use a system based on a scripting language, such as Tcl/Tk, than many of the conventional packages available. For example, getting to grips with the X windows suite of C libraries is not an easy task. Tcl/Tk can produce the same thing using simple scripting with much less to learn. The penalty for this is that programs written in an interpreted scripting language will execute more slowly than those written using compiled C library calls, but for many interfaces that do not need great speed Tcl/Tk is fast enough and its ease of use more than outweighs the loss of speed. In any case, Tcl/Tk can easily handle hundreds of events per mouse movement without the user noticing.

Thirdly, Tcl/Tk is good for making cross-platform GUIs. The Tk toolkit has been ported to native look-and-feel widgets on Mac, PC (Windows), and UNIX (X windows) platforms. You can write your scripts once and they will execute on any of these platforms.

Lastly, the software is distributed under a free software license and so is available in both binary and source formats free of charge.


Node:What is Tcl/Tks relationship to SICStus Prolog?, Next:, Previous:What is Tcl/Tk good for?, Up:Introduction (Tcl)

What is Tcl/Tks relationship to SICStus Prolog?

SICStus Prolog comes with a Prolog library for interfacing to Tcl/Tk. The purpose of the library is to enable Prolog application developers to add GUIs to their applications rapidly and easily.


Node:A quick example of Tcl/Tk in action, Next:, Previous:What is Tcl/Tks relationship to SICStus Prolog?, Up:Introduction (Tcl)

A quick example of Tcl/Tk in action

As a taster, we will show you two simple examples programs that use SICStus Prolog with the Tcl/Tk extensions: the ubiquitous "hello world" example; and a very simple telephone book look up example.

You are not expected to understand how these examples work at this stage. They are something for you to quickly type in to see how easy it is to add GUIs to Prolog programs through Tcl/Tk. After reading through the rest of this tutorial you will fully understand these examples and be able to write your own GUIs.


Node:hello world, Next:, Previous:A quick example of Tcl/Tk in action, Up:A quick example of Tcl/Tk in action

hello world

Here is the program; also in library('tcltk/examples/ex1.pl'):

:- use_module(library(tcltk)).

go :-
    tk_new([name('Example 1')], Interp),
    tcl_eval(Interp, 'button .fred -text "hello world" -command { puts "hello world"}', _),
    tcl_eval(Interp, 'pack .fred', _),
    tk_main_loop.

images/tcltkex1.png

SICStus+Tcl/Tk hello world program.

To run it just start up SICStus (on Windows use sicstus, not spwin), load the program, and evaluate the Prolog goal go. The first line of the go clause calls tk_new/2 which creates a Tcl/Tk interpreter and returns a handle Interp through which Prolog will interact with the interpreter. Next a call to tcl_eval/3 is made which creates a button displaying the hello world text. Next a call is made to tcl_eval/3 that causes the button to be displayed in the main application window. Finally, a call is make to tk_main_loop/0 that passes control to Tcl/Tk, making sure that window events are serviced.

See how simple it is with just a three line Prolog program to create an application window and display a button in it. Click on the button and see what it does.

The reason you should use sicstus on Windows instead of spwin is that the latter does not have the C standard streams (stdin,stdout,stderr) and the Tcl command puts will give an error if there is no stdout.


Node:telephone book, Previous:hello world, Up:A quick example of Tcl/Tk in action

telephone book

The previous example showed us how to create a button and display some text in it. It was basically pure Tcl/Tk generated from within Prolog but did not have any interaction with Prolog. The following example demonstrates a simple callback mechanism. A name is typed into an text entry box, a button is pressed which looks up the telephone number corresponding to the name in a Prolog clause database, and the telephone number is then displayed.

Here is the code; also in library('tcltk/examples/ex2.pl'):

:- use_module(library(tcltk)).

telephone(fred, '123-456').
telephone(wilbert, '222-2222').
telephone(taxi, '200-0000').
telephone(mary, '00-36-1-666-6666').

go :-
     tk_new([name('Example 2')], T),
     tcl_eval(T, 'entry .name -textvariable name',_),
     tcl_eval(T, 'button .search -text search -command {
                      prolog telephone($name,X);
                      set result $prolog_variables(X) }', _),
     tcl_eval(T, 'label .result -relief raised -textvariable result', _),
     tcl_eval(T, 'pack .name .search .result -side top -fill x', _),
     tk_main_loop.

images/tcltkex2.png

SICStus+Tcl/Tk telephone number lookup

Again, to run the example, start up SICStus Prolog, load the code, and run the goal go.

You will notice that three widgets will appear in a window: one is for entering the name of the person or thing that you want to find the telephone number for, the button is for initiating the search, and the text box at the bottom is for displaying the result.

Type fred into the entry box, hit the search button and you should see the phone number displayed. You can then try the same thing but with wilbert, taxi or mary typed into the text entry box.

What is happening is that when the button is pressed, the value in the entry box is retrieved, then the telephone/2 predicate is called in Prolog with the entry box value as first argument, then the second argument of telephone is retrieved (by this time bound to the number) and is displayed below the button.

This is a very crude example of what can be done with the Tcl/Tk module in Prolog. For example, this program does not handle cases where there is no corresponding phone number or where there is more than one corresponding phone number. The example is just supposed to wet your appetite, but all these problems can be handled by Prolog + Tcl/Tk, although with a more sophisticated program. You will learn how to do this in the subsequent chapters.


Node:Outline of this tutorial, Previous:A quick example of Tcl/Tk in action, Up:Introduction (Tcl)

Outline of this tutorial

Now we have motivated using Tcl/Tk as a means of creating GUIs for Prolog programs, this document goes into the details of using Tcl/Tk as a means of building GUIs for SICStus Prolog applications.

Firstly, Tcl is introduced and its syntax and core commands described. Then the Tk extensions to Tcl are introduced. We show how with Tcl and Tk together the user can build sophisticated GUIs easily and quickly. At the end of this Tcl/Tk part of the tutorial an example of a pure Tcl/Tk program will be presented together with some tips on how to design and code Tcl/Tk GUIs.

The second phase of this document describes the SICStus Prolog tcltk library. It provides extensions to Prolog that allow Prolog applications to interact with Tcl/Tk: Prolog can make calls to Tcl/Tk code and vice versa.

Having reached this point in the tutorial the user will know how to write a Tcl/Tk GUI interface and how to get a Prolog program to interact with it, but arranging which process (the Prolog process or the Tcl/Tk process) is the dominant partner is non-trivial and so is described in a separate chapter on event handling. This will help the user choose the most appropriate method of cooperation between Tcl/Tk and Prolog to suit their particular application.

This section, the Tcl/Tk+Prolog section, will be rounded off with the presentation of some example applications that make use of Tcl/Tk and Prolog.

Then there is a short discussion section on how to use other Tcl extension packages with Tcl/Tk and Prolog. Many such extension packages have been written and when added to Prolog enhanced with Tcl/Tk can offer further functionality to a Prolog application.

The appendices provide a full listing with description of the predicates available in the tcltk SICStus Prolog library, and the extensions made to Tcl/Tk for interacting with Prolog.

Lastly, a section on resources gives pointers to where the reader can find more information on Tcl/Tk.


Node:Tcl, Next:, Previous:Introduction (Tcl), Up:Tcl/Tk library

Tcl

Tcl is an interpreted scripting language. In this chapter, first the syntax of Tcl is described and then the core commands are described. It is not intended to give a comprehensive description of the Tcl language here but an overview of the core commands, enough to get the user motivated to start writing their own scripts.

For pointers to more information on Tcl; see Resources.


Node:Syntax (Tcl), Next:, Previous:Tcl, Up:Tcl

Syntax

A Tcl script consists of a series of strings separated from each other by a newline character. Each string contains a command or series of semi-colon separated commands. A command is a series of words separated by spaces. The first word in a command is the name of the command and subsequent words are its arguments.

An example is:

set a 1
set b 2

which is a Tcl script of two commands: the first command sets the value of variable a to 1, and the second command sets the value of variable b to 2.

An example of two commands on the same line separated by a semi-colon is:

set a 1; set b 2

which is equivalent to the previous example but written entirely on one line.

A command is executed in two phases. In the first phase, the command is broken down into its constituent words and various textual substitutions are performed on those words. In the second phase, the procedure to call is identified from the first word in the command, and the procedure is called with the remaining words as arguments.

There are special syntactic characters that control how the first phase, the substitution phase, is carried out. The three major substitution types are variable substitution, command substitution, and backslash substitution.


Node:Variable substitution, Next:, Previous:Syntax (Tcl), Up:Syntax (Tcl)

Variable substitution

Variable substitution happens when a $ prefixed word is found in a command. There are three types of variable substitution:

An example of variable substitution is:

set a 1
set b $a

which sets the value of variable a to 1, and then sets the value of variable b to the value of variable a.


Node:Command substitution, Next:, Previous:Variable substitution, Up:Syntax (Tcl)

Command substitution

Command substitution happens when a word contains an open square bracket, [. The string between the open bracket and matching closing bracket are treated as a Tcl script. The script is evaluated and its result is substituted in place of the original command substitution word.

A simple example of command substitution is:

set a 1
set b [set a]

which does the same as the previous example but using command substitution. The result of a set a command is to return the value of a which is then passed as an argument to set b and so variable b acquires the value of variable a.


Node:Backslash substitution, Next:, Previous:Command substitution, Up:Syntax (Tcl)

Backslash substitution

Backslash substitution is performed whenever the interpreter comes across a backslash. The backslash is an escape character and when it is encountered is causes the interpreter to handle the next characters specially. Commonly escaped characters are \a for audible bell, \b for backspace, \f for form feed, \n for newline, \r for carriage return, \t for horizontal tab, and \v for vertical tab. Double-backslash, \\, is substituted with a single backslash. Other special backslash substitutions have the following forms:

Any other character that is backslash escaped is simply substituted by the character itself. For example, \W is replaced by W.


Node:Delaying substitution, Next:, Previous:Backslash substitution, Up:Syntax (Tcl)

Delaying substitution

A further syntactic construction is used to delay substitution. When the beginning of a word starts with a curly bracket, {, it does not do any of the above substitutions between the opening curly bracket and its matching closing curly bracket. The word ends with the matching closing curly bracket. This construct is used to make the bodies of procedures in which substitutions happen when the procedure is called, not when it is constructed. Or it is used anywhere when the programmer does not want the normal substitutions to happen. For example:

puts {I have $20}

will print the string I have $20 and will not try variable substitution on the $20 part.

A word delineated by curly brackets is replaced with the characters within the brackets without performing the usual substitutions.


Node:Double-quotes, Previous:Delaying substitution, Up:Syntax (Tcl)

Double-quotes

A word can begin with a double-quote and ending with the matching closing double-quote. Substitutions as detailed above are done on the characters between the quotes, and the result is then substituted for the original word. Typically double-quotes are used to group sequences of characters that contain spaces into a single command word.

For example:

set name "Fred the Great"
puts "Hello my name is $name"

outputs Hello my name is Fred the Great. The first command sets the value of variable name to the following double-quoted string "Fred the Great". The the next command prints its argument, a single argument because it is a word delineated by double-quotes, that has had variable substitution performed on it.

Here is the same example but using curly brackets instead of double-quotes:

set name {Fred the Great}
puts {Hello my name is $name}

gives the output Hello my name is $name because substitutions are suppressed by the curly bracket notation.

And again the same example but without either curly brackets or double-quotes:

set name Fred the Great
puts Hello my name is $name

simply fails because both set and puts expect a single argument but without the word grouping effects of double-quotes or curly brackets they find that they have more than one argument and throw an exception.

Being a simple scripting language, Tcl does not have any real idea of data types. The interpreter simply manipulates strings. The Tcl interpreter is not concerned with whether those strings contain representations of numbers or names or lists. It is up to the commands themselves to interpret the strings that are passed to them as arguments in any manner those choose.


Node:Variables (Tcl), Next:, Previous:Syntax (Tcl), Up:Tcl

Variables

This has been dealt with implicitly above. A variable has a name and a value. A name can be any string whatsoever, as can its value.

For example,

set "Old King Cole" "merry soul"

sets the value of the variable named Old King Cole to the value merry soul. Variable names can also be numbers:

set 123 "one two three"

sets the variable with name 123 to the value one two three. In general, it is better to use the usual conventions -- start with a letter then follow with a combination of letters, digits, and underscores -- when giving variables names to avoid confusion.

Array variables are also available in Tcl. These are denoted by an array name followed by an array index enclosed in round brackets. As an example:

set fred(one) 1
set fred(two) 2

will set the variable fred(one) to the value 1 and fred(two) to the value 2.

Tcl arrays are associative arrays in that both the array name and the array index can be arbitrary strings. This also makes multidimensional arrays possible if the index contains a comma:

set fred(one,two) 12

It is cheating in that the array is not stored as a multidimensional array with a pair of indices, but as a linear array with a single index that happens to contain a comma.


Node:Commands, Next:, Previous:Variables (Tcl), Up:Tcl

Commands

Now that the Tcl syntax and variables have been been dealt with, we will now look at some of the commands that are available.

Each command when executed returns a value. The return value will be described along with the command.


Node:Notation (Tcl), Next:, Previous:Commands, Up:Commands

Notation

A quick word about the notation used to describe Tcl commands. In general, a description of a command is the name of the command followed by its arguments separated by spaces. An example is:

set varName ?value?

which is a description of the Tcl set command, which takes a variable name varName and an optional argument, a value.

Optional arguments are enclosed in question mark, ?, pairs, as in the example.

A series of three dots ... represents repeated arguments. An example is a description of the unset command:

unset varName ?varName varName ...?

which shows that the unset command has at least one compulsory argument varName but has any number of subsequent optional arguments.


Node:Commands to do with variables, Next:, Previous:Notation (Tcl), Up:Commands

Commands to do with variables

The most used command over variables is the set command. It has the form

set varName ?value?

The value of value is determined, the variable varName is set to it, and the value is returned. If there is no value argument then simply the value of the variable is returned. It is thus used to set and/or get the value of a variable.

The unset command is used to remove variables completely from the system:

unset varName ?varName varName ...?

which given a series of variable names deletes them. The empty string is always returned.

There is a special command for incrementing the value of a variable:

incr varName ?increment?

which, given the name of a variable thats value is an integer string, increments it by the amount increment. If the increment part is left out then it defaults to 1. The return value is the new value of the variable.


Node:Expressions, Next:, Previous:Commands to do with variables, Up:Commands

Expressions

Expressions are constructed from operands and operators and can then be evaluated. The most general expression evaluator in Tcl is the expr command:

expr arg ?arg arg ... arg?

which evaluates its arguments as an expression and returns the value of the evaluation.

A simple example expression is

expr 2 * 2

which when executed returns the value 4.

There are different classes of operators: arithmetic, relational, logical, bitwise, and choice. Here are some example expressions involving various operators:

arithmetic $x * 2
relational $x > 2
logical ($x == $y) || ($x == $z)
bitwise 8 & 2
choice ($a == 1) ? $x : $y

Basically the operators follow the syntax and meaning of their ANSI C counterparts.

Expressions to the expr command can be contained in curly brackets in which case the usual substitutions are not done before the expr command is evaluated, but the command does its own round of substitutions. So evaluating a script such as:

set a 1
expr { ($a==1) : "yes" ? "no" }

will evaluate to yes.

Tcl also has a whole host of math functions that can be used in expressions. Their evaluation is again the same as that for their ANSI C counterparts. For example:

expr { 2*log($x) }

will return 2 times the natural log of the value of variable x.


Node:Lists (Tcl), Next:, Previous:Expressions, Up:Commands

Lists

Tcl has a notion of lists, but as with everything it is implemented through strings. A list is a string that contains words.

A simple list is just a space separated series of strings:

set a {one two three four five}

will set the variable a to the list containing the five strings shown. The empty list is denoted by an open and close curly bracket pair with nothing in between: {}.

For the Prolog programmer, there is much confusion between a Prolog implementation of lists and the Tcl implementation of lists. In Prolog we have a definite notion of the printed representation of a list: a list is a sequence of terms enclosed in square brackets (we ignore dot notation for now); a nested list is just another term.

In Tcl, however, a list is really just a string that conforms to a certain syntax: a string of space separated words. But in Tcl there is more than one way of generating such a string. For example,

set fred {a b c d}

sets fred to

"a b c d"

as does

set fred "a b c d"

because {a b c d} evaluates to the string a b c d which has the correct syntax for a list. But what about nested lists? Those are represented in the final list-string as being contained in curly brackets. For example:

set fred {a b c {1 2 3} e f}

results in fred having the value

"a b c {1 2 3} e f"

The outer curly brackets from the set command have disappeared which causes confusion. The curly brackets within a list denote a nested list, but there are no curly brackets at the top-level of the list. (We can't help thinking that life would have been easier if the creators of Tcl would have chosen a consistent representation for lists, as Prolog and LISP do.)

So remember: a list is really a string with a certain syntax, space separated items or words; a nested list is surrounded by curly brackets.

There are a dozen commands that operate on lists.

concat ?list list ...?

This makes a list out of a series of lists by concatenating its argument lists together. The return result is the list resulting from the concatenation.

lindex list index

returns the index-th element of the list. The first element of a list has an index of 0.

linsert list index value ?value ...?

returns a new list in which the value arguments have been inserted in turn before the index-th element of list.

list ?value value ...?

returns a list where each element is one of the value arguments.

llength list

returns the number of elements in list list.

lrange list first last

returns a slice of a list consisting of the elements of the list list from index first until index last.

lreplace list first last ?value ... value?

returns a copy of list list but with the elements between indices first and last replaced with a list formed from the value arguments.

lsearch ?-exact? ?-glob? ?-regexp? list pattern

returns the index of the first element in the list that matches the given pattern. The type of matching done depends on which of the switch is present -exact, -glob, -regexp, is present. Default is -glob.

lsort ?-ascii? ?-integer? ?-real? ?-command command? ?-increasing? ?-decreasing{? list

returns a list which is the original list list sorted by the chosen technique. If none of the switches supplies the intended sorting technique then the user can provide one through the -command command switch.

There are also two useful commands for converting between lists and strings:

join list ?joinString?

which concatenates the elements of the list together, with the separator joinString between them, and returns the resulting string. This can be used to construct filenames; for example:

set a {{} usr local bin}
set filename [join $a /]

results in the variable filename having the value /usr/local/bin.

The reverse of the join command is the split command:

split string ?splitChars?

which takes the string string and splits it into string on splitChars boundaries and returns a list with the strings as elements. An example is splitting a filename into its constituent parts:

set a [split /usr/local/src /]

gives a the value {{} usr local src}, a list.


Node:Control flow, Next:, Previous:Lists (Tcl), Up:Commands

Control flow

Tcl has the four usual classes of control flow found in most other programming languages:

if...elseif...else, while, for, foreach, switch, and eval.

We go through each in turn.

The general form of an if command is the following:

if test1 body1 ?elseif test2 body2 elseif ...? ?else bodyn?

which when evaluated, evaluates expression test1 which if true causes body1 to be evaluated, but if false, causes test2 to be evaluated, and so on. If there is a final else clause then its bodyn part is evaluated if all of the preceding tests failed. The return result of an if statement is the result of the last body command evaluated, or the empty list if none of the bodies are evaluated.

Conditional looping is done through the while command:

while test body

which evaluates expression test which if true then evaluates body. It continues to do that until test evaluates to 0, and returns the empty string.

A simple example is:

set a 10
while {$a > 0} { puts $a; incr a -1 }

which initializes variable a with value ten and then loops printing out the value of a and decrementing it until its value is 0, when the loop terminates.

The for loop has the following form:

for init test reinit body

which initializes the loop by executing init, then each time around the loop the expression test is evaluated which if true causes body to be executed and then executes reinit. The loop spins around until test evaluates to 0. The return result of a for loop is the empty string.

An example of a for loop:

for {set a 10} ($a>0) {incr a -1} {puts $a}

which initializes the variable a with value 10, then goes around the loop printing the value of a and decrementing it as long as its value is greater than 0. Once it reaches 0 the loop terminates.

The foreach command has the following form:

foreach varName list body

where varName is the name of a variable, list is an instance of a list, and body is a series of commands to evaluate. A foreach then iterates over the elements of a list, setting the variable varName to the current element, and executes body. The result of a foreach loop is always the empty string.

An example of a foreach loop:

foreach friend {joe mary john wilbert} {puts "I like $friend"}

will produce the output:

I like joe
I like mary
I like john
I like wilbert

There are also a couple of commands for controlling the flow of loops: continue and break.

continue stops the current evaluation of the body of a loop and goes on to the next one.

break terminates the loop altogether.

Tcl has a general switch statement which has two forms:

switch ?options? string pattern body ?pattern body ... ?
switch ?options? string { pattern body ?pattern body ...? }

When executed, the switch command matches its string argument against each of the pattern arguments, and the body of the first matching pattern is evaluated. The matching algorithm depends on the options chosen which can be one of

-exact use exact matching
-glob use glob-style matching
-regexp use regular expression matchinig

An example is:

set a rob
switch -glob $a {
    a*z { puts "A to Z"}
    r*b { puts "rob or rab"}
}

which will produce the output:

rob or rab

There are two forms of the switch command. The second form has the command arguments surrounded in curly brackets. This is primarily so that multi-line switch commands can be formed, but it also means that the arguments in brackets are not evaluated (curly brackets suppress evaluation), whereas in the first type of switch statement the arguments are first evaluated before the switch is evaluated. These effects should be borne in mind when choosing which kind of switch statement to use.

The final form of control statement is eval:

eval arg ?arg ...?

which takes one or more arguments, concatenates them into a string, and executes the string as a command. The return result is the normal return result of the execution of the string as a command.

An example is

set a b
set b 0
eval set $a 10

which results in the variable b being set to 10. In this case, the return result of the eval is 10, the result of executing the string "set b 10" as a command.


Node:Commands over strings, Next:, Previous:Control flow, Up:Commands

Commands over strings

Tcl has several commands over strings. There are commands for searching for patterns in strings, formatting and parsing strings (much the same as printf and scanf in the C language), and general string manipulation commands.

Firstly we will deal with formatting and parsing of strings. The commands for this are format and scan respectively.

format formatString ?value value ...?

which works in a similar to C's printf; given a format string with placeholders for values and a series of values, return the appropriate string.

Here is an example of printing out a table for base 10 logarithms for the numbers 1 to 10:

for {set n 1} {$n <= 10} {incr n} {
    puts [format "log10(%d) = %.4f" $n [expr log10($n)]]
}

which produces the output

ln(1) = 0.0000
ln(2) = 0.3010
ln(3) = 0.4771
ln(4) = 0.6021
ln(5) = 0.6990
ln(6) = 0.7782
ln(7) = 0.8451
ln(8) = 0.9031
ln(9) = 0.9542
ln(10) = 1.0000

The reverse function of format is scan:

scan string formatString varName ?varName ...?

which parses the string according to the format string and assigns the appropriate values to the variables. it returns the number of fields successfully parsed.

An example,

scan "qty 10, unit cost 1.5, total 15.0" \
     "qty %d, unit cost %f, total %f"    \
     quantity cost_per_unit total

would assign the value 10 to the variable quantity, 1.5 to the variable cost_per_unit and the value 15.0 to the variable total.

There are commands for performing two kinds of pattern matching on strings: one for matching using regular expressions, and one for matching using UNIX-style wildcard pattern matching (globbing).

The command for regular expressions matching is as follows:

regexp ?-indices? ?-nocase? exp string ?matchVar? ?subVar subVar ...?

where exp is the regular expression and string is the string on which the matching is performed. The regexp command returns 1 if the expression matches the string, 0 otherwise. The optional -nocase switch does matching without regard to the case of letters in the string. The optional matchVar and subVar variables, if present, are set to the values of string matches. In the regular expression, a match that is to be saved into a variable is enclosed in round braces. An example is

regexp {([0-9]+)} "I have 3 oranges" a

will assign the value 3 to the variable a.

If the optional switch -indices is present then instead of storing the matching substrings in the variables, the indices of the substrings are stored; that is a list with a pair of numbers denoting the start and end position of the substring in the string. Using the same example:

regexp -indices {([0-9]+)} "I have 3 oranges" a

will assign the value "7 7", because the matched numeral 3 is in the eighth position in the string, and indices count from 0.

String matching using the UNIX-style wildcard pattern matching technique is done through the string match command:

string match pattern string

where pattern is a wildcard pattern and string is the string to match. If the match succeeds, the command returns 1; otherwise, it returns 0. An example is

string match {[a-z]*[0-9]} {a_$%^_3}

which matches because the command says match any string that starts with a lower case letter and ends with a number, regardless of anything in between.

There is a command for performing string substitutions using regular expressions:

regsub ?-all? ?-nocase? exp string subSpec varName

where exp is the regular expression and string is the input string on which the substitution is made, subSpec is the string that is substituted for the part of the string matched by the regular expression, and varName is the variable on which the resulting string is copied into. With the -nocase switch, then the matching is done without regard to the case of letters in the input string. The -all switch causes repeated matching and substitution to happen on the input string. The result of a regsub command is the number of substitutions made.

An example of string substitution is:

regsub {#name#} {My name is #name#} Rob result

which sets the variable result to the value "My name is Rob". An example of using the -all switch:

regsub -all {#name#} {#name#'s name is #name#} Rob result

sets the variable result to the value "Rob's name is Rob" and it returns the value 2 because two substitutions were made.

The are a host of other ways to manipulate strings through variants of the string command. Here we will go through them.

To select a character from a string given the character position, use the string index command. An example is:

string index "Hello world" 6

which returns w, the 7th character of the string. (Strings are indexed from 0).

To select a substring of a string, given a range of indices use the string range command. An example is:

string range "Hello world" 3 7

which returns the string "lo wo". There is a special index marker named end which is used to denote the the end of a string, so the code

string range "Hello world" 6 end

will return the string "world".

There are two ways to do simple search for a substring on a string, using the string first and string last commands. An example of string first is:

string first "dog" "My dog is a big dog"

find the first position in string "My dog is a big dog" that matches "dog". It will return the position in the string in which the substring was found, in this case 3. If the substring cannot be found then the value -1 is returned.

Similarly,

string last "dog" "My dog is a big dog"

will return the value 16 because it returns the index of the last place in the string that the substring matches. Again, if there is no match, -1 is returned.

To find the length of a string use string length which given a string simply returns its length.

string length "123456"

returns the value 6.

To convert a string completely to upper case use string toupper:

string toupper "this is in upper case"

returns the string "THIS IS IN UPPER CASE".

Similarly,

string tolower "THIS IS IN LOWER CASE"

returns the string "this is in lower case".

There are commands for removing characters from strings: string trim, string trimright, and string trimleft.

string trim string ?chars?

which removes the characters in the string chars from the string string and returns the trimmed string. If chars is not present, then whitespace characters are removed. An example is:

string string "The dog ate the exercise book" "doe"

which would return the string "Th g at th xrcis bk".

string trimleft is the same as string trim except only leading characters are removed. Similarly string trimright removes only trailing characters. For example:

string trimright $my_input

would return a copy of the string contained in $my_input but with all the trailing whitespace characters removed.


Node:File I/O, Next:, Previous:Commands over strings, Up:Commands

File I/O

There is a comprehensive set of commands for file manipulation. We will cover only the some of the more important ones here.

To open a file the open command is used:

open name ?access?

where name is a string containing the filename, and the option access parameter contains a string of access flags, in the UNIX style. The return result is a handle to the open file.

If access is not present then the access permissions default to "r" which means open for reading only. The command returns a file handle that can be used with other commands. An example of the use of the open command is

set fid [open "myfile" "r+"]

which means open the file myfile for both reading and writing and set the variable fid to the file handle returned.

To close a file simply use

close fileId

For example,

close $fid

will close the file that has the file handle stored in the variable fid.

To read from a file, the read command is used:

read fileId numBytes

which reads numBytes bytes from the file attached to file handle fileId, and returns the bytes actually read.

To read a single line from a file use gets:

gets fileId ?varName?

which reads a line from the file attached to file handle fileId but chops off the trailing newline. If variable varName is specified then the string read in is stored there and the number of bytes is returned by the command. If the variable is not specified, then the command returns the string only.

To write to a file, use puts:

puts ?-nonewline? ?fileId? string

which outputs the string string. If the file handle fileId is present then the string is output to that file; otherwise, it is printed on stdout. If the switch -nonewline is present then a trailing newline is not output.

To check if the end of a file has been reached, use eof:

eof fileId

which, given a file handle fileId returns 1 if the end has been reached, and 0 otherwise.

The are a host of other commands over files and processes which we will not go into here.

(For extra information on file I/O commands, refer to the Tcl manual pages.)


Node:User defined procedures, Next:, Previous:File I/O, Up:Commands

User defined procedures

Tcl provides a way of creating new commands, called procedures, that can be executed in scripts. The arguments of a procedure can be call-by-value or call-by-reference, and there is also a facility for creating new user defined control structures using procedures.

A procedure is declared using the proc command:

proc name argList body

where the name of the procedure is name, the arguments are contained in argList and the body of the procedure is the script body. An example of a procedure is:

proc namePrint { first family } {
    puts "My first name is $first"
    puts "My family name is $family"
}

which can be called with

namePrint Tony Blair

to produce the output:

My first name is Tony
My family name is Blair

A procedure with no arguments is specified with an empty argument list. An example is a procedure that just prints out a string:

proc stringThing {} {
    puts "I just print this string"
}

Arguments can be given defaults by pairing them with a value in a list. An example here is a counter procedure:

proc counter { value { inc 1 } } {
    eval $value + $inc
}

which can be called with two arguments like this

set v 10
set v [counter $v 5]

which will set variable v to the value 15; or it can be called with one argument:

set v 10
set v [counter $v]

in which case v will have the value 11, because the default of the argument inc inside the procedure is the value 1.

There is a special argument for handling procedures with variable number of arguments, the args argument. An example is a procedure that sums a list of numbers:

proc sum { args } {
    set result 0;

    foreach n $args {
     set result [expr $result + $n ]
    }

    return $result;
}

which can be called like this:

sum 1 2 3 4 5

which returns the value 15.

The restriction on using defaulted arguments is that all the arguments that come after the defaulted ones must also be defaulted. If using args then it must be the last argument in the argument list.

A procedure can return a value through the return command:

return ?options? ?value?

which terminates the procedure returning value value, if specified, or just causes the procedure to return, if no value specified. (The ?options? part has to do with raising exceptions which we will will not cover here.)

The return result of a user defined procedure is the return result of the last command executed by it.

So far we have seen the arguments of a procedure are passed using the call-by-value mechanism. They can be passed call by reference using the upvar command:

upvar ?level? otherVar1 myVar1 ?otherVar2 myVar2 ...?

which makes accessible variables somewhere in a calling context with the current context. The optional argument level describes how many calling levels up to look for the variable. This is best shown with an example:

set a 10
set b 20

proc add { first second } {
    upvar $first f $second s
    expr $f+$s
}

which when called with

add a b

will produce the result 30. If you use call-by-value instead:

add $a $b

then the program will fail because when executing the procedure add it will take the first argument 10 as the level argument, a bad level. (Also variable 20 doesn't exist at any level.)

New control structures can be generated using the uplevel command:

uplevel ?level? arg ?arg arg ...?

which is like eval, but it evaluates its arguments in a context higher up the calling stack. How far up the stack to go is given by the optional level argument.

proc do { loop condition } {
    set nostop 1

    while { $nostop } {
        uplevel $loop
        if {[uplevel "expr $condition"] == 0} {
            set nostop 0
         }
    }
}

which when called with this

set x 5
do { puts $x; incr x -1 } { $x > 0 }

will print

5
4
3
2
1

(NOTE: this doesn't quite work for all kinds of calls because of break, continue, and return. It is possible to get around these problem, but that is outside the scope of this tutorial.)


Node:Global variables, Next:, Previous:User defined procedures, Up:Commands

Global variables

A word about the scope of variables. Variables used within procedures are normally created only for the duration of that procedure and have local scope.

It is possible to declare a variable as having global scope, through the global command:

global name1 ? name2 ...?

where name1, name2, ..., are the names of global variables. Any references to those names will be taken to denote global variables for the duration of the procedure call.

Global variables are those variables declared at the topmost calling context. It is possible to run a global command at anytime in a procedure call. After such a command, the variable name will refer to a global variable until the procedure exits.

An example:

set x 10

proc fred { } {
    set y 20
    global x
    puts [expr $x + $y]
}

fred

will print the result 30 where 20 comes from the local variable y and 10 comes from the global variable x.

Without the global x line, the call to fred will fail with an error because there is no variable x defined locally in the procedure for the expr to evaluate over.


Node:source, Previous:Global variables, Up:Commands

source

In common with other scripting languages, there is a command for evaluating the contents of a file in the Tcl interpreter:

source fileName

where fileName is the filename of the file containing the Tcl source to be evaluated. Control returns to the Tcl interpreter once the file has been evaluated.


Node:What we have left out (Tcl), Previous:Commands, Up:Tcl

What we have left out (Tcl)

We have left out a number of Tcl commands as they are outside of the scope of this tutorial. We list some of them here to show some of what Tcl can do. Please refer to the Tcl manual for more information.

http
implements the http protocol for retrieving web pages
namespaces
a modules systems for Tcl
trace
commands can be attached to variables that are triggered when the variable changes value (amongst other things)
processes
start, stop, and manage processes
sockets
UNIX and Internet style socket management
exception handling

3rd party extension packages
load extension packages into Tcl and use their facilities as native Tcl commands


Node:Tk, Next:, Previous:Tcl, Up:Tcl/Tk library

Tk

Tk is an extension to Tcl. It provides Tcl with commands for easily creating and managing graphical objects, or widgets, so providing a way to add graphical user interfaces (GUIs) to Tcl applications.

In this section we will describe the main Tk widgets, the Tcl commands used to manipulate them, how to give them behaviors, and generally how to arrange them into groups to create a GUI.


Node:Widgets, Next:, Previous:Tk, Up:Tk

Widgets

A widget is a "window object". It is something that is displayed that has at least two parts: a state and a behavior. An example of a widget is a button. Its state is things like what color is it, what text is written it in, and how big it is. Its behavior is things like what it does when you click on it, or what happens when the cursor is moved over or away from it.

In Tcl/Tk there are three parts to creating a useful widget. The first is creating an instance of the widget with its initial state. The second is giving it a behavior by defining how the widget behaves when certain events happen -- event handling. The third is actually displaying the widget possibly in a group of widgets or inside another widget -- geometry management. In fact, after creating all the widgets for a GUI, they are not displayed until handled by a geometry manager, which has rules about how to calculate the size of the widgets and how they will appear in relation to each other.


Node:Types of widget, Next:, Previous:Widgets, Up:Tk

Types of widget

In Tcl/Tk there are currently 15 types of widget. In alphabetical order they are (see also see also library('tcltk/examples/widgets.tcl')):

button
a simple press button
canvas
is a container for displaying "drawn" objects such as lines, circles, and polygons.
checkbutton
a button that hold a state of either on or off
entry
a text entry field
frame
a widget that is a container for other widgets
label
a simple label
listbox
a box containing a list of options
menu
a widget for creating menu bars
menubutton
a button which when pressed offers a selection of choices
message
a multi-line text display widget
radiobutton
a button used to form groups of mutually interacting buttons (When one button is pressed down, the others pop up.)
scale
is like a slider on a music console. It consists of a trough scale and a slider. Moving the slider to a position on the scale sets the overall value of the widget to that value.
scollbar
used to add scrollbars to windows or canvases. The scrollbar has a slider which when moved changes the value of the slider widget.
text
a sophisticated multi-line text widget that can also display other widgets such as buttons
toplevel
for creating new standalone toplevel windows. (These windows are containers for other widgets. They are not terminal windows.)

images/tcltkwidgets.png

Meet The Main Tk Widgets


Node:Widgets hierarchies, Next:, Previous:Types of widget, Up:Tk

Widgets hierarchies

Before going further it is necessary to understand how instances of widgets are named. Widgets are arranged in a hierarchy. The names of widget instances are formed from dot separated words. The root window is simply . on its own. So for, example, a button widget that is displayed in the root window might have the name .b1. A button that is displayed inside a frame that is displayed inside the root window may have the name .frame1.b1. The frame would have the name .frame1.

Following this notation, it is clear that widgets are both formed in hierarchies, with the dot notation giving the path to a widget, and in groups, all widgets with the same leading path are notionaly in the same group.

(It is a similar to the way file systems are organized. A file has a path which shows where to find it in the hierarchical file system. But also files with the same leading path are in the same directory/folder and so are notionaly grouped together.)

An instance of a widget is created through the a Tcl command for that widget. The widget command my have optional arguments set for specifying various attributes of the widget that it will have when it is created. The result of a successful widget command is the name of the new widget.

For example, a command to create a button widget named .mybutton that displays the text "I am a button" would look like this:

button .mybutton -text "I am a button"

and this will return the name .mybutton.

A widget will only be created if all the windows/widgets in the leading path of the new widget also exist, and also that the name of the new widget does not already exist.

For example, the following

button .mybutton -text "I am a button"
button .mybutton -text "and so am I"

will fail at the second command because there is also a widget named .mybutton from the first command.

The following will also fail

button .frame.mybutton -text "I am a button"

if there is no existing widget with the name .frame to be the parent of .mybutton.

All this begs the question: why are widgets named and arranged in a hierarchy? Isn't a GUI just a bunch of widgets displayed in a window?

This is not generally how GUIs are arranged. For example, they often have a menubar over the top of each window. The menubar contains pulldown menus. The pulldown menus may have cascading menu items that may cascade down several levels. Under the menu bar is the main part of the window that may also be split into several "frames". A left hand frame my have a set of buttons in it, for example. And so on. From this you can see that the widgets in GUIs are naturally arranged in a hierarchy. To achieve this in Tcl/Tk instances of widgets are placed in a hierarchy which is reflected in their names.

Now we will go through each of the widget commands in turn. Each widget command has many options most of which will not be described here. Just enough will be touched on for the reader to understand the basic operation of each widget. For a complete description of each widget and its many options refer to the Tk manual.


Node:Widget creation, Next:, Previous:Widgets hierarchies, Up:Tk

Widget creation

As has already been said, a widget is a window object that has state and behavior. In terms of Tcl/Tk a widget is created by calling a widget creation command. There is a specific widget creation for each type of widget.

The widget creation command is supplied with arguments. The first argument is always the name you want to give to the resulting widget; the other arguments set the initial state of the widget.

The immediate result of calling a widget creation command is that it returns the name of the new widget. A side effect is that the instance of the widget is created and its name is defined as in the Tcl interpreter as a procedure through which the widget state can be accessed and manipulated.

This needs an example. We will use the widget creator command button to make a button widget:

button .fred -text 'Fred' -background red

which creates an instance of a button widget named .fred that will display the text Fred on the button and will have a red background color. Evaluating this command returns the string .fred, the name of the newly created widget.

As a side effect, a Tcl procedure named .fred is created. A call to a widget instance has the following form:

widgetName method methodArgs

where widgetName is the name of the widget to be manipulated, method is the action to be performed on the widget, and methodArgs are the arguments passed to the method that is performed on the widget.

The two standard methods for widgets are configure and cget. configure - is used to change the state of a widget; for example:

.fred configure -background green -text 'Sid'

will change the background color of the widget .fred to green and the text displayed to Sid.

cget is used to get part of the state of a widget; for example:

.fred cget -text

will return Sid if the text on the button .fred is Sid.

In addition to these general methods, there are special methods for each widget type. For example, with button widgets you have the flash and invoke methods.

For example,

.fred invoke

can be called somewhere in the Tcl code to invoke button .fred as though it had been clicked on.

.fred flash

can be called somewhere in the Tcl code to cause the button to flash.

We will come across some of these special method when we discuss the widgets in detail. For a comprehensive list of widget methods, refer to entry for the appropriate widget creation command in the Tcl/Tk manual.

We now discuss the widget creation command for each widget type.


Node:label, Next:, Previous:Widget creation, Up:Widget creation

label

A label is a simple widget for displaying a single line of text. An example of creating an instance of a label is

label .l -text "Hello world!"

which simply creates the label named .l with the text Hello world! displayed in it. Most widgets that display text can have a variable associated with them through the option -textvariable. When the value of the variable is changed the text changes in the associated label. For example,

label .l -text "Hello world!" -textvariable mytext

creates a text label called .l displaying the initial text Hello world! and associated text variable mytext; mytext will start with the value Hello world!. However, if the following script is executed:

set mytext "Goodbye moon!"

then magically the text in the label will change to Goodbye moon!.


Node:message, Next:, Previous:label, Up:Widget creation

message

A message widget is similar to a label widget but for multi-line text. As its name suggests it is mostly used for creating popup message information boxes.

An example of a message widget is

message .msg -text "Your data is incorrect.\n\n \
              Please correct it and try again." \
    -justify center

which will create a message widget displaying the text shown, center justified. The width of the message box can be given through the -width switch. Any lines that exceed the width of the box are wrapped at word boundaries.


Node:button, Next:, Previous:message, Up:Widget creation

button

Calling the button command creates an instance of a button widget. An example is:

button .mybutton -text "hello" -command {puts "howdie!"}

which creates a button with name .mybutton that will display the text "hello" and will execute the Tcl script puts "howdie!" (that is print howdie! to the terminal) when clicked on.


Node:checkbutton, Next:, Previous:button, Up:Widget creation

checkbutton

Checkbuttons are buttons that have a fixed state that is either on or off. Clicking on the button toggles the state. To store the state, a checkbutton is associated with a variable. When the state of the checkbutton changes, so does that of the variable. An example is:

checkbutton .on_or_off -text "I like ice cream" -variable ice

which will create a checkbutton with name .on_or_off displaying the text I like ice cream and associated with the variable ice. If the checkbutton is checked then ice will have the value 1; if not checked then it will have the value 0. The state of the checkbutton can also be changed by changing the state of the variable. For example, executing

set ice 0

will set the state of .on_or_off to not checked.


Node:radiobutton, Next:, Previous:checkbutton, Up:Widget creation

radiobutton

Radiobuttons are buttons that are grouped together to select one value among many. Each button has a value, but only one in the button group is active at any one time. In Tcl/Tk this is achieved by creating a series of radiobutton that share an associated variable. Each button has a value. When a radiobutton is clicked on, the variable has that value and all the other buttons in the group are put into the off state. Similarly, setting the value of the variable is reflected in the state of the button group. An example is:

radiobutton .first -value one -text one -variable count
radiobutton .second -value two -text two -variable count
radiobutton .third -value three -text three -variable count

which creates three radiobuttons that are linked through the variable count. If button .second is active, for example, then the other two buttons are in the inactive state and count has the value two. The following code sets the button group to make the button .third active and the rest inactive regardless of the current state:

set count three

If the value of count does not match any of the values of the radiobuttons then they will all be off. For example executing the script

set count four

will turn all the radiobuttons off.


Node:entry, Next:, Previous:radiobutton, Up:Widget creation

entry

An entry widget allows input of a one line string. An example of a an entry widget:

label .l -text "Enter your name"
entry .e -width 40 -textvariable your_name

would display a label widget named .l showing the string Enter your name and an entry widget named .e of width 40 characters. The value of variable your_name will reflect the string in the entry widget: as the entry widget string is updated, so is the value of the variable. Similarly, changing the value of your_name in a Tcl script will change the string displayed in the entry field.


Node:scale, Next:, Previous:entry, Up:Widget creation

scale

A scale widget is for displaying an adjustable slider. As the slider is moved its value, which is displayed next to the slider, changes. To specify a scale, it must have -from and -to attributes which is the range of the scale. It can have a -command option which is set to a script to evaluate when the value of the slider changes.

An example of a scale widget is:

scale .s -from 0 -to 100

which creates a scale widget with name .s that will slide over a range of integers from 0 to 100.

There are several other options that scales can have. For example it is possible to display tick marks along the length of the scale through the -tickinterval attribute, and it is possible to specify both vertically and horizontally displayed scales through the -orient attribute.


Node:listbox, Next:, Previous:scale, Up:Widget creation

listbox

A listbox is a widget that displays a list of single line strings. One or more of the strings may be selected through using the mouse. Initializing and manipulating the contents of a listbox is done through invoking methods on the instance of the listbox. As examples, the insert method is used to insert a string into a listbox, delete to delete one, and get to retrieve a particular entry. Also the currently selected list items can be retrieved through the selection command.

Here is an example of a listbox that is filled with entries of the form entry N:

listbox .l
for { set i 0 } { $i<10 } { incr i } {
    .l insert end "entry $i"
}

A listbox may be given a height and/or width attribute, in which case it is likely that not all of the strings in the list are visible at the same time. There are a number of methods for affecting the display of such a listbox.

The see method causes the listbox display to change so that a particular list element is in view. For example,

.l see 5

will make sure that the sixth list item is visible. (List elements are counted from element 0.)


Node:scrollbar, Next:, Previous:listbox, Up:Widget creation

scrollbar

A scrollbar widget is intended to be used with any widget that is likely to be able to display only part of its contents at one time. Examples are listboxes, canvases, text widgets, and frames, amongst others.

A scrollbar widget is displayed as a movable slider between two arrows. Clicking on either arrow moves the slider in the direction of the arrow. The slider can be moved by dragging it with the cursor.

The scollbar and the widget it scrolls are connected through Tcl script calls. A scrollable widgets will have a scrollcommand attribute that is set to a Tcl script to call when the widget changes its view. When the view changes the command is called, and the command is usually set to change the state of its associated scrollbar.

Similarly, the scrollbar will have a command attribute that is another script that is called when an action is performed on the scrollbar, like moving the slider or clicking on one of its arrows. That action will be to update the display of the associated scrollable widget (which redraws itself and then invokes its scrollcommand which causes the scrollbar to be redrawn).

How this is all done is best shown through an example:

listbox .l -yscrollcommand ".s set" -height 10
scrollbar .s -command ".l yview"
for { set i 0 } { $i < 50 } { incr i } {
    .l insert end "entry $i"
}

creates a listbox named .l and a scrollbar named .s. Fifty strings of the form entry N are inserted into the listbox. The clever part is the way the scrollbar and listbox are linked. The listbox has its -yscrollcommand attribute set to the script ".s set". What happens is that if the view of .l is changed, then this script is called with 4 arguments attached: the number of entries in the listbox, the size of the listbox window, the index of the first entry currently visible, and the index of the last entry currently visible. This is exactly enough information for the scrollbar to work out how to redisplay itself. For example, changing the display of the above listbox could result in the following -yscrollcommand script being called:

.s set 50 10 5 15

which says that the listbox contains 50 elements, it can display 10 at one time, the first element displayed has index 5 and the last one on display has index 15. This call invokes the set method of the scrollbar widget .s, which causes it to redraw itself appropriately.

If, instead, the user interacts with the scrollbar, then the scrollbar will invoke its -command script, which in this example is ".l yview". Before invoking the script, the scrollbar widget calculates which element should the first displayed in its associated widget and appends its index to the call. For example, if element with index 20 should be the first to be displayed, then the following call will be made:

.l yview 20

which invokes the yview method of the listbox .l. This causes .l to be updated (which then causes its -yscrollcommand to be called which updates the scrollbar).


Node:frame, Next:, Previous:scrollbar, Up:Widget creation

frame

A frame widget does not do anything by itself except reserve an area of the display. Although this does not seem to have much purpose, it is a very important widget. It is a container widget; that is, it is used to group together collections of other widgets into logical groups. For example, a row of buttons may be grouped into a frame, then as the frame is manipulated so will the widgets displayed inside it. A frame widget can also be used to create large areas of color inside a another container widget (such as another frame widget or a toplevel widget).

An example of the use of a frame widget as a container:

canvas .c -background red
frame .f
button .b1 -text button1
button .b2 -text button2
button .b3 -text button3
button .b4 -text button4
button .b5 -text button5
pack .b1 .b2 .b3 .b4 .b5 -in .f -side left
pack .c -side top -fill both -expand 1
pack .f -side bottom

which specifies that there are two main widgets a canvas named .c and a frame named .f. There are also 5 buttons, .b1 through .b5. The buttons are displayed inside the frame. Then then the canvas is displayed at the top of the main window and the frame is displayed at the bottom. As the frame is displayed at the bottom, then so will the buttons because they are displayed inside the frame.

(The pack command causes the widgets to be handled for display by the packer geometry manager. The -fill and -expand 1 options to pack for .c tell the display manager that if the window is resized then the canvas is to expand to fill most of the window. You will learn about geometry managers later in the Geometry Managers section.)


Node:toplevel, Next:, Previous:frame, Up:Widget creation

toplevel

A toplevel widget is a new toplevel window. It is a container widget inside which other widgets are displayed. The root toplevel widget has path . -- i.e. dot on its own. Subsequent toplevel widgets must have a name which is lower down the path tree just like any other widget.

An example of creating a toplevel widget is:

toplevel .t

All the widgets displayed inside .t must also have .t as the root of their path. For example, to create a button widget for display inside the .t toplevel the following would work:

button .t.b -text "Inside 't'"

(Attributes, such as size and title, of toplevel widgets can be changed through the wm command, which we will not cover in this tutorial. The reader is referred to the Tk manual.)


Node:menu, Next:, Previous:toplevel, Up:Widget creation

menu

Yet another kind of container is a menu widget. It contains a list of widgets to display inside itself, as a pulldown menu. A simple entry in a menu widget is a command widget, displayed as an option in the menu widget, which if chosen executes a Tcl command. Other types of widgets allowed inside a menu widget are radiobuttons and checkboxes. A special kind of menu item is a separator that is used to group together menu items within a menu. (It should be noted that the widgets inside a menu widget are special to that menu widget and do not have an independent existence, and so do not have their own Tk name.)

A menu widget is built by first creating an instance of a menu widget (the container) and then invoking the add method to make entries into the menu. An example of a menu widget is as follows:

menu .m
.m add command -label "Open file" -command "open_file"
.m add command -label "Open directory" -command "open_directory"
.m add command -label "Save buffer" -command "save_buffer"
.m add command -label "Save buffer as..." -command "save_buffer_as"
.m add separator
.m add command -label "Make new frame" -command "new_frame"
.m add command -label "Open new display" -command "new_display"
.m add command -label "Delete frame" -command "delete_frame"

which creates a menu widget called .m which contains eight menu items, the first four of which are commands, then comes a separator widget, then the final three command entries. (Some of you will notice that this menu is a small part of the Files menu from the menubar of the Emacs text editor.)

An example of a checkbox and some radiobutton widget entries:

.m add checkbox -label "Inverse video" -variable inv_vid
.m add radiobutton -label "black" -variable color
.m add radiobutton -label "blue" -variable color
.m add radiobutton -label "red" -variable color

which gives a checkbox displaying Inverse video, keeping its state in the variable inv_vid, and three radiobuttons linked through the variable color.

Another menu item variant is the cascade variant which is used to make cascadable menus, i.e. menus that have submenus. An example of a cascade entry is the following:

.m add cascade -label "I cascade" -menu .m.c

which adds a cascade entry to the menu .m that displays the text I cascade. If the I cascade option is chosen from the .m menu then the menu .m.c will be displayed.

The cascade option is also used to make menubars at the top of an application window. A menu bar is simply a menu each element of which is a cascade entry, (for example). The menubar menu is attached to the application window through a special configuration option for toplevel widgets, the -menu option. Then a menu is defined for each of the cascade entry in the menubar menu.

There are a large number of other variants to menu widgets: menu items can display bitmaps instead of text; menus can be specified as tear-off menus; accelerator keys can be defined for menu items; and so on.


Node:menubutton, Next:, Previous:menu, Up:Widget creation

menubutton

A menubutton widget displays like a button, but when activated a menu pops up. The menu of the menubutton is defined through the menu command and is attached to the menubutton. An example of a menu button:

menubutton .mb -menu .mb.m -text "mymenu"
menu .mb.m
.mb.m add command -label hello
.mb.m add command -label goodbye

which crates a menubutton widget named .mb with attached menu .mb.m and displays the text mymenu. Menu .mb.m is defined as two command options, one labelled hello and the other labelled goodbye. When the menubutton .mb is clicked on then the menu .mb.m will popup and its options can be chosen.


Node:canvas, Next:, Previous:menubutton, Up:Widget creation

canvas

A canvas widget is a container widget that is used to manage the drawing of complex shapes; for example, squares, circles, ovals, and polygons. (It can also handle bitmaps, text and most of the Tk widgets too.) The shapes may have borders, filled in, be clicked on, moved around, and manipulated.

We will not cover the working of the canvas widget here. It is enough to know that there is a powerful widget in the Tk toolkit that can handle all manner of graphical objects. The interested reader is referred to the Tk manual.


Node:text, Previous:canvas, Up:Widget creation

text

A text widget is another powerful container widget that handles multi-line texts. The textwidget can display texts with varying font styles, sizes, and colors in the same text, and can also handle other Tk widgets embedded in the text.

The text widget is a rich and complicated widget and will not be covered here. The interested reader is referred to the Tk manual.


Node:Geometry managers, Next:, Previous:Widget creation, Up:Tk

Geometry managers

So far we have described each of the Tk widgets but have not mentioned how they are arranged to be displayed. Tk separates the creating of widgets from the way they are arranged for display. The "geometry" of the display is handled by a "geometry manager". A geometry manager is handed the set of widgets to display with instructions on their layout. The layout instructions are particular to each geometry manager.

Tk comes with three distinct geometry managers: grid, place, and pack. As might be expected the grid geometry manager is useful for creating tables of widgets, for example, a table of buttons.

The place geometry manager simply gives each widget an X and Y coordinate and places them at that coordinate in their particular parent window.

The pack geometry manager places widgets according to constraints, like "these three button widgets should be packed together from the left in their parent widget, and should resize with the parent".

(In practice the grid and pack geometry managers are the most useful because they can easily handle events such as resizing of the toplevel window, automatically adjusting the display in a sensible manner. place is not so useful for this.)

Each container widget (the master) has a geometry manager associated with it which tells the container how to display its sub-widgets (slaves) inside it. A single master has one and only one kind of geometry manager associated with it, but each master can have a different kind. For example, a frame widget can use the packer to pack other frames inside it. One of the slave frames could use the grid manager to display buttons inside it itself, while another slave frame could use the packer to pack labels inside it itself.


Node:pack, Next:, Previous:Geometry managers, Up:Geometry managers

pack

The problem is how to display widgets. For example, there is an empty frame widget inside which a bunch of other widgets will be displayed. The pack geometry manager's solution to this problem is to successively pack widgets into the empty space left in the container widget. The container widget is the master widget, and the widgets packed into it are its slaves. The slaves are packed in a sequence: the packing order.

What the packer does is to take the next slave to be packed. It allocates an area for the slave to be packed into from the remaining space in the master. Which part of the space is allocated depends on instructions to the packer. When the size of the space has been determined, this is sliced off the free space, and allocated to the widget which is displayed in it. Then the remaining space is available to subsequent slaves.

At any one time the space left for packing is a rectangle. If the widget is too small to use up a whole slice from the length or breadth of the free rectangle, still a whole slice is allocated so that the free space is always rectangular.

It can be tricky to get the packing instructions right to get the desired finished effect, but a large number of arrangements of widgets is possible using the packer.

Let us take a simple example: three buttons packed into the root window. First we create the buttons; see also library('tcltk/examples/ex3.tcl'):

button .b1 -text b1
button .b2 -text b2
button .b3 -text b3

then we can pack them thus:

pack .b1 .b2 .b3

which produces a display of the three buttons, one on top of the other, button .b1 on the top, and button .b3 on the bottom.

images/tcltkex3.png

Three Plain Buttons

If we change the size of the text in button .b2 through the command:

.b2 config -text "hello world"

then we see that the window grows to fit the middle button, but the other two buttons stay their original size.

images/tcltkex4.png

Middle Button Widens

The packer defaults to packing widgets in from the top of the master. Other directions can be specified. For example, the command:

pack .b1 .b2 .b3 -side left

will pack starting at the left hand side of the window. The result of this is that the buttons are formed in a horizontal row with the wider button, .b2, in the middle.

images/tcltkex5.png

Packing From The Left


Node:pad-ding, Next:, Previous:pack, Up:Geometry managers

pad-ding

It is possible to leave space between widgets through the padding options to the packer: -padx and -pady. What these do is to allocate space to the slave that is padded with the padding distances. An example would be:

pack .b1 .b2 .b3 -side left -padx 10

images/tcltkex6.png

External Padding

which adds 10 pixels of space to either side of the button widgets. This has the effect of leaving 10 pixels at the left side of button .b1, 20 pixels between buttons .b1 and .b2, 20 pixels between buttons .b2 and .b3, and finally 10 pixels on the right side of button .b3.

That was external padding for spacing widgets. There is also internal padding for increasing the size of widgets in the X and Y directions by a certain amount, through -ipadx and -ipady options; i.e. internal padding. For example:

pack .b1 .b2 .b3 -side left -ipadx 10 -ipady 10

images/tcltkex7.png

Internal Padding

instead of spacing out the widgets, will increase their dimensions by 10 pixels in each direction.


Node:fill-ing, Next:, Previous:pad-ding, Up:Geometry managers

fill-ing

Remember that space is allocated to a widget from the currently available space left in the master widget by cutting off a complete slice from that space. It is often the case that the slice is bigger that the widget to be displayed in it.

There are further options for allowing a widget to fill the whole slice allocated to it. This is done through the -fill option, which can have one of four values: none for no filling (default), x to fill horizontally only, y to fill vertically only, and both to fill both horizontally and vertically at the same time.

Filling is useful, for example, for creating buttons that are the same size even though they display texts of differing lengths. To take our button example again, the following code produces three buttons, one on top of each other, but of the same size:

button .b1 -text b1
button .b2 -text "hello world"
button .b3 -text b3
pack .b1 .b2 .b3 -fill x

images/tcltkex8.png

Using fill For Evenly Sized Widgets

How does this work? The width of the toplevel windows is dictated by button .b2 because it has the widest text. Because the three buttons are packed from top to bottom, then the slices of space allocated to them are cut progressively straight along the top of the remaining space. i.e. each widget gets a horizontal slice of space the same width cut from the top-level widget. Only the wide button .b2 would normally fit the whole width of its slice. But by allowing the other two widgets to fill horizontally, then they will also take up the whole width of their slices. The result: 3 buttons stacked on top of each other, each with the same width, although the texts they display are not the same length.

A further common example is adding a scrollbar to a listbox. The trick is to get the scrollbar to size itself to the listbox; see also library('tcltk/examples/ex9a.tcl'):

listbox .l
scrollbar .s
pack .l .s -side left

images/tcltkex9a.png

Scrollbar With Listbox, First Try

So far we have a listbox on the left and a tiny scrollbar on the right. To get the scrollbar to fill up the vertical space around it add the following command:

pack .s -fill y

Now the display looks like a normal listbox with a scrollbar.

images/tcltkex9b.png

Scrollbar With Listbox, Second Try

Why does this work? They are packed from the left, so first a large vertical slice of the master is given to the listbox, then a thin vertical slice is given to the scrollbar. The scrollbar has a small default width and height and so it does not fill the vertical space of its slice. But filling in the vertical direction (through the pack .s -fill y command) allows it to fill its space, and so it adjusts to the height of the listbox.


Node:expand-ing, Next:, Previous:fill-ing, Up:Geometry managers

expand-ing

The fill packing option specifies whether the widget should fill space left over in its slice of space. A further option to take into account is what happens when the space allocated to the master widget is much greater than the that used by its slaves. This is not usually a problem initially because the master container widget is sized to shrink-wrap around the space used by its slaves. If the container is subsequently resized, however, to a much larger size there is a question as to what should happen to the slave widgets. A common example of resizing a container widget is the resizing of a top-level window widget.

The default behavior of the packer is not to change the size or arrangement of the slave widgets. There is an option though through the expand option to cause the slices of space allocated to slaves to expand to fill the newly available space in the master. expand can have one of two values: 0 for no expansion, and 1 for expansion.

Take the listbox-scrollbar example; see also library('tcltk/examples/ex10.tcl'):

listbox .l
scrollbar .s
pack .l -side left
pack .s -side left -fill y

Initially this looks good, but now resize the window to a much bigger size. You will find that the listbox stays the same size and that empty space appears at the top and bottom of it, and that the scrollbar resizes in the vertical. It is now not so nice.

images/tcltkex10.png

Scrollbar And Listbox, Problems With Resizing

We can fix part of the problem by having the listbox expand to fill the extra space generated by resizing the window.

pack .l -side left -expand 1

images/tcltkex10a.png

Scrollbar And Listbox, Almost There

The problem now is that expand just expands the space allocated to the listbox, it doesn't stretch the listbox itself. To achieve that we need to apply the fill option to the listbox too.

pack .l -side left -expand 1 -fill both

images/tcltkex10b.png

Scrollbar And Listbox, Problem Solved Using fill

Now whichever way the top-level window is resized, the listbox-scrollbar combination should look good.

If more than one widget has the expansion bit set, then the space is allocated equally to those widgets. This can be used, for example, to make a row of buttons of equal size that resize to fill the widget of their container. Try the following code; see also library('tcltk/examples/ex11.tcl'):

button .b1 -text "one"
button .b2 -text "two"
button .b3 -text "three"
pack .b1 .b2 .b3 -side left -fill x -expand 1

images/tcltkex11.png

Resizing Evenly Sized Widgets

Now resize the window. You will see that the buttons resize to fill the width of the window, each taking an equal third of the width.

(NOTE: the best way to get the hang of the packer is to play with it. Often the results are not what you expect, especially when it comes to fill and expand options. When you have created a display that looks pleasing, always try resizing the window to see if it still looks pleasing, or whether some of your fill and expand options need revising.)


Node:anchors and packing order, Next:, Previous:expand-ing, Up:Geometry managers

anchors and packing order

There is an option to change how a slave is displayed if its allocated space is larger than itself. Normally it will be displayed centered. That can be changed by anchoring it with the -anchor option. The option takes a compass direction as its argument: n, s, e, w, nw, ne, sw, se, or c (for center).

For example, the previous example with the resizing buttons displays the buttons in the center of the window, the default anchoring point. If we wanted the buttons to be displayed at the top of the window then we would anchor them there thus; see also library('tcltk/examples/ex12.tcl'):

button .b1 -text "one"
button .b2 -text "two"
button .b3 -text "three"
pack .b1 .b2 .b3 -side left -fill x -expand 1 -anchor n

images/tcltkex12.png

Anchoring Widgets

Each button is anchored at the top of its slice and so in this case is displayed at the top of the window.

The packing order of widget can also be changed. For example,

pack .b3 -before .b2

will change the positions of .b2 and .b3 in our examples.

images/tcltkex13.png

Changing The Packing Order Of Widgets


Node:grid, Next:, Previous:anchors and packing order, Up:Geometry managers

grid

The grid geometry manager is useful for arranging widgets in grids or tables. A grid has a number of rows and columns and a widget can occupy one of more adjacent rows and columns.

A simple example of arranging three buttons; see also library('tcltk/examples/ex14.tcl'):

button .b1 -text b1
button .b2 -text b2
button .b3 -text b3
grid .b1 -row 0 -column 0
grid .b2 -row 1 -column 0
grid .b3 -row 0 -column 1 -rowspan 2

this will display button .b1 above button .b2. Button .b3 will be displayed in the next column and it will take up two rows.

images/tcltkex14.png

Using the grid Geometry Manager

However, .b3 will be displayed in the center of the space allocated to it. It is possible to get it to expand to fill the two rows it has using the -sticky option. The -sticky option says to which edges of its cells a widget "sticks" to, i.e. expands to reach. (This is like the fill and expand options in the pack manager.) So to get .b3 to expand to fill its space we could use the following:

grid .b3 -sticky ns

which says stick in the north and south directions (top and bottom). This results in .b3 taking up two rows and filling them.

images/tcltkex15.png

grid Geometry Manager, Cells With Sticky Edges

There are plenty of other options to the grid geometry manager. For example, it is possible to give some rows/columns more "weight" than others which gives them more space in the master. For example, if in the above example you wanted to allocate 1/3 of the width of the master to column 0 and 2/3 of the width to column 1, then the following commands would achieve that:

grid columnconfigure . 0 -weight 1
grid columnconfigure . 1 -weight 2

which says that the weight of column 0 for master . (the root window) is 1 and the weight of column 1 is 2. Since column 1 has more weight than column 0 it gets proportionately more space in the master.

It may not be apparent that this works until you resize the window. You can see even more easily how much space is allocated to each button by making expanding them to fill their space through the sticky option. The whole example looks like this; see also library('tcltk/examples/ex16.tcl'):

button .b1 -text b1
button .b2 -text b2
button .b3 -text b3
grid .b1 -row 0 -column 0 -sticky nsew
grid .b2 -row 1 -column 0 -sticky nsew
grid .b3 -row 0 -column 1 -rowspan 2 -sticky nsew
grid columnconfigure . 0 -weight 1
grid columnconfigure . 1 -weight 2

Now resize the window to various sizes and we will see that button .b3 has twice the width of buttons .b1 and .b2.

images/tcltkex16.png

Changing Row/Column Ratios

The same kind of thing can be specified for each row too via the grid rowconfigure command.

For other options and a full explanation of the grid manager see the manual.


Node:place, Previous:grid, Up:Geometry managers

place

Place simply places the slave widgets in the master at the given x and y coordinates. It displays the widgets with the given width and height. For example (see also library('tcltk/examples/ex17.tcl')):

button .b1 -text b1
button .b2 -text b2
button .b3 -text b3
place .b1 -x 0 -y 0
place .b2 -x 100 -y 100
place .b3 -x 200 -y 200

images/tcltkex17.png

Using The place Geometry Manager

will place the buttons .b1, .b2, and .b3 along a diagonal 100 pixels apart in both the x and y directions. Heights and widths can be given in absolute sizes, or relative to the size of the master in which case they are specified as a floating point proportion of the master; 0.0 being no size and 1.0 being the size of the master. x and y coordinates can also be specified in a relative way, also as a floating point number. For example, a relative y coordinate of 0.0 refers to the top edge of the master, while 1.0 refers to the bottom edge. If both relative and absolute x and y values are specified then they are summed.

Through this system the placer allows widgets to be placed on a kind of rubber sheet. If all the coordinates are specified in relative terms, then as the master is resized then so will the slaves move to their new relative positions.


Node:Event Handling, Next:, Previous:Geometry managers, Up:Tk

Event Handling

So far we have covered the widgets types, how instances of them are created, how their attributes can be set and queried, and how they can be managed for display using geometry managers. What we have not touched on is how to give each widget a behavior.

This is done through event handlers. Each widget instance can be given a window event handler for each kind of window event. A window event is something like the cursor moving into or out of the widget, a key press happening while the widget is active (in focus), or the widget being destroyed.

Event handlers are specified through the bind command:

bind widgetName eventSequence command

where widgetName is the name or class of the widget to which the event handler should be attached, eventSqueuence is a description of the event that this event handler will handle, and command is a script that is invoked when the event happens (i.e. it is the event handler).

Common event types are

Key
KeyPress
when a key was pressed
KeyRelease
when a key was released
Button
ButtonPress
when a mouse button was pressed
ButtonRelease
when a mouse button was released
Enter
when the cursor moves into a widget
Leave
when the cursor moved our of a widget
Motion
when the cursor moves within a widget

There are other event types. Please refer to the Tk documentation for a complete list.

The eventSequence part of a bind command is a list of one or more of these events, each event surrounded by angled brackets. (Mostly, an event sequence consists of handling a single event. Later we will show more complicated event sequences.)

An example is the following:

button .b -text "click me"
pack .b
bind .b <Enter> { puts "entering .b" }

makes a button .b displaying text click me and displays it in the root window using the packing geometry manager. The bind command specifies that when the cursor enters (i.e. goes onto) the widget, then the text entering .b is printed at the terminal.

We can make the button change color as the cursor enters or leaves it like this:

button .b -text "click me" -background red
pack .b
bind .b <Enter> { .b config -background blue }
bind .b <Leave> { .b config -background red }

which causes the background color of the button to change to blue when the cursor enters it and to change back to red when the cursor leaves.

An action can be appended to an event handler by prefixing the action with a + sign. An example is:

bind .b <Enter> {+puts "entering .b"}

which, when added to the example above, would not only change the color of the button to red when the cursor enters it, but would also print entering .b to the terminal.

A binding can be revoked simply by binding the empty command to it:

bind .b <Enter> {}

A list of events that are bound can be found by querying the widget thus:

bind .b

which will return a list of bound events.

To get the current command(s) bound to an event on a widget, invoke bind with the widget name and the event. An example is:

bind .b <Enter>

which will return a list of the commands bound to the event <Enter> on widget .b.

Binding can be generalized to sequences of events. For example, we can create an entry widget that prints spells rob each time the key sequence ESC r o b happens:

entry .e
pack .e
bind .e <Escape>rob {puts "spells rob"}

(A letter on its own in an event sequence stands for that key being pressed when the corresponding widget is in focus.)

Events can also be bound for entire classes of widgets. For example, if we wanted to perform the same trick for ALL entry widgets we could use the following command:

bind entry <Escape>rob {puts "spells rob"}

In fact, we can bind events over all widgets using all as the widget class specifier.

The event script can have substitutions specified in it. Certain textual substitutions are then made at the time the event is processed. For example, %x in a script gets the x coordinate of the mouse substituted for it. Similarly, %y becomes the y coordinate, %W the dot path of the window on which the event happened, %K the keysym of the button that was pressed, and so on. For a complete list, see the manual.

In this way it is possible to execute the event script in the context of the event.

A clever example of using the all widget specifier and text substitutions is given in John Ousterhout's book on Tcl/Tk (see Resources):

bind all <Enter> {puts "Entering %W at (%x, %y)"}
bind all <Leave> {puts "Leaving %W at (%x, %y)"}
bind all <Motion> {puts "Pointer at (%x, %y)"}

which implements a mouse tracker for all the widgets in a Tcl/Tk application. The widget's name and x and y coordinates are printed at the terminal when the mouse enters or leaves any widget, and also the x and y coordinates are printed when the mouse moves within a widget.


Node:Miscellaneous, Next:, Previous:Event Handling, Up:Tk

Miscellaneous

There are a couple of other Tk commands that we ought to mention: destroy and update.

The destroy command is used to destroy a widget, i.e. remove it from the Tk interpreter entirely and so from the display. Any children that the widget may have are also destroy-ed. Anything connected to the destroyed widget, such as bindings, are also cleaned up automatically.

For example, to create a window containing a button that is destroyed when the button is pressed:

button .b -text "Die!" -command { destroy . }
pack .b

creates a button .b displaying the text Die! which runs the command destroy . when it is pressed. Because the widget . is the main toplevel widget or window, running that command will kill the entire application associated with that button.

The command update is used to process any pending Tk events. An event is not just such things as moving the mouse but also updating the display for newly created and displayed widgets. This may be necessary in that usually Tk draws widgets only when it is idle. Using the update command forces Tk to stop and handle any outstanding events including updating the display to its actually current state, i.e. flushing out the pending display of any widgets. (This is analogous to the fflush command in C that flushes writes on a stream to disk. In Tk displaying of widgets is "buffered"; calling the update command flushes the buffer.)


Node:What we have left out (Tk), Next:, Previous:Miscellaneous, Up:Tk

What we have left out (Tk)

There are a number of Tk features that we have not described but we list some of them here in case the reader is interested. Refer to the Tk manual for more explanation.

photo
creating full color images through the command
wm
setting and getting window attributes
selection and focus commands

modal interaction
(not recommended)
send
sending messages between Tk applications


Node:Queens Display, Previous:What we have left out (Tk), Up:Tk

Example pure Tcl/Tk program

To show some of what can be done with Tcl/Tk, we will show an example of part of a GUI for an 8-queens program. Most people will be familiar with the 8-queens problem: how to place 8 queens on a chess board such that they do not attack each other according to the normal rules of chess.

Our example will not be a program to solve the 8-queens problem (that will come later in the tutorial) but just the Tcl/Tk part for displaying a solution. The code can be found in library('tcltk/examples/ex18.tcl').

The way an 8-queens solution is normally presented is as a list of numbers. The position of a number in the list indicates the column the queens is placed at and the number itself indicates the row. For example, the Prolog list [8, 7, 6, 5, 4, 3, 2, 1] would indicate 8 queens along the diagonal starting a column 1, row 8 and finishing at column 8 row 1.

The problem then becomes, given this list of numbers as a solution, how to display the solution using Tcl/Tk. This can be divided into two parts: how to display the initial empty chess board, and how to display a queen in one of the squares.

Here is our code for setting up the chess board:

#! /usr/bin/wish

proc setup_board { } {
    # create container for the board
    frame .queens

    # loop of rows and columns
    for {set row 1} {$row <= 8} {incr row} {
        for {set column 1} {$column <= 8} {incr column} {

            # create label with a queen displayed in it
            label .queens.$column-$row -bitmap @bitmaps/q64s.bm -relief flat

            # choose a background color depending on the position of the
            # square; make the queen invisible by setting the foreground
            # to the same color as the background
            if { [expr ($column + $row) % 2] } {
                .queens.$column-$row config -background #ffff99
                .queens.$column-$row config -foreground #ffff99
            } else {
                .queens.$column-$row config -background #66ff99
                .queens.$column-$row config -foreground #66ff99
            }

            # place the square in a chess board grid
            grid .queens.$column-$row -row $row -column $column -padx 1 -pady 1
        }
    }
    pack .queens
}

setup_board

The first thing that happens is that a frame widget is created to contain the board. Then there are two nested loops that loop over the rows and columns of the chess board. Inside the loop, the first thing that happens is that a label widget is created. It is named using the row and column variables so that it can be easily referenced later. The label will not be used to display text but to display an image, a bitmap of a queen. The label creation command therefore has the special argument -bitmap @q64s.bm which says that the label will display the bitmap loaded from the file q64s.bm.

The label with the queen displayed in it has now been created. The next thing that happens is that the background color of the label (square) is chosen. Depending on the position of the square it becomes either a "black" or a "white" square. At the same time, the foreground color is set to the background color. This is so that the queen (displayed in the foreground color) will be invisible, at least when the board is first displayed.

The final action in the loop is to place the label (square) in relation to all the other squares for display. A chess board is a simple grid of squares, and so this is most easily done through the grid geometry manager.

After the board has been setup square-by-square it still needs to be displayed which is done by pack-ing the outermost frame widget.

To create and display a chess board widget, all that is needed is to call the procedure

setup_board

which creates the chess board widget.

Once the chess board has been displayed, we need to be able to take a solution, a list of rows ordered by column, and place queens in the positions indicated.

Taking a topdown approach, our procedure for taking a solution and displaying is as follows:

proc show_solution { solution } {
    clear_board
    set column 1
    foreach row $solution {
        place_queen $column $row
        incr column
    }
}

This takes a solution in solution, clears the board of all queens, and then places each queen from the solution on the board.

Next we will handle clearing the board:

proc clear_board { } {
    for { set column 1 } {$column <= 8} {incr column} {
        reset_column $column
    }
}

proc reset_column { column } {
    for {set row 1 } { $row <= 8 } {incr row} {
        set_queens $column $row off
    }
}

proc set_queens { column row state } {
    if { $state == "on" } {
        .queens.$column-$row config -foreground black
    } else {
        .queens.$column-$row config -foreground [.queens.$column-$row cget -background]
    }
}

The procedure clear_board clears the board of queens by calling the procedure reset_column for each of the 8 columns on a board. reset_column goes through each square of a column and sets the square to off through set_queens. In turn, set_queens sets the foreground color of a square to black if the square is turned on, thus revealing the queen bitmap, or sets the foreground color of a square to its background color, thus making the queens invisible, if it is called with something other than on.

That handles clearing the board, clearing a column or turning a queen on or off on a particular square.

The final part is place_queen:

proc place_queen { column row } {
    reset_column $column
    set_queens $column $row on
}

This resets a column so that all queens on it are invisible and then sets the square with coordinates given in row and column to on.

A typical call would be:

show_solution "1 2 3 4 5 6 7 6 8"

images/tcltkex18.png

8-Queens Display In Tcl/Tk

which would display queens along a diagonal. (This is of course not a solution to the 8-queens problem. This Tcl/Tk code only displays possible queens solutions; it doesn't check if the solution is valid. Later we will combine this Tcl/Tk display code with Prolog code for generating solutions to the 8-queens problem.)


Node:The Prolog library, Next:, Previous:Tk, Up:Tcl/Tk library

The Prolog library

Now we have covered the wonders of Tcl/Tk, we come to the real meat of the tutorial: how to couple the power of Tcl/Tk with the power of SICStus Prolog.

Tcl/Tk is included in SICStus Prolog by loading a special library. The library provides a bidirectional interface between Tcl/Tk and Prolog.


Node:How it works - an overview, Next:, Previous:The Prolog library, Up:The Prolog library

How it works - an overview

Before describing the details of the Tcl/Tk library we will give an overview of how it works with the Prolog system.

The Tcl/Tk library provides a loosely coupled integration of Prolog and Tcl/Tk. By this we mean that the two systems, Prolog and Tcl/Tk, although joined through the library, are mostly separate; Prolog variables have nothing to do with Tcl variables, Prolog and Tcl program states are separate, and so on.

The Tcl/Tk library extends Prolog so that Prolog can create a number of independent Tcl interpreters with which it can interact. Basically, there is a predicate which when executed creates a Tcl interpreter and returns a handle with which Prolog can interact with the interpreter.

Prolog and a Tcl interpreter interact, and so communicate and cooperate, through two ways:

  1. One system evaluates a code fragment in the other system and retrieves the result. For example, Prolog evaluates a Tcl code fragment in an attached Tcl interpreter and gets the result of the evaluation in a Prolog variable. Similarly, a Tcl interpreter can evaluate a Prolog goal and get the result back through a Tcl variable.

    This is synchronous communication in that the caller waits until the callee has finished their evaluation and reads the result.

  2. One system passing a "message" to the other on an "event" queue.

    This is asynchronous communication in that the receiver of the message can read the message whenever it likes, and the sender can send the message without having to wait for a reply.

The Tk part of Tcl/Tk comes in because an attached Tcl interpreter may be extended with the Tk widget set and so be a Tcl/Tk interpreter. This makes it possible to add GUIs to a Prolog application: the application loads the Tcl/Tk Prolog library, creates a Tcl/Tk interpreter, and sends commands to the interpreter to create a Tk GUI. The user interacts with the GUI and therefore with the underlying Prolog system.

There are two main ways to partition the Tcl/Tk library functions: by function, i.e. the task they perform; or by package, i.e. whether they are Tcl, Tk, or Prolog functions. We will describe the library in terms of the former because it fits in with the tutorial style better, but at the end is a summary section that summarizes the library functions both ways.

Taking the functional approach, the library can be split into six function groups:

We go through each group in turn.


Node:Basic functions, Next:, Previous:How it works - an overview, Up:The Prolog library

Basic functions


Node:Loading the library, Next:, Previous:Basic functions, Up:Basic functions

Loading the library

First we need to know how to load the Tcl/Tk library into Prolog. This is done through the use_module/1 predicate thus:

| ?- use_module(library(tcltk)).


Node:Creating a Tcl interpreter, Next:, Previous:Loading the library, Up:Basic functions

Creating a Tcl interpreter

The heart of the system is the ability to create an embedded Tcl interpreter with which the Prolog system can interact. A Tcl interpreter is created within Prolog through a call to tcl_new/1:

tcl_new(-TclInterpreter)

which creates a new interpreter, initializes it, and returns a reference to it in the variable TclInterpreter. The reference can then be used in subsequent calls to manipulate the interpreter. More than one Tcl interpreter object can be active in the Prolog system at any one time.


Node:Creating a Tcl interpreter extended with Tk, Next:, Previous:Creating a Tcl interpreter, Up:Basic functions

Creating a Tcl interpreter extended with Tk

To start a Tcl interpreter extended with Tk, the tk_new/2 predicate is called from Prolog. It has the following form:

tk_new(+Options, -TclInterpreter)

which returns through the variable TclInterpreter a handle to the underlying Tcl interpreter. The usual Tcl/Tk window pops up after this call is made and it is with reference to that window that subsequent widgets are created. As with the tcl_new/1 predicate, many Tcl/Tk interpreters may be created from Prolog at the same time through calls to tk_new/2.

The Options part of the call is a list of some (or none) of the following elements:

top_level_events
This allows Tk events to be handled while Prolog is waiting for terminal input; for example, while the Prolog system is waiting for input at the Prolog prompt. Without this option, Tk events are not serviced while the Prolog system is waiting for terminal input. (For information on Tk events; see Event Handling).

NOTE: This option is not currently supported under Microsoft Windows.

name(+ApplicationName)
This gives the main window a title ApplicationName. This name is also used for communicating between Tcl/Tk applications via the Tcl send command. (send is not covered in this document. Please refer to the Tcl/Tk documentation.)
display(+Display)
(This is X windows specific.) Gives the name of the screen on which to create the main window. If this is not given, the default display is determined by the DISPLAY environment variable.

An example of using tk_new/2:

| ?- tk_new([top_level_events, name('My SICStus/Tk App')], Tcl).

which creates a Tcl/Tk interpreter, returns a handle to it in the variable Tcl and Tk events are serviced while Prolog is waiting at the Prolog prompt. The window that pops up will have the title My SICStus/Tk App.

The reference to a Tcl interpreter returned by a call to tk_new/2 is used in the same way and in the same places as a reference returned by a call to tcl_new/1. They are both references to Tcl interpreters.


Node:Removing a Tcl interpreter, Previous:Creating a Tcl interpreter extended with Tk, Up:Basic functions

Removing a Tcl interpreter

To remove a Tcl interpreter from the system, use the tcl_delete/1 predicate:

tcl_delete(+TclInterpreter)

which given a reference to a Tcl interpreter, closes down the interpreter and removes it. The reference can be for a plain Tcl interpreter or for a Tk enhanced one; tcl_delete/1 removes both kinds.


Node:Evaluation functions, Next:, Previous:Basic functions, Up:The Prolog library

Evaluation functions

There are two functions in this category: Prolog extended to be able to evaluate Tcl expressions in a Tcl interpreter; Tcl extended to be able to evaluate a Prolog expression in the Prolog system.


Node:Command Format, Next:, Previous:Evaluation functions, Up:Evaluation functions

Command format

There is a mechanism for describing Tcl commands in Prolog as Prolog terms. This is used in two ways: firstly, to be able to represent Tcl commands in Prolog so that they can be subsequently passed to Tcl for evaluation; and secondly for passing terms back from Tcl to Prolog by doing the reverse transformation.

Why not represent a Tcl command as a simple atom or string? This can indeed be done, but commands are often not static and each time they are called require slightly different parameters. This means constructing different atoms or strings for each command in Prolog, which are expensive operations. A better solution is to represent a Tcl command as a Prolog term, something that can be quickly and efficiently constructed and stored by a Prolog system. Variable parts to a Tcl command (for example command arguments) can be passed in through Prolog variables.

In the special command format, a Tcl command is specified as follows.

Command   ==> Name
                | chars(PrologString)    { a list of character codes }
                | write(Term)
                | writeq(Term)
                | write_canonical(Term)
                | format(Fmt,Args)
                | dq(Command)
                | br(Command)
                | sqb(Command)
                | min(Command)
                | dot(ListOfNames)
                | list(ListOfCommands)
                | ListOfCommands

Name      ==> Atom           { other than [] }
                | Number

ListOfCommands ==> []
                | [ Command | ListOfCommands ]

ListOfNames ==> []
                | [ Name | ListOfNames ]

where

Atom
Number
denote their printed representations
chars(PrologString)
denotes the string represented by PrologString (a list of character codes)
write(Term)
writeq(Term)
write_canonical(Term)
denotes the string that is printed by the corresponding built-in predicate. Please note: In general it is not possible to reconstruct Term from the string printed by write/1. If Term will be passed back into Prolog it therefore safest to use write_canonical(Term) (see Term I/O).
format(Fmt, Args)
denotes the string that is printed by the corresponding built-in predicate
dq(Command)
denotes the string specified by Command, enclosed in double quotes
br(Command)
denotes the string specified by Command, enclosed in curly brackets
sqb(Command)
denotes the string specified by Command, enclosed in square brackets
min(Command)
denotes the string specified by Command, immediately preceded by a hyphen
dot(ListOfName)
denotes the widget path specified by ListOfName, preceded by and separated by dots
list(ListOfCommands)
denotes the TCL list with one element for each element in ListOfCommands. This differs from just using ListOfCommands or br(ListOfCommands) when any of the elements contains spaces, braces or other characters treated specially by TCL.
ListOfCommands
denotes the string denoted by each element, separated by spaces. In many cases list(ListOfCommands) is a better choice.

Examples of command specifications and the resulting Tcl code:

[set, x, 32]
    => set x 32
[set, x, br([a, b, c])]
    => set x {a b c}
[dot([panel,value_info,name]), configure, min(text), br(write('$display'/1))]
     => .panel.value_info.name configure -text {$display/1 
['foo bar',baz]
     =>foo bar baz
list(['foo bar',bar])
     => {foo bar} baz
list(['foo { bar'',bar])
     => foo\ \{ \bar baz


Node:Evaluating Tcl expressions from Prolog, Next:, Previous:Command Format, Up:Evaluation functions

Evaluating Tcl expressions from Prolog

Prolog calls Tcl through the predicate tcl_eval/3 which has the following form:

tcl_eval(+TclInterpreter, +Command, -Result)

which causes the interpreter TclInterpreter to evaluate the Tcl command Command and return the result Result. The result is a string (a list of character codes) that is the usual return string from evaluating a Tcl command. Command is not just a simple Tcl command string (although that is a possibility) but a Tcl command represented as a Prolog term in the special Command Format (see Command Format).

Through tcl_eval/3, Prolog has a method of synchronous communication with an embedded Tcl interpreter and a way of manipulating the state of the interpreter.

An example:

?- tcl_new(Interp),
   tcl_eval(Interp, 'set x 1', _),
   tcl_eval(Interp, 'incr x', R)

which creates a Tcl interpreter the handle of which is stored in the variable Interp. Then variable x is set to the value "1" and then variable x is incremented and the result returned in R as a string. The result will be "2". By evaluating the Tcl commands in separate tcl_eval/3 calls, we show that we are manipulating the state of the Tcl interpreter and that it remembers its state between manipulations.

It is worth mentioning here also that because of the possibility of the Tcl command causing an error to occur in the Tcl interpreter, two new exceptions are added by the tcltk library:

tcl_error(Goal, Message)
tk_error(Goal, Message)

where Message is a list of character codes detailing the reason for the exception. Also two new user:portray_message/2 rules are provided so that any such uncaught exceptions are displayed at the Prolog top-level as

[TCL ERROR: Goal - Message]
[TK ERROR: Goal - Message]

respectively.

These exception conditions can be raised/caught/displayed in the usual way through the user module builtin predicates raise_exception/3, on_exception/1, and portray_message/2.

As an example, the following Prolog code will raise such an exception:

| ?- tcl_new(X), tcl_eval(X, 'wilbert', R).

which causes a tcl_error/2 exception and prints the following:

{TCL ERROR: tcl_eval/3 - invalid command name "wilbert"}

assuming that there is no command or procedure defined in Tcl called wilbert.


Node:Evaluating Prolog expressions from Tcl, Previous:Evaluating Tcl expressions from Prolog, Up:Evaluation functions

Evaluating Prolog expressions from Tcl

The Tcl interpreters created through the SICStus Prolog Tcl/Tk library have been extended to allow calls to the underlying Prolog system.

To evaluate a Prolog expression in the Prolog system from a Tcl interpreter, the new prolog Tcl command is invoked. It has the following form:

prolog PrologGoal

where PrologGoal is the printed form of a Prolog goal. This causes the goal to be executed in Prolog. It will be executed in the user module unless it is prefixed by a module name. Execution is always deterministic.

The return value of the command either of the following:

"1", if execution succeeded,

"0", if execution failed,

If succeeded (and "1" was returned) then any variable in PrologGoal that has become bound to a Prolog term will be returned to Tcl in the Tcl array named prolog_variables with the variable name as index. The term is converted to Tcl using the same conversion as used for Tcl commands (Command Format). As a special case the values of unbound variables and variables with names starting with _, are not recorded and need not conform to the special command format, this is similar to the threatment of such variables by the Prolog top-level.

An example:

test_callback(Result) :-
    tcl_new(Interp),
    tcl_eval(Interp,
        'if {[prolog "foo(X,Y,Z)"] == 1} \\
            {list $prolog_variables(X) \\
                  $prolog_variables(Y) \\
                  $prolog_variables(Z)}',
            Result),
    tcl_delete(Interp).

foo(1, bar, [a, b, c]).

When called with the query:

| ?- test_callback(Result).

will succeed, binding the variable Result to:

"1 bar {a b c}"

This is because execution of the tcl_eval/3 predicate causes the execution of the prolog command in Tcl, which executes foo(X, Y, Z) in Prolog making the following bindings: X = 1, Y = bar, Z = [a, b, c]. The bindings are returned to Tcl in the associative array prolog_variables where prolog_variables(X) is "1", prolog_variables(Y) is "bar", and prolog_variables(Z) is "a b c". Then Tcl goes on to execute the list command as

list "1" "bar" "a b c"

which returns the result

"1 bar {a b c}"

(remember: nested lists magically get represented with curly brackets) which is the string returned in the Result part of the Tcl call, and is ultimately returned in the Result variable of the top-level call to test_callback(Result).

If an error occurs during execution of the prolog Tcl command, a tcl_error/2 exception will be raised. The message part of the exception will be formed from the string Exception during Prolog execution: appended to the Prolog exception message. An example is the following:

?- tcl_new(T), tcl_eval(T, 'prolog wilbert', R).

which will print

{TCL ERROR: tcl_eval/3 - Exception during Prolog execution: wilbert  existence_error(wilbert,0,procedure,user:wilbert/0,0)}

at the Prolog top-level, assuming that the predicate wilbert/0 is not defined on the Prolog side of the system. (This is a tcl_error exception containing information about the underlying exception, an existence_error exception, which was caused by trying to execute the non-existent predicate wilbert.)


Node:Event functions, Next:, Previous:Evaluation functions, Up:The Prolog library

Event functions


Node:Evaluate a Tcl expression and get Prolog events, Next:, Previous:Event functions, Up:Event functions

Evaluate a Tcl expression and get Prolog events

Another way for Prolog to communicate with Tcl is through the predicate tcl_event/3:

tcl_event(+TclInterpreter, +Command, -Events)

This is similar to tcl_eval/3 in that the command Command is evaluated in the Tcl interpreter TclInterpreter, but the call returns a list of events in Events rather than the result of the Tcl evaluation. Command is again a Tcl command represented as a Prolog term in the special Command Format described previously (Command Format).

This begs the questions what are these events and where does the event list come from? The Tcl interpreters in the SICStus Prolog Tcl/Tk library have been extended with the notion of a Prolog event queue. (This is not available in plain standalone Tcl interpreters.) The Tcl interpreter can put events on the event queue by executing a prolog_event command. Each event is a Prolog term. So a Tcl interpreter has a method of putting Prolog terms onto a queue, which can later be picked up by Prolog as a list as the result of a call to tcl_event/3. (It may be helpful to think of this as a way of passing messages as Prolog terms from Tcl to Prolog.)

A call to tcl_event/3 blocks until there is something on the event queue.

A second way of getting Prolog events from a Prolog event queue is through the tk_next_event/[2,3] predicates. These have the form:

tk_next_event(+TclInterpreter, -Event)
tk_next_event(+ListOrBitMask, +TclInterpreter, -Event)

where TclInterpreter reference to a Tcl interpreter and Event is the Prolog term at the head of the associated Prolog event queue. (The ListOrBitMask feature will be described below in the Housekeeping section when we talk about Tcl and Tk events; see Housekeeping.).

(We will meet tk_next_event/[2,3] again later when we discuss how it can be used to service Tk events; see Servicing Tk Events).

If the interpreter has been deleted then the empty list [] is returned.


Node:prolog_event, Next:, Previous:Evaluate a Tcl expression and get Prolog events, Up:Event functions

Adding events to the Prolog event queue

The Tcl interpreters under the SICStus Prolog library are extended with a command, prolog_event, for adding events to a Prolog event queue.

The prolog_event command has the following form:

   prolog_event Terms ...

where Terms are strings that contain the printed representation of Prolog terms. These are stored in a queue and retrieved as Prolog terms by tcl_event/3 or tk_next_event/[2,3] (described above).

An example of using the prolog_event command:

test_event(Event) :-
    tcl_new(Interp),
    tcl_event(Interp, [prolog_event, dq(write(zap(42)))], Event),
    tcl_delete(Interp).

with the query:

| ?- test_event(Event).

will succeed, binding Event to the list [zap(42)].

This is because tcl_event converts its argument using the special Command Format conversion (see Command Format) which yields the Tcl command prolog_event "zap(42)". This command is evaluated in the Tcl interpreter referenced by the variable Interp. The effect of the command is to take the string given as argument to prolog_event (in this case "zap(42)") and to place it on the Tcl to Prolog event queue. The final action of a tcl_event/3 call is to pick up any strings on the Prolog queue from Tcl, add a trailing full stop and space to each string, and parse them as Prolog terms, binding Event to the list of values, which in this case is the singleton list [zap(42)]. (The queue is a list the elements of which are terms put there through calls to prolog_event).

If any of the Term-s in the list of arguments to prolog_event is not a valid representation of a Prolog term, then an exception is raised in Prolog when it is converted from the Tcl string to the Prolog term using read. To ensure that Prolog will be able to read the term correctly it is better to always use write_canonical and to ensure that Tcl is not confused by special characters in the printed representation of the prolog term it is best to wrap the list with list.

A safer variant that safely passes any term from Prolog via Tcl and back to Prolog is thus:

test_event(Term, Event) :-
    tcl_new(Interp),
    tcl_event(Interp, list([prolog_event, write_canonical(Term)]), Event),
    tcl_delete(Interp).


Node:An example, Previous:prolog_event, Up:Event functions

An example

As an example of using the prolog event system supplied by the tcltk library, we will return to our 8-queens example but now approaching from the Prolog side rather than the Tcl/Tk side:

:- use_module(library(tcltk)).

setup :-
    tk_new([name('SICStus+Tcl/Tk - Queens')], Tcl),
    tcl_eval(Tcl, 'source queens.tcl', _),
    tk_next_event(Tcl, Event),
    (   Event = next -> go(Tcl),
    ;   closedown(Tcl)
    ).

closedown(Tcl) :-
    tcl_delete(Tcl).

go(Tcl) :-
    tcl_eval(Tcl, 'clear_board', _),
    queens(8, Qs),
    show_solution(Qs, Tcl),
    tk_next_event(Tcl, Event),
    (   Event = next -> fail
    ;   closedown(Tcl)
    ).
go(Tcl) :-
    tcl_eval(Tcl, 'disable_next', _),
    tcl_eval(Tcl, 'clear_board', _),
    tk_next_event(Tcl, _Event),
    closedown(Tcl).

This is the top-level fragment of the Prolog side of the 8-queens example. It has three predicates: setup/0, closedown/1, and go/1. setup/0 simply creates the Tcl interpreter, loads the Tcl code into the interpreter using a call to tcl_eval/3 (which also initialises the display) but then calls tk_next_event/2 to wait for a message from the Tk side.

The Tk part that sends prolog_event-s to Prolog looks like this:

button .next -text next -command {prolog_event  next}
pack .next

button .stop -text stop -command {prolog_event stop}
pack .stop

that is two buttons, one that sends the atom next, the other that sends the atom stop. They are used to get the next solution and to stop the program respectively.

So if the user presses the next button in the Tk window, then the Prolog program will receive a next atom via a prolog_event/tk_next_event pair, and the program can proceed to execute go/1.

go/1 is a failure driven loop that generates 8-queens solutions and displays them. First it generates a solution in Prolog and displays it through a tcl_eval/3 call. Then it waits again for a Prolog events via tk_next_event/2. If the term received on the Prolog event queue is next, corresponding to the user pressing the "next solution" button, then fail is executed and the next solution found, thus driving the loop.

If the stop button is pressed then the program does some tidying up (clearing the display and so on) and then executes closedown/1, which deletes the Tcl interpreter and the corresponding Tk windows altoegther, and the program terminates.

This example fragment show how it is possible for a Prolog program and a Tcl/Tk program to communicate via the Prolog event queue.


Node:Servicing Tk Events, Next:, Previous:Event functions, Up:The Prolog library

Servicing Tcl and Tk events

The notion of an event in the Prolog+Tcl/Tk system is overloaded. We have already come across the following kinds of events:

It is further about to be overloaded with the notion of Tcl/Tk events. It is possible to create event handlers in Tcl/Tk for reacting to other kinds of events. We will not cover them here but describe them so that the library functions are understandable and in case the user needs these features in an advanced application.

There are the following kinds of Tcl/Tk events:

idle events
happen when the Tcl/Tk system is idle
file events
happen when input arrives on a file handle that has a file event handler attached to it
timer events
happen when a Tcl/Tk timer times out
window events
when something happens to a Tk window, such as being resized or destroyed

The problem is that in advanced Tcl/Tk applications it is possible to create event handlers for each of these kinds of event, but they are not normally serviced while in Prolog code. This can result in unresponsive behavior in the application; for example, if window events are not serviced regularly then if the user tries to resize a Tk window, it will not resize in a timely fashion.

The solution to this is to introduce a Prolog predicate that passes control to Tk for a while so that it can process its events, tk_do_one_event/[0,1]. If an application is unresponsive because it is spending a lot of time in Prolog and is not servicing Tk events often enough, then critical sections of the Prolog code can be sprinkled with calls to tk_do_one_event/[0,1] to alleviate the problem.

tk_do_one_event/[0,1] has the following forms:

tk_do_one_event
tk_do_one_event(+ListOrBitMask)

which passes control to Tk to handle a single event before passing control back to Prolog. The type of events handled is passed through the ListOrBitMask variable. As indicated, this is either a list of atoms which are event types, or a bit mask as specified in the Tcl/Tk documentation. (The bit mask should be avoided for portability between Tcl/Tk versions.)

The ListOrBitMask list can contain the following atoms:

tk_dont_wait
don't wait for new events, process only those that are ready
tk_x_events
tk_window_events
process window events
tk_file_events
process file events
tk_timer_events
process timer events
tk_idle_events
process Tk_DoWhenIdle events
tk_all_events
process any event

Calling tk_do_one_event/0 is equivalent to a call to tk_do_one_event/1 with all flags set.

A call to either of these predicates succeeds only if an event of the appropriate type happens in the Tcl/Tk interpreter. If there are no such events, then tk_do_one_event/1 will fail if the tk_dont_wait wait flag is present, as will tk_do_one_event/0 which has that flag set implicitly.

If the tk_dont_wait flag is not set, then a call to tk_do_one_event/1 will block until an appropriate Tk event happens (in which case it will succeed).

It is straight forward to define a predicate which handles all Tk events and then returns:

tk_do_all_events :-
    tk_do_one_event, !,
    tk_do_all_events.
tk_do_all_events.

The predicate tk_next_event/[2,3] is similar to tk_do_one_event/[0,1] except that it processes Tk events until at least one Prolog event happens. (We came across this predicate before when discussing Prolog event queue predicates. This shows the overloading of the notion event where we have a predicate that handles both Tcl/Tk events and Prolog queue events.)

It has the following forms:

tk_next_event(+TclInterpreter, -Event)
tk_next_event(+ListOrBitMask, +TclInterpreter, -Event)

The Prolog event is returned in the variable Event and is the first term on the Prolog event queue associated with the interpreter TclInterpreter. (Prolog events are initiated on the Tcl side through the new Tcl command prolog_event, covered earlier; see prolog_event).


Node:Passing control to Tk, Next:, Previous:Servicing Tk Events, Up:The Prolog library

Passing control to Tk

There is a predicate for passing control completely over to Tk, the tk_main_loop/0 command. This passes control to Tk until all windows in all the Tcl/Tk interpreters in the Prolog have have been destroyed:

tk_main_loop


Node:Housekeeping, Next:, Previous:Passing control to Tk, Up:The Prolog library

Housekeeping functions

Here we will described the functions that do not fit into any of the above categories and are essentially housekeeping functions.

There is a predicate that returns a reference to the main window of a Tcl/Tk interpreter:

tk_main_window(+TclInterpreter, -TkWindow)

which given a reference to a Tcl interpreter Tclnterpreter, returns a reference to its main window in TkWindow.

The window reference can then be used in tk_destroy_window/1:

tk_destroy_window(+TkWindow)

which destroys the window or widget referenced by TkWindow and all of its sub-widgets.

The predicate tk_make_window_exist/1 also takes a window reference:

tk_make_window_exist(+TkWindow)

which causes the window referenced by TkWindow in the Tcl interpreter TclInterpreter to be immediately mapped to the display. This is useful because normally Tk delays displaying new information for a long as possible (waiting until the machine is idle, for example), but using this call causes Tk to display the window immediately.

There is a predicate for determining how many main windows, and hence Tcl/Tk interpreters (excluding simple Tcl interpreters), are currently in use:

tk_num_main_windows(-NumberOfWindows)

which returns an integer in the variable NumberOfWindows.


Node:Summary, Previous:Housekeeping, Up:The Prolog library

Summary

The functions provided by the SICStus Prolog Tcl/Tk library can be grouped in two ways: by function, and by package.

By function, we can group them like this:

By package, we can group them like this:

In the next section we will discuss how to use the tcltk library to build graphical user interfaces to Prolog applications. More specifically we will discuss the ways in which cooperation between Prolog and Tcl/Tk can be arranged: how to achieve them, and their benefits.


Node:Putting it all together, Next:, Previous:The Prolog library, Up:Tcl/Tk library

Putting it all together

At this point we now know Tcl, the Tk extensions, and how they can be integrated into SICStus Prolog through the tcltk library module. The next problem is how to get all this to work together to produce a coherent application. Because Tcl can make Prolog calls and Prolog can make Tcl calls it is easy to create programming spaghetti. In this section we will discuss some general principles of organizing the Prolog and Tcl code to make writing applications easier.

The first thing to do is to review the tools that we have. We have two programming systems: Prolog and Tcl/Tk. They can interact in the following ways:

With these interaction primitives there are three basic ways in which Prolog and Tcl/Tk can be organized:

  1. Tcl the master, Prolog the slave: program control is with Tcl, which makes occasional calls to Prolog, through the prolog function.
  2. Prolog the master, Tcl the slave: program control is with Prolog which makes occasional call to Tcl through the tcl_eval function
  3. Prolog and Tcl share control: program control is shared with Tcl and Prolog interacting via the Prolog event queue, through tcl_event, tk_next_event, and prolog_event.

These are three ways of organizing cooperation between Tcl/Tk and Prolog to produce an application. In practice an application my use only one of these methods throughout, or may use a combination of them where appropriate. We describe them here so that the developer can see the different patterns of organization and can pick those relevant to their application.


Node:Tcl the master, Next:, Previous:Putting it all together, Up:Putting it all together

Tcl the master, Prolog the slave

This is the classical way that GUIs are bolted onto applications. The slave (in this case Prolog) sits mostly idle while the user interacts with the GUI, for example filling in a form. When some action happens in the GUI that requires information from the slave (a form submit, for example), the slave is called, performs a calculation, and the GUI retrieves the result and updates its display accordingly.

In our Prolog+Tcl/Tk setting this involves the following steps:

Some of The Tk widgets in the GUI will have "callbacks" to Prolog, i.e. they will call the prolog Tcl command. When the Prolog call returns, the values stored in the prolog_variables array in the Tcl interpreter can then be used by Tcl to update the display.

Here is a simple example of a callback. The Prolog part is this:

:- use_module(library(tcltk)).

hello('world').

go :-
    tk_new([], Tcl),
    tcl_eval(Tcl, 'source simple.tcl', _),
    tk_main_loop.

which just loads the tcltk library module, defines a hello/1 data clause, and go/0 which starts a new Tcl/Tk interpreter, loads the code simple.tcl into it, and passes control to Tcl/Tk.

The Tcl part, simple.tcl, is this:

label .l -textvariable tvar
button .b -text "push me" -command { call_and_display }
pack .l .b -side top

proc call_and_display { } {
    global tvar

    prolog "hello(X)"
    set tvar $prolog_variables(X)
}

which creates a label, with an associated text variable, and a button, that has a call back procedure, call_and_display, attached to it. When the button is pressed, call_and_display is executed, which simply evaluates the goal hello(X) in Prolog and the text variable of the label .l to whatever X becomes bound to, which happens to be world. In short, pressing the button causes the word world to be displayed in the label.

Having Tcl as the master and Prolog as the slave, although a simple model to understand and implement, does have disadvantages. The Tcl command prolog is deterministic, i.e. it can return only one result with no backtracking. If more than one result is needed it means either performing some kind of all-solutions search and returning a list of results for Tcl to process, or asserting a clause into the Prolog clause store reflecting the state of the computation.

Here is an example of how an all-solutions search can be done. It is a program that calculates the outcome of certain ancestor relationships; i.e. enter the name of a person, click on a button and it will tell you the mother, father, parents or ancestors of that person.

The Prolog portion looks like this (see also library('tcltk/examples/ancestors.pl')):

:- use_module(library(tcltk)).

go :- tk_new([name('ancestors')], X),
    tcl_eval(X, 'source ancestors.tcl', _),
    tk_main_loop,
    tcl_delete(X).

father(ann, fred).
father(fred, jim).
mother(ann, lynn).
mother(fred, lucy).
father(jim, sam).

parent(X, Y) :- mother(X, Y).
parent(X, Y) :- father(X, Y).

ancestor(X, Y) :- parent(X, Y).
ancestor(X, Y) :- parent(X, Z), ancestor(Z, Y).

all_ancestors(X, Z) :- findall(Y, ancestor(X, Y), Z).

all_parents(X, Z) :-   findall(Y, parent(X, Y), Z).

This program consists of three parts. The first part is defined by go/0, the now familiar way in which a Prolog program can create a Tcl/Tk interpreter, load a Tcl file into that interpreter, and pass control over to the interpreter.

The second part is a small database of mother/father relationships between certain people through the clauses mother/2 and father/2.

The third part is a set of "rules" for determining certain relationships between people: parent/2, ancestor/2, all_ancestors/2 and all_parents/2.

The Tcl part looks like this (see also library('tcltk/examples/ancestors.tcl')):

#!/usr/bin/wish

# set up the tk display

# construct text filler labels
label .search_for -text "SEARCHING FOR THE" -anchor w
label .of         -text "OF"                -anchor w
label .gives      -text "GIVES"             -anchor w

# construct frame to hold buttons
frame .button_frame

# construct radio button group
radiobutton .mother    -text mother    -variable type -value mother
radiobutton .father    -text father    -variable type -value father
radiobutton .parents   -text parents   -variable type -value parents
radiobutton .ancestors -text ancestors -variable type -value ancestors

# add behaviors to radio buttons
.mother    config -command { one_solution mother $name}
.father    config -command { one_solution father $name}
.parents   config -command { all_solutions all_parents $name}
.ancestors config -command { all_solutions all_ancestors $name}

# create entry box and result display widgets
entry .name -textvariable name
label .result -text ">>> result <<<" -relief sunken -anchor nw -justify left

# pack buttons into button frame
pack .mother .father .parents .ancestors -fill x -side left -in .button_frame

# pack everything together into the main window
pack .search_for .button_frame .of .name .gives .result -side top -fill x

# now everything is set up
# defined the callback procedures

# called for one solution results
proc one_solution { type name } {
    if [prolog "${type}('$name', R)"] {
        display_result $prolog_variables(R)
    } else {
        display_result ""
    }
}

# called for all solution results
proc all_solutions { type name } {
    prolog  "${type}('$name', R)"
    display_result $prolog_variables(R)
}

# display the result of the search in the results box
proc display_result { result } {
    if { $result != "" } {
# create a multiline result
        .result config -text $result
    } else {
        .result config -text "*** no result ***"
    }
}

images/tcltkancestors.png

Ancestors Calculator

This program is in two parts. The first part sets up the Tk display which consists of four radiobuttons to choose the kind of relationship we want to calculate, an entry box to put the name of the person we want to calculate the relationship over, and a label in which to display the result.

Each radio buttons has an associated callback. Clicking on the radio button will invoke the appropriate callback, apply the appropriate relationship to the name entered in the text entry box, and display the result in the results label.

The second part consists of the callback procedures themselves. There are actually just two of them: one for a single solution calculation, and one for an all-solutions calculation. The single solution callback is used when we want to know the mother or father as we know that a person can have only one of each. The all-solutions callback is used when we want to know the parents or ancestors as we know that these can return more than one results. (We could have used the all-solutions callback for the single solutions cases too, but we would like to illustrate the difference in the two approaches.) There is little difference between the two approaches, except that in the single solution callback, it is possible that the call to Prolog will fail, so we wrap it in an if ... else construct to catch this case. An all-solutions search, however, cannot fail, and so the if ... else is not needed.

But there are some technical problems too with this approach. During a callback Tk events are not serviced until the callback returns. For Prolog callbacks that take a very short time to complete this is not a problem, but in other cases, for example during a long search call when the callback takes a significant time to complete, this can cause problems. Imagine that, in our example, we had a vast database describing the parent relationships of millions of people. Performing an all-solutions ancestors search could take a long time. The classic problem is that the GUI no longer reacts to the user until the callback completes.

The solution to this is to sprinkle tk_do_one_event/[0,1] calls throughout the critical parts of the Prolog code, to keep various kinds of Tk events serviced.

If this method is used in its purest form, then it is recommended that after initialization and passing of control to Tcl, Prolog does not make calls to Tcl through tcl_eval/3. This is to avoid programming spaghetti. In the pure master/slave relationship it is a general principle that the master only call the slave, and not the other way around.


Node:Queens Prolog, Next:, Previous:Tcl the master, Up:Putting it all together

Prolog the master, Tk the slave

The second approach is to have Prolog be the master and Tk the slave. This is suitable when heavy processing is done in the Prolog code and Tk is used mostly to display the state of the computation in some way rather than as a traditional GUI; i.e. during computation Prolog often makes calls to Tk to show some state, but the user rarely interacts with the application.

In our Prolog+Tcl/Tk setting this involves the following steps:

Again it its purest form, Prolog makes calls to Tcl, but Tcl does not make calls to Prolog. The result of a call to Tcl is either passed back through the Result variable of a tcl_eval/3 call.

A good example of this is the Tcl/Tk display for our 8-queens problem, that we saw earlier; see Queens Display.

We will now fill out the example by presenting the Prolog master part. The Prolog program calculates a solution to the 8-queens problem and then makes calls Tcl/Tk to display the solution. In this way Tcl/Tk is the slave, just being used as a simple display.

We have already seen the Tcl/Tk part, but here is the Prolog part for generating a solution and displaying it:

:- use_module(library(tcltk)).
:- use_module(library(lists)).

go :-
    tk_new([name('SICStus+Tcl/Tk - Queens')], Tcl),
    tcl_eval(Tcl, 'source queens.tcl', _),
    tk_next_event(Tcl, Event),
    queens(8, Qs),
    reverse(L, LR),
    tcl_eval(Tcl, [show_solution, br(LR)], _),
    fail.
go.

queens(N, Qs) :-
    range(1, N, Ns),
    queens(Ns, [], Qs).

queens(UnplacedQs, SafeQs, Qs) :-
    select(Q, UnplacedQs, UnplacedQs1),
    \+ attack(Q, SafeQs),
    queens(UnplacedQs1, [Q|SafeQs], Qs).
    queens([], Qs, Qs).

attack(X, Xs) :- attack(X, 1, Xs).

attack(X, N, [Y|_Ys]) :- X is Y + N.
attack(X, N, [Y|_Ys]) :- X is Y - N.
attack(X, N, [_Y|Ys]) :-
    N1 is N + 1,
attack(X, N1, Ys).

range(M, N, [M|Ns]) :-
    M < N,
    M1 is M + 1,
    range(M1, N, Ns).
range(N, N, [N]).

:- go.

All this simply does it to create a Tcl/Tk interpreter, load the Tcl code for displaying queens into it, generate a solution to the 8-queens problem as a list of integers, and then calls show_solution/2 in the Tcl interpreter to display the solution. At the end of first clause for go/0 is a fail clause that turns go/0 into a failure driven loop. The result of this is that the program will calculate all the solutions to the 8-queens problem, displaying them rapidly one after the other, until there are none left.


Node:Prolog and Tcl interact through Prolog event queue, Next:, Previous:Queens Prolog, Up:Putting it all together

Prolog and Tcl interact through Prolog event queue

In the previous two methods, one of the language systems was the master and the other slave, the master called the slave to perform some action or calculation, the slave sits waiting until the master calls it. We have seen that this has disadvantages when Prolog is the slave in that the state of the Prolog call is lost. Each Prolog call starts from the beginning unless we save the state using message database manipulation through calls to assert and retract.

Using the Prolog event queue, however, it is possible to get a more balanced model where the two language systems cooperate without either really being the master or the slave.

One way to do this is the following:

What can processing a Prolog event mean? Well, for example, a button press from Tk could tell the Prolog program to finish or to start processing something else. The Tcl program is not making an explicit call to the Prolog system but sending a message to Prolog. The Prolog system can pick up the message and process it when it chooses, in the meantime keeping its run state and variables intact.

To illustrate this, we return to the 8-queens example. If Tcl/Tk is the master and Prolog the slave, then we have shown that using a callback to Prolog, we can imagine that we hit a button, call Prolog to get a solution and then display it. But how do we get the next solution? We could get all the solutions, and then use Tcl/Tk code to step through them, but that doesn't seem satisfactory. If we use the Prolog is the master and Tcl/Tk is the slave model then we have shown how we can use Tcl/Tk to display the solutions generate from the Prolog side: Prolog just make a call to the Tcl side when it has a solution. But in this model Tcl/Tk widgets do not interact with the Prolog side; Tcl/Tk is mearly an add-on display to Prolog.

But using the Prolog event queue we can get the best of both worlds: Prolog can generate each solution in turn as Tcl/Tk asks for it.

Here is the code on the Prolog side that does this. (We have left out parts of the code that haven't changed from our previous example, see Queens Prolog).

:- use_module(library(tcltk)).
:- use_module(library(lists)).

setup :-
    tk_new([name('SICStus+Tcl/Tk - Queens')], Tcl),
    tcl_eval(Tcl, 'source queens2.tcl', _),
    tk_next_event(Tcl, Event),
    (   Event = next -> go(Tcl)
    ;   closedown(Tcl)
    ).

closedown(Tcl) :-
    tcl_delete(Tcl).

go(Tcl) :-
    tcl_eval(Tcl, 'clear_board', _),
    queens(8, Qs),
    show_solution(Qs),
    tk_next_event(Tcl, Event),
    (   Event = next -> fail
    ;   closedown(Tcl)
    ).
go(Tcl) :-
    tcl_eval(Tcl, 'disable_next', _),
    tcl_eval(Tcl, 'clear_board', _),
    tk_next_event(Tcl, _Event),
    closedown(Tcl).

show_solution(Tcl, L) :-
    tcl(Tcl),
    reverse(L, LR),
    tcl_eval(Tcl, [show_solution, br(LR)], _),
    tk_do_all_events.

Notice here that we have used tk_next_event/2 in several places. The code is executed by calling setup/0. As usual, this loads in the Tcl part of the program, but then Prolog waits for a message from the Tcl side. This message can either be next, indicating that we want to show the next solution, or stop, indicating that we want to stop the program.

If next is received, then the program goes on to execute go/1. What this does it to first calculate a solution to the 8-queens problem, displays the solution through show_solution/2, and then waits for another message from Tcl/Tk. Again this can be either next or stop. If next, the the program goes into the failure part of a failure driven loop and generates and displays the next solution.

If at any time stop is received, the program terminates gracefully, cleaning up the Tcl interpreter.

On the Tcl/Tk side all we need are a couple of buttons: one for sending the next message, and the other for sending the stop message.

button .next -text next -command {prolog_event next}
pack .next

button .stop -text stop -command {prolog_event stop}
pack .stop

(We could get more sophisticated. We might want it so that when the button it is depressed until Prolog has finished processing the last message, when the button is allowed to pop back up. This would avoid the problem of the user pressing the button many times while the program is still processing the last request. We leave this as an exercise for the reader.)


Node:The Whole 8-queens Example, Previous:Prolog and Tcl interact through Prolog event queue, Up:Putting it all together

The Whole 8-queens Example

To finish off, we our complete 8-queens program.

Here is the Prolog part, which we have covered in previous sections. The code is in library('tcltk/examples/8-queens.pl'):

:- use_module(library(tcltk)).
:- use_module(library(lists)).

setup :-
    tk_new([name('SICStus+Tcl/Tk - Queens')], Tcl),
    tcl_eval(Tcl, 'source 8-queens.tcl', _),
    tk_next_event(Tcl, Event),
    (   Event = next -> go(Tcl)
    ;   closedown(Tcl)
    ).

closedown(Tcl) :-
    tcl_delete(Tcl).

go(Tcl) :-
    tcl_eval(Tcl, 'clear_board', _),
    queens(8, Qs),
    show_solution(Tcl,Qs),
    tk_next_event(Tcl, Event),
    (   Event = next -> fail
    ;   closedown(Tcl)
    ).
go(Tcl) :-
    tcl_eval(Tcl, 'disable_next', _),
    tcl_eval(Tcl, 'clear_board', _),
    tk_next_event(Tcl, _Event),
    closedown(Tcl).

queens(N, Qs) :-
    range(1, N, Ns),
    queens(Ns, [], Qs).

queens(UnplacedQs, SafeQs, Qs) :-
    select(Q, UnplacedQs, UnplacedQs1),
    \+ attack(Q, SafeQs),
    queens(UnplacedQs1, [Q|SafeQs], Qs).
    queens([], Qs, Qs).

attack(X, Xs) :- attack(X, 1, Xs).

attack(X, N, [Y|_Ys]) :- X is Y + N.
attack(X, N, [Y|_Ys]) :- X is Y - N.
attack(X, N, [_Y|Ys]) :-
    N1 is N + 1,
    attack(X, N1, Ys).

range(M, N, [M|Ns]) :-
    M < N,
    M1 is M + 1,
    range(M1, N, Ns).
range(N, N, [N]).

show_solution(Tcl, L) :-
    reverse(L, LR),
    tcl_eval(Tcl, [show_solution, br(LR)], _),
    tk_do_all_events.

tk_do_all_events :-
    tk_do_one_event, !,
    tk_do_all_events.
tk_do_all_events.

:- setup.

And here is the Tcl/Tk part which we have covered in bits and pieces but here is the whole thing. We have added an enhancement where when the mouse is moved over one of the queens, the squares that the queen attacks are highlighted. Move the mouse away and the board reverts to normal. This is an illustration of how the Tcl/Tk bind feature can be used. The code is in library('tcltk/examples/8-queens.tcl'):

#! /usr/bin/wish

# create an 8x8 grid of labels
proc setup_display { } {
    frame .queens -background black
    pack .queens

    for {set y 1} {$y <= 8} {incr y} {
        for {set x 1} {$x <= 8} {incr x} {

            # create a label and display a queen in it
            label .queens.$x-$y -bitmap @bitmaps/q64s.bm -relief flat

            # color alternate squares with different colors
            # to create the chessboard pattern
            if { [expr ($x + $y) % 2] } {
                .queens.$x-$y config -background #ffff99
            } else {
                .queens.$x-$y config -background #66ff99
            }

            # set foreground to the background color to
            # make queen image invisible
            .queens.$x-$y config -foreground [.queens.$x-$y cget -background]

            # bind the mouse to highlight the squares attacked by a
            # queen on this square
            bind .queens.$x-$y <Enter> "highlight_attack on $x $y"
            bind .queens.$x-$y <Leave> "highlight_attack off $x $y"

            # arrange the queens in a grid
            grid .queens.$x-$y -row $y -column $x -padx 1 -pady 1

            }
       }
}

# clear a whole column
proc reset_column { column } {
    for {set y 1 } { $y <= 8 } {incr y} {
        set_queens $column $y ""
    }
}

# place or unplace a queen
proc set_queens { x y v } {
    if { $v == "Q" } {
        .queens.$x-$y config -foreground black
    } else {
        .queens.$x-$y config -foreground [.queens.$x-$y cget -background]
    }
}

# place a queen on a column
proc place_queen { x y } {
    reset_column $x
    set_queens $x $y Q
}

# clear the whole board by clearing each column in turn
proc clear_board { } {
    for { set x 1 } {$x <= 8} {incr x} {
        reset_column $x
    }
}

# given a solution as a list of queens in column positions
# place each queen on the board
proc show_solution { solution } {
    clear_board
    set x 1
    foreach y $solution {
        place_queen $x $y
        incr x
    }
}

proc highlight_square { mode x y } {
    # check if the square we want to highlight is on the board
    if { $x < 1 || $y < 1 || $x > 8 || $y > 8 } { return };

    # if turning the square on make it red,
    # otherwise determine what color it should be and set it to that
    if { $mode == "on" } { set color red } else {
        if { [expr ($x + $y) % 2] } { set color "#ffff99" } else {
            set color "#66ff99" }
        }

        # get the current settings
        set bg [ .queens.$x-$y cget -bg ]
        set fg [ .queens.$x-$y cget -fg ]

        # if the current foreground and background are the same
        # there is no queen there
        if { $bg == $fg } {
            # no queens
            .queens.$x-$y config -bg $color -fg $color
         } else {
             .queens.$x-$y config -bg $color
    }
}

proc highlight_attack { mode x y } {
    # get current colors of square at x y
    set bg [ .queens.$x-$y cget -bg ]
    set fg [ .queens.$x-$y cget -fg ]

    # no queen there, give up
    if { $bg == $fg } { return };

    # highlight the sqaure the queen is on
    highlight_square $mode $x $y

    # highlight vertical and horizontal
    for { set i 1 } {$i <= 8} {incr i} {
        highlight_square $mode $x $i
        highlight_square $mode $i $y
    }

    # highlight diagonals
    for { set i 1} { $i <= 8} {incr i} {
        highlight_square $mode [expr $x+$i] [expr $y+$i]
        highlight_square $mode [expr $x-$i] [expr $y-$i]
        highlight_square $mode [expr $x+$i] [expr $y-$i]
        highlight_square $mode [expr $x-$i] [expr $y+$i]
    }
}

proc disable_next {} {
    .next config -state disabled
}

setup_display

# button for sending a 'next' message
button .next -text next -command {prolog_event next}
pack .next

# button for sending a 'stop' message
button .stop -text stop -command {prolog_event stop}
pack .stop

images/tcltk8queens.png

8-Queens Solution, Attacked Squares Highlighted


Node:Quick Reference, Next:, Previous:Putting it all together, Up:Tcl/Tk library

Quick Reference


Node:Command Format Summary, Next:, Previous:Quick Reference, Up:Quick Reference

Command Format Summary

Command   ==> Name
                | chars(PrologString)
                | write(Term)
                | writeq(Term)
                | write_canonical(Term)
                | format(Fmt,Args)
                | dq(Command)
                | br(Command)
                | sqb(Command)
                | min(Command)
                | dot(ListOfNames)
                | list(ListOfCommands)
                | ListOfCommands

Name      ==> Atom           { other than [] }
                | Number

ListOfCommands ==> []
                | [ Command | ListOfCommands ]

ListOfNames ==> []
                | [ Name | ListOfNames ]

where

Atom
Number
denote their printed representations
chars(PrologString)
denotes the string represented by PrologString (a list of character codes)
write(Term)
writeq(Term)
write_canonical(Term)
denotes the string that is printed by the corresponding built-in predicate
format(Fmt, Args)
denotes the string that is printed by the corresponding built-in predicate
dq(Command)
denotes the string specified by Command, enclosed in double quotes
br(Command)
denotes the string specified by Command, enclosed in curly brackets
sqb(Command)
denotes the string specified by Command, enclosed in square brackets
min(Command)
denotes the string specified by Command, immediately preceded by a hyphen
dot(ListOfName)
denotes the widget path specified by ListOfName, preceded by and separated by dots
list(ListOfCommands)
denotes the TCL list with one element for each element in ListOfCommands.
ListOfCommands
denotes the string denoted by each element, separated by spaces


Node:Predicates for Prolog to interact with Tcl interpreters, Next:, Previous:Command Format Summary, Up:Quick Reference

Predicates for Prolog to interact with Tcl interpreters


tcl_new(-TclInterpreter)
Create a Tcl interpreter and return a handle to it in the variable Interpreter.
tcl_delete(+TclInterpreter)
Given a handle to a Tcl interpreter in variable TclInterpreter, it deletes the interpreter from the system.
tcl_eval(+TclInterp, +Command, -Result)
Evaluates the Tcl command term given in Command in the Tcl interpreter handle provided in TclInterpreter. The result of the evaluation is returned as a string in Result.
tcl_event(+TclInterp, +Command, -Events)
Evaluates the Tcl command term given in Command in the Tcl interpreter handle provided in TclInterpreter. The first Prolog events arising from the evaluation is returned as a list in Events. Blocks until there is something on the event queue.


Node:Predicates for Prolog to interact with Tcl interpreters with Tk extensions, Next:, Previous:Predicates for Prolog to interact with Tcl interpreters, Up:Quick Reference

Predicates for Prolog to interact with Tcl interpreters with Tk extensions


tk_new(+Options, -Interp)
Create a Tcl interpreter with Tk extensions.

Options should be a list of options described following:

top_level_events
This allows Tk events to be handled while Prolog is waiting for terminal input; for example, while the Prolog system is waiting for input at the Prolog prompt. Without this option, Tk events are not serviced while the Prolog system is waiting for terminal input.

Note: This option is not currently supported under Microsoft Windows.

name(+ApplicationName)
This gives the main window a title ApplicationName. This name is also used for communicating between Tcl/Tk applications via the Tcl send command.
display(+Display)
(This is X windows specific.) Gives the name of the screen on which to create the main window. If this is not given, the default display is determined by the DISPLAY environment variable.

tk_do_one_event *HERE*
tk_do_one_event(+ListOrBitMask)
Passes control to Tk to handle a single event before passing control back to Prolog. The type of events handled is passed through the ListOrBitMask variable. As indicated, this is either a list of atoms which are event types, or a bit mask as specified in the Tcl/Tk documentation. (The bit mask should be avoided for portability between Tcl/Tk versions.)

The ListOrBitMask list can contain the following atoms:

tk_dont_wait
don't wait for new events, process only those that are ready
tk_x_events
tk_window_events
process window events
tk_file_events
process file events
tk_timer_events
process timer events
tk_idle_events
process Tk_DoWhenIdle events
tk_all_events
process any event

Calling tk_do_one_event/0 is equivalent to a call to tk_do_one_event/1 with all flags set. If the tk_dont_wait flag is set and there is no event to handle, the call will fail.

tk_next_event(+TclInterpreter, -Event)
tk_next_event(+ListOrBitMask, +TclInterpreter, -Event)
These predicates are similar to tk_do_one_event/[0,1] except that they processes Tk events until is at least one Prolog event happens, when they succeed binding Event to the first term on the Prolog event queue associated with the interpreter TclInterpreter.
tk_main_loop
Pass control to Tk until all windows in all Tcl/Tk interpreters are gone.
tk_main_window(+TclInterpreter, -TkWindow)
Return in TkWindow a reference to the main window of a Tcl/Tk interpreter with handle passed in TclInterpreter.
tk_destroy_window(+TkWindow)
Destroy a window or widget.
tk_make_window_exist(+TkWindow)
Force display of a window or widget.
tk_num_main_windows(-NumberOfWindows)
Return in NumberOfWindows the total number of Tk main windows existing in the system.


Node:Commands for Tcl interpreters to interact with the Prolog system, Previous:Predicates for Prolog to interact with Tcl interpreters with Tk extensions, Up:Quick Reference

Commands for Tcl interpreters to interact with the Prolog system

prolog
Evaluate a Prolog expression from Tcl.
prolog_event
Place a Prolog term on the Prolog event queue from inside Tcl.


Node:Resources, Previous:Quick Reference, Up:Tcl/Tk library

Resources

We do not know of any resources out there specifically for helping with creating Prolog applications with Tcl/Tk interfaces. Instead we list here some resources for Tcl/Tk which may help readers to build the Tcl/Tk side of the application.


Node:Web sites, Next:, Previous:Resources, Up:Resources

Web sites

Ajuba Solutions (formerly Scriptics) is the home of Tcl/Tk:

http://www.ajubasolutions.com

The Tcl Consortium is a non-profit organization formed to promote the distribution and use of Tcl/Tk. Its website is at

http://www.tclconsortium.org


Node:Books, Next:, Previous:Web sites, Up:Resources

Books

There are a surprising number of books on Tcl/Tk, extensions to Tcl/Tk, and Tk as an extension to other languages. Here we mention just a few of the well-known books that will get you started with building Tcl/Tk GUIs, which can then be interfaced to your Prolog applications.


Practical Programming in Tcl and Tk - Brent Welch. Prentice Hall,
1999. 3rd Edition ISBN: 0-13-022028-0 http://www.beedub.com/book/
Tcl and the Tk Toolkit - John Ousterhout, Addison-Wesley, 1994, ISBN 0-201-63337-X
Tcl/Tk Pocket Reference - Paul Raines, 1st Ed., Oct. 1998, ISBN 1-56592-498-3
Tcl/Tk in a Nutshell - Paul Raines & Jeff Tranter, 1st Ed., March 1999, 1-56592-433-9

Also visit the books section of the Ajuba Solutions web site:

<http://dev.scriptics.com/resource/doc/books/>

Another list of Tcl/Tk books can be found at the Tcl Consortium web site:

http://www.tclconsortium.org/resources/books.html


Node:Manual pages, Next:, Previous:Books, Up:Resources

Manual pages

Complete manual pages in various formats and for various versions of the Tcl/Tk library can be found at the Ajuba Solutions site:

<http://dev.scriptics.com/man/>


Node:Usenet news groups, Previous:Manual pages, Up:Resources

Usenet news groups

The newsgroup for everything Tcl is

<news:comp.lang.tcl>


Node:Gauge, Next:, Previous:Tcl/Tk library, Up:Top

The Gauge Profiling Tool

The Gauge library package is a graphical interface to the Sicstus built-in predicates profile_data/4 and profile_reset/1. See Profiling, for more information about execution profiling. The interface is based on Tcl/Tk (see Tcl/Tk library).

To use the Gauge package, enter the query:

| ?- use_module(library(gauge)).
view(:Spec)

Creates a graphical user interface for viewing the profile data for the predicates covered by the generalized predicate spec Spec. For example, the call view([user:_,m2:_]), will bring up the graphical user interface on the predicates contained in the modules user and m2. When the display first comes up it is blank except for the control panel. A screen shot is shown below.


images/gauge.png

Gauge graphical user interface

The menus and buttons on the control panel are used as follows:

Specification
Selects what statistics to display. One of:
Calls
The number of times a predicate/clause was called.
Execution Time
The execution time. NOTE, this is a synthetic value.
Choicepoints
Number of choicepoints created.
Shallow Failures
Number of failures in the "if" part of if-then-else statements, or in the "guard" part of guarded clauses.
Deep Failures
Number of failures that don't count as shallow.
Backtracking
Number of times a clause was backtracked into.

Resolution
Selects the level of resolution. One of:
Predicate
Compute results on a per predicate basis.
Clause
Compute results on a per clause basis, not counting disjunctions and similar control structures as full predicates.
User+System Clauses
Compute results on a per clause basis, counting disjunctions and similar control structures as full predicates.

Sort Order
Selects the sort order of the histogram. One of:
Alphabetic
Sort the bars in alphabetic order.
Descending values
Sort the bars by descending values.
Ascending values
Sort the bars by ascending values.
Top 40
Show just the 40 highest values in descending order.

Scale
Controls the scaling of the bars. One of:
Linear
Display values with a linear scale.
Logarithmic
Display values with a logarithmic scale.

Show
Controls whether to show bars with zero counts. One of:
All
Show all values in the histogram.
No zero values
Show only non-zero values.

Font
The font used in the histogram chart.
Calculate
Calculates the values according to the current settings. The values are displayed in a histogram.
Reset
The execution counters of the selected predicates and clauses are reset.
Print
A choice of printing the histogram on a Postscript printer, or to a file.
Help
Shows a help text.
Quit
Quits Gauge and closes its windows.

By clicking on the bars of the histogram, the figures are displayed in the Value Info window.


Node:Chars I/O, Next:, Previous:Gauge, Up:Top

I/O on Lists of Character Codes

This package defines I/O predicates that read from, or write to, a list of character codes (a string). There are also predicates to open a stream referring to a list of character codes. The stream may be used with general Stream I/O predicates.

Note that the predicates in this section properly handle wide characters, irrespectively of the wide character encodings selected. Note also that here, the term chars refers to a list of character codes, rather than to one-char atoms.

This library fully supports multiple SICStus run-times in a process.

To load the package, enter the query

| ?- use_module(library(charsio)).
format_to_chars(+Format, :Arguments, -Chars)
format_to_chars(+Format, :Arguments, ?S0, ?S)

Prints Arguments into a list of character codes using format/3 (see Term I/O). Chars is unified with the list, alternatively S0 and S are unified with the head and tail of the list, respectively.

write_to_chars(+Term, -Chars)
write_to_chars(+Term, ?S0, ?S)

A specialized format_to_chars/[3,4]. Writes Term into a list of character codes using write/2 (see Term I/O). Chars is unified with the list. Alternatively, S0 and S are unified with the head and tail of the list, respectively.

write_term_to_chars(+Term, -Chars, +Options)
write_term_to_chars(+Term, ?S0, ?S, +Options)

A specialized format_to_chars/[3,4]. Writes Term into a list of character codes using write_term/3 and Options (see Term I/O). Chars is unified with the list. Alternatively, S0 and S are unified with the head and tail of the list, respectively.

atom_to_chars(+Atom, -Chars)
atom_to_chars(+Atom, ?S0, ?S)

A specialized format_to_chars/[3,4]. Converts Atom to the list of characters comprising its name. Chars is unified with the list, alternatively S0 and S are unified with the head and tail of the list, respectively.

number_to_chars(+Number, -Chars)
number_to_chars(+Number, ?S0, ?S)

A specialized format_to_chars/[3,4]. Converts Number to the list of characters comprising its name. Chars is unified with the list, alternatively S0 and S are unified with the head and tail of the list, respectively.

read_from_chars(+Chars, -Term)

Reads Term from Chars using read/2. The Chars must, as usual, be terminated by a full-stop, i.e. a ., possibly followed by layout-text.

read_term_from_chars(+Chars, -Term, +Options)

Reads Term from Chars using read_from_term/3 and Options. The Chars must, as usual, be terminated by a full-stop, i.e. a ., possibly followed by layout-text.

open_chars_stream(+Chars, -Stream)

Stream is opened as an input stream to an existing list of character codes. The stream may be read with the Stream I/O predicates and must be closed using close/1. The list is copied to an internal buffer when the stream is opened and must therefore be a ground list of character codes at that point.

with_output_to_chars(:Goal, -Chars)
with_output_to_chars(:Goal, ?S0, ?S)
with_output_to_chars(:Goal, -Stream, ?S0, ?S)

Goal is called with the current_output stream set to a new stream. This stream writes to an internal buffer which is, after the successful execution of Goal, converted to a list of character codes. Chars is unified with the list, alternatively S0 and S are unified with the head and tail of the list, respectively. with_output_to_chars/4 also passes the stream in the Stream argument. It can be used only by Goal for writing.


Node:Jasper, Next:, Previous:Chars I/O, Up:Top

Jasper Java Interface

The Jasper library module is the Prolog interface to the Java VM. It corresponds to the se.sics.jasper package in Java. It is loaded by executing the query:

| ?- use_module(library(jasper)).

It is recommended that the reader first reads Mixing Java and Prolog, as that chapter contains important information on how to use Java and Prolog together.

The Jasper library fully supports multiple SICStus run-times in a process.

Jasper cannot be used when the SICStus run-time is statically linked to the executable, such as when using spld --static.

The following functionality is provided:


Node:Jasper Method Call Example, Next:, Up:Jasper

Jasper Method Call Example

We begin with a small example.

/* Simple.java */
import se.sics.jasper.*;

public class Simple {
  private String instanceDatum = "this is instance data";

  static int simpleMethod(int value) {
    return value*42;
  }

  public String getInstanceData(String arg) {
    return instanceDatum + arg;
  }
}

Compile Simple.java (UNIX):

% javac -deprecation \
  -classpath <installdir>/lib/sicstus-3.9.0/bin/jasper.jar Simple.java

On Windows this may look like (the command should go on a single line):

C:\> c:\jdk1.2.2\bin\javac -deprecation
 -classpath "D:\Program Files\SICStus Prolog\bin\jasper.jar" Simple.java

The flag -deprecation is always a good idea, it makes javac warn if your code use deprecated methods.

%%% simple.pl

:- use_module(library(jasper)).
main :-
   %% Replace '/my/java/dir' below with the path containing
   %% 'Simple.class', e.g. to look in the current directory use
   %% classpath(['.']).
   %% You can also use the CLASSPATH environment variable and call
   %% jasper_initialize(JVM)
   %% On Windows it may look like classpath(['C:/MyTest'])
   jasper_initialize([classpath(['/my/java/dir'])],JVM),

   format('Calling a static method...~n',[]),
   jasper_call(JVM,
               method('Simple','simpleMethod',[static]), % Which method
               simple_method(+integer,[-integer]), % Types of arguments
               simple_method(42,X)), % The arguments.
   format('simpleMethod(~w) = ~w~n',[42,X]),

   format('Creating an object...~n',[]),
   jasper_new_object(JVM, 'Simple', init, init, Object),

   format('Calling an instance method on ~w...~n',[Object]),
   jasper_call(JVM,
               method('Simple','getInstanceData',[instance]),
               %% first arg is the instance to call
               get_instance_data(+object('Simple'), +string,[-string]),
               get_instance_data(Object, 'foobar', X1)),
   format('getInstanceData(~w) = ~w~n',['foobar',X1]).

Then, run SICStus (if necessary with the -m flag):

% echo "[simple],main." | sicstus -m
SICStus 3.9 (x86-linux-glibc2): Fri Sep 24 17:43:20 CEST 1999
Licensed to SICS
% consulting /home1/jojo/simple.pl...
[...]
% consulted /home1/jojo/simple.pl in module user, 100 msec 26644 bytes
Calling a static method...
simpleMethod(42) = 1764
Creating an object...
Calling and instance method on $java_object(135057576)...
getInstanceData(foobar) = this is instance datafoobar

yes

This example performed three things.


Node:Jasper Library Predicates, Next:, Previous:Jasper Method Call Example, Up:Jasper

Jasper Library Predicates

jasper_initialize(-JVM)
jasper_initialize(+Options, -JVM)

Loads and initializes the Java VM. JVM is a reference to the Java VM. Options is a list of options. The options can be of the following types:


classpath(<classpath>)
If <classpath> is an atom it will be added (unmodified) to the Java VM's classpath. If <classpath> is a list, each element will be expanded using absolute_file_name/2 and concatenated using the Java VM's path-separator. Example:
classpath([library('jasper/examples'),'$HOME/joe'])
In addition to the classpaths specified here, Jasper will automatically add jasper.jar to the classpath together with the contents of the CLASSPATH environment variable.
if_exists(flag)
This flag determines what happens if a JVM has already been initialized, either through a previous call to jasper_initialize or because Prolog have been called from Java. If a JVM already exists then the other options are ignored.
ok
The default. Argument JVM is bound to the existing JVM.
fail
The call to jasper_initialize/2 fails.
error
The call to jasper_initialize/2 throws an exception (java_exception(some text)).

if_not_exists(flag)
This flag determines what happens if a JVM has not already been initialized.
ok
The default. The remaining options are used to initialize the JVM.
fail
The call to jasper_initialize/2 fails.
error
The call to jasper_initialize/2 throws an exception (java_exception(some text)).

As an example, to access the currently running JVM and to give an error if there is no running JVM use jasper_initialize([if_exists(ok),if_not_exists(error)], JVM).

Option
The option is an atom which will be passed directly to the Java VM as an option. This enables the user to send additional options to the Java VM. Example:
jasper_initialize(['-Dkenny.is.dead=42'],JVM),
In addition to the options specified by the user, Jasper adds a couple of options on its own in order for Java to find the Jasper classes and the Jasper native library.

There is currently no support for creating multiple JVMs (few JDKs, if any, supports this).

jasper_deinitialize(+JVM)

De-initialize Java. Do not call this, current versions of the JVM does not support deinitialization.

jasper_call(+JVM,+Method,+TypeInfo,+Args)

Calls a Java static or instance method.

JVM
A reference to the Java VM, as obtained by jasper_initialize/[1-2].
TypeInfo
Information about the argument types and the argument conversion that should be applied. See Conversion between Prolog Arguments and Java Types, for more information on specifying argument types.

Note that for an instance method the first argument must be an object reference (specified with +object(Class)). In this case the class is ignored but should still be an atom, e.g. ''.

Args
A term with one position for each argument to the constructor.
Method

A term of the form method(ClassName, MethodName, Flags) that identifies the method to call.


ClassName
This is the Fully Qualified Classname of the class (for example, java/lang/String) of the object or where to look for the static method. Note that you need to surround the atom with single quotes since it contains / characters. The class is ignored when calling instance methods but should still be an atom, e.g. ''.
Name
This is the name of the method, as an atom.
Flags
This is the singleton list [instance] for instance methods and [static] for static methods.

jasper_new_object(+JVM,+ClassName,+TypeInfo,+Args,-Object)

Creates a new Java object.

See jasper_call/4 above for an explanation of the arguments JVM, ClassName, TypeInfo and Args.

ClassName
An an atom containing the fully qualified classname
TypeInfo
TypeInfo has the same format as for a static void method.
Args
A term with one position for each argument to the constructor.
Object
This argument is bound to a (local) reference to the created object. See Global vs. Local References.

As an example, the following code creates a java/lang/Integer object initialized from a string of digits. It then calls the instance method doubleValue to obtain the floating point representation of the Integer.

| ?- Chars = "4711",
%% get existing JVM
jasper_initialize([if_not_exists(error)], JVM),
jasper_new_object(JVM, 'java/lang/Integer',
                  init(+chars), init(Chars), S),
jasper_call(JVM,
            method('java/lang/Integer', doubleValue, [instance]),
            to_double(+object('java/lang/Integer'), [-double]),
            to_double(S,X)).

S = '$java_object'(135875344),
X = 4711.0,  % note that this is now a floating point number
JVM = '$jvm'(1076414148),
Chars = [52,55,49,49] ?   % a.k.a. "4711"


jasper_create_global_ref(+JVM,+Ref,-GlobalRef)

Creates a global reference (GlobalRef) for a (non-null) Java object (Ref). See Global vs. Local References.

jasper_delete_global_ref(+JVM,+GlobalRef)

Destroys a global reference. See Global vs. Local References.

jasper_create_local_ref(+JVM,+Ref,-LocalRef)

Creates a local reference (LocalRef) for a (non-null) Java object (Ref). See Global vs. Local References. Rarely needed.

jasper_delete_local_ref(+JVM,+GlobalRef)

Destroys a local reference. See Global vs. Local References.

jasper_is_jvm(+JVM)

Succeeds if JVM is a reference to a Java Virtual Machine.

jasper_is_object(+Object)
jasper_is_object(+JVM,+Object)

Succeeds if Object is a reference to a Java object. The representation of Java object will change so use jasper_is_object/1 to recognize objects instead of relying on the internal representation. Currently the JVM argument is ignored. If, and when, multiple JVMs becomes a possibility jasper_is_object/2 will verify that Object is an object in a particular JVM.

jasper_is_same_object(+JVM,+Object1,+Object2)

Succeeds if Object1 and Object2 refers to the same Java object (or both are null object references). The same object may be represented by two different terms in prolog so ==/2 can not be used to reliably detect if two object references refer to the same object.

jasper_is_instance_of(+JVM,+Object,+ClassName)

Succeeds if Object is an instance of class ClassName; fails otherwise. ClassName is a fully qualified classname, see jasper_call/4.

jasper_object_class_name(+JVM,+Object,-ClassName)

Returns the fully qualified name of the class of +Object as an atom.

jasper_null(+JVM,-NullRef)

Create a null object reference.

jasper_is_null(+JVM,+Ref)

Succeeds if Ref is a null object reference, fails otherwise, e.g. if Ref is not an object reference.


Node:Conversion between Prolog Arguments and Java Types, Next:, Previous:Jasper Library Predicates, Up:Jasper

Conversion between Prolog Arguments and Java Types

The following table lists the possible values of arguments of the argument type specification to jasper_call/4 and jasper_new_object/5 (see Jasper Library Predicates). The value specifies which conversion between corresponding Prolog argument and Java type will take place.

There is currently no mechanism for specifying Java arrays in this way.

In the following the package prefix (java/lang or se/sics/jasper) has been left out for brevity.

For several of the numerical types there is the possibility that the target type cannot accurately represent the source type, e.g. when converting from a Prolog integer to a Java byte. The behavior in such cases is unspecified.

Prolog: +integer
Java: int
The argument should be a number. It is converted to a Java int.
Prolog: +byte
Java: byte
The argument should be a number. It is converted to a Java byte.
Prolog: +short
Java: short
The argument should be a number. It is converted to a Java short.
Prolog: +long
Java: long
The argument should be a number. It is converted to a Java long.

NOTE: Since Java's long type is 64 bits wide and there is no standardized support for 64 bits integers in C, the value will be truncated. So, this declaration is really only useful in order to indicate which method should be used. For example:

class Bar
{
  void foo(int x)
    { ... }

  void foo(long x)
    { ... }
}

In order to be able to indicate that the latter of the foo methods should be called, a +long declaration must be used, even if the value itself will be truncated in the call. The behavior when converting a Java long to and from a Prolog integer will probably be changed to non-truncating in a future release of SICStus

Prolog: +float
Java: float
The argument should be a number. It is converted to a Java float.
Prolog: +double
Java: double
The argument should be a number. It is converted to a Java double.
Prolog: +term
Java: SPTerm
The argument can be any term. It is passed to Java as an object of the class SPTerm.
Prolog: +object(Class)
Java: Class
The argument should be the Prolog representation of a Java object of class Class. Unless it is the first argument in a non-static method (in which case is it treated as the object on which the method should be invoked), it is passed to the Java method as an object of class Class.
Prolog: +atom [Obsolescent]
Java: SPCanonicalAtom
The argument should be an atom. The Java method will be passed an object of class SPCanonicalAtom. Often +string, see below, is more useful.
Prolog: +boolean
Java: boolean
The argument should be an atom in {true,false}. The Java method will receive a boolean.
Prolog: +chars
Java: String
The argument should be a list of character codes. The Java method will receive an object of class String.
Prolog: +string
Java: String
The argument should be an atom. The Java method will receive an object of class String.
Prolog: -atom [Obsolescent]
Java: SPTerm
The Java method will receive an object of class SPTerm which should be be set to an atom (e.g. using SPTerm.putString). The argument will be bound to the value of the atom when the method returns. Often -term, see below, is more useful.
Prolog: -chars
Java: StringBuffer
The Java method will receive an (empty) object of type StringBuffer which can be modified. The argument will be bound to a list of the character codes of the StringBuffer object.
Prolog: -string
Java: StringBuffer
The Java method will receive an object of type StringBuffer which can be modified. The argument will be bound to an atom converted from the StringBuffer object.
Prolog: -term
Java: SPTerm
The Java method will receive an object of class SPTerm which can be set to a term (e.g. using SPTerm.consFunctor). The argument will be bound to the term when the method returns.
Prolog: [-integer]
Java: int M()
The Java method should return an int. The value will be converted to a Prolog integer.
Prolog: [-byte]
Java: byte M()
The Java method should return a byte. The value will be converted to a Prolog integer.
Prolog: [-short]
Java: short M()
The Java method should return a short. The value will be converted to a Prolog integer.
Prolog: [-long]
Java: long M()
The Java method should return a long. The value will be converted and possibly truncated to a 32 bit Prolog integer. The behavior when converting a Java long to and from a Prolog integer will probably be changed to non-truncating in a future release of SICStus
Prolog: [-float]
Java: float M()
The Java method should return a float. The value will be converted to a Prolog float.
Prolog: [-double]
Java: double M()
The Java method should return a double. The value will be converted to a Prolog float.
Prolog: [-term]
Java: SPTerm M()
The Java method should return an object of class SPTerm which will be converted to a Prolog term.
Prolog: [-object(Class)]
Java: SPTerm M()
The Java method should return an object of class Class which will be converted to the internal Prolog representation of the Java object.
Prolog: [-atom] [Obsolescent]
Java: SPTerm M()
The Java method should return an object of class SPCanonicalAtom which will be converted to a Prolog atom. Often [-term], see above, is more useful.
Prolog: [-boolean]
Java: boolean M()
The Java should return a boolean. The value will be converted to a Prolog atom in {true,false}.
Prolog: [-chars]
Java: String M()
The Java method should return an object of class String which will be converted to a list of character codes.
Prolog: [-string]
Java: String M()
The Java method should return an object of class String which will be converted to an atom.


Node:Global vs. Local References, Next:, Previous:Conversion between Prolog Arguments and Java Types, Up:Jasper

Global vs. Local References

It is important to understand the rules which determines the life-span of Java object references. These are similar in spirit to the term-refs found in the C-Prolog interface, but since they are used to handle Java objects instead of Prolog terms they work a little differently.

Java object references (currently represented in Prolog as '$java_object'/1 terms) exist in two flavors: local and global. Their validity are governed by the following rules.

  1. A local reference is valid until Prolog returns to Java or the reference is deleted with jasper_delete_local_ref/2. It is only valid in the (native) thread in which is was created. As a rule of thumb a local reference can be used safely as long as it is not saved away using assert/3 or similar.

    Since local references are never reclaimed until Prolog returns to Java (which may never happen) you should typically call jasper_delete_local_ref/2 when your code is done with an object.

  2. A global reference is valid until explicitly freed. It can be used from any native thread.
  3. All objects returned by Java methods are converted to local references.
  4. Java exceptions not caught by Java are thrown as prolog exceptions consisting of a global reference to the exception object, see Handling Java Exceptions.

Local references can be converted into global references (jasper_create_global_ref/3). When the global reference is no longer needed, it should be delete using jasper_delete_global_ref/2.

For a more in-depth discussion of global and local references, consult the JNI Documentation.

Using a local (or global) reference that has been deleted (either explicitly or by returning to Java) is illegal and will generally lead to crashes. This is a limitation of the Java Native Interface used to implement the low level interface to Java.


Node:Handling Java Exceptions, Next:, Previous:Global vs. Local References, Up:Jasper

Handling Java Exceptions

If a Java method throws an exception, e.g. by using throw new Exception("...") and the exception is not caught by Java then it is passed on as a Prolog exception. The thrown term is a global reference to the Exception object. The following example code illustrates how to handle Java exceptions in Prolog:

exception_example(JVM, ...) :-
   catch(
         %% Call Java method that may raise an exception
         jasper_call(JVM, ...),
         Excp,
         (
           ( is_java_exception(JVM, Excp)
           -> print_exception_info(JVM, Excp)
           ; throw(Excp)       % pass non-Java exceptions to caller
           )
         )
        ).

is_java_exception(_JVM, Thing) :- var(Thing), !, fail.
is_java_exception(_JVM, Thing) :-
   Thing = java_exception(_),      % misc error in Java/Prolog glue
   !.
is_java_exception(JVM, Thing) :-
   jasper_is_object(JVM, Thing),
   jasper_is_instance_of(JVM, Thing, 'java/lang/Throwable').


print_exception_info(_JVM, java_exception(Message)) :- !,
   format(user_error, '~NJasper exception: ~w~n', [Message]).
print_exception_info(JVM, Excp) :-
   /*
   // Approximate Java code
   {
      String messageChars = excp.getMessage();
   }
   */
   jasper_call(JVM,
               method('java/lang/Throwable', 'getMessage', [instance]),
               get_message(+object('java/lang/Throwable'), [-chars]),
               get_message(Excp, MessageChars)),

   /*
   // Approximate Java code
   {
      StringWriter stringWriter = new StringWriter();
      PrintWriter printWriter =  new PrintWriter(stringWriter);
      excp.printStackTrace(printWriter);
      printWriter.close();
      stackTraceChars = StringWriter.toString();
   }
   */

   jasper_new_object(JVM, 'java/io/StringWriter',
                     init, init, StringWriter),
   jasper_new_object(JVM, 'java/io/PrintWriter',
                     init(+object('java/io/Writer')),
                     init(StringWriter), PrintWriter),
   jasper_call(JVM,
               method('java/lang/Throwable', 'printStackTrace', [instance]),
               print_stack_trace(+object('java/lang/Throwable'),
                                 +object('java/io/PrintWriter')),
               print_stack_trace(Excp, PrintWriter)),
   jasper_call(JVM,
               method('java/io/PrintWriter','close',[instance]),
               close(+object('java/io/PrintWriter')),
               close(PrintWriter)),
   jasper_call(JVM,
               method('java/io/StringWriter','toString',[instance]),
               to_string(+object('java/io/StringWriter'),[-chars]),
               to_string(StringWriter, StackTraceChars)),

   jasper_delete_local_ref(JVM, PrintWriter),
   jasper_delete_local_ref(JVM, StringWriter),
   %% ! exceptions are thrown as global references
   jasper_delete_global_ref(JVM, Excp),

   format(user_error, '~NJava Exception: ~s\nStackTrace: ~s~n',
          [MessageChars, StackTraceChars]).


Node:Deprecated Jasper API, Previous:Handling Java Exceptions, Up:Jasper

Deprecated Jasper API

The information in this section is only of interest to those that need to read or modify code that used library(jasper) before SICStus 3.8.5.

A different way of doing method call and creating objects was used in versions of library(jasper) earlier than SICStus 3.8.5. Use of these facilities are strongly discouraged although they are still available in the interest of backward compatibility.

The old method call predicates are jasper_call_static/6 and jasper_call_instance/6 as well as the old way of calling jasper_new_object/5.


Node:Deprecated Argument Conversions, Next:, Up:Deprecated Jasper API

Deprecated Argument Conversions

The pre SICStus 3.8.5 method call predicates in this library use a specific form of argument lists containing conversion information so the predicates know how to convert the input arguments from Prolog datatypes to Java datatypes. This is similar to the (new) mechanism described in Conversion between Prolog Arguments and Java Types. The argument lists are standard Prolog lists containing terms on the following form:

jboolean(X)
X is the atom true or false, representing a Java boolean primitive type.
jbyte(X)
X is an integer which is converted to a Java byte.
jchar(X)
X is an integer which is converted to a Java char.
jdouble(X)
X is a float which is converted to a Java double.
jfloat(X)
X is a float which is converted to a Java float.
jint(X)
X is an integer which is converted to a Java int.
jlong(X)
X is an integer which is converted to a Java long.
jshort(X)
X is an integer which is converted to a Java short.
jobject(X)
X is a reference to a Java object, as returned by jasper_new_object/5 (see Jasper Library Predicates).
jstring(X)
X is an atom which is converted to a Java String.

If the Prolog term does not fit in the corresponding Java data type (jbyte(4711), for example), the result is undefined.


Node:Deprecated Jasper Predicates, Previous:Deprecated Argument Conversions, Up:Deprecated Jasper API

Deprecated Jasper Predicates


jasper_new_object(+JVM,+Class,+TypeSig,+Args,-Object) [Obsolescent]

Creates a new Java object.

JVM
A reference to the Java VM, as obtained by jasper_initialize/[1-2].
Class
An an atom containing the fully qualified classname (i.e. package name separated with '/', followed by the class name), for example java/lang/String, se/sics/jasper/SICStus.
TypeSig
The type signature of the class constructor. A type signature is a string which uniquely defines a method within a class. For a definition of type signatures, see the JNI Documentation.
Args
A list of argument specifiers. See Deprecated Argument Conversions.
Object
A term on the form '$java_object'(X), where X is a Java object reference. This is the Prolog handle to the Java object. See Global vs. Local References.

jasper_call_static(+JVM,+Class,+MethodName,+TypeSig,+Args,-RetVal) [Obsolescent]

Calls a static Java method. For an explanation of the JVM, Class, TypeSig, and Args, see jasper_new_object/5. MethodName is the name of the static method. RetVal is the return value of the method.

jasper_call_instance(+JVM,+Object,+MethodName,+TypeSig,+Args,-RetVal) [Obsolescent]

Calls a Java method on an object. For an explanation of the JVM, Class, TypeSig, and Args, see jasper_new_object/5. Object is an object reference as obtained from jasper_new_object/5. RetVal is the return value of the method.


Node:COM Client, Next:, Previous:Jasper, Up:Top

COM Client

This library provides rudimentary access to COM automation objects. As an example it is possible to manipulate Microsoft Office applications and Internet Explorer. It is not possible, at present, to build COM objects using this library.

Feedback is very welcome. Please contact SICStus support (sicstus-support@sics.se) if you have suggestions for how this library could be improved.


Node:Preliminaries, Next:, Up:COM Client

Preliminaries

In most contexts both atoms and lists of character codes are treated as strings. With the wide character support available in SICStus 3.8 and later, is should now be possible to pass UNICODE atoms and strings successfully to the COM interface.


Node:Terminology, Next:, Previous:Preliminaries, Up:COM Client

Terminology

ProgID
A human readable name for an object class, typically as an atom, e.g. 'Excel.Application'.
CLSID (Class Identifier)
A globally unique identifier of a class, typically as an atom, e.g. '{00024500-0000-0000-C000-000000000046}'.

Where it makes sense a ProgID can be used instead of the corresponding CLSID.

IID (Interface Identifier)
A globally unique identifier of an interface. Currently only the IDispatch interface is used so you do not have to care about this.
IName (Interface Name)
The human readable name of an interface, e.g. IDispatch.

Where it makes sense an IName can be used instead of the corresponding IID.

Object
A COM-object (or rather a pointer to an interface).
ComValue
A value that can be passed from COM to SICStus. Currently numeric types, booleans (treated as 1 for true, 0 for false), strings, and COM objects.
ComInArg
A value that can be passed as an in-argument to COM, currently one of:
atom
Passed as a string (BSTR)
numeric
Passed as the corresponding number
list
A list of char codes are treated as a string.
compound
Other compound terms are presently illegal but will be used to extend the permitted types.

It is, at present, not possible to pass an object as an argument. This restriction will be lifted.

SimpleCallSpec
Denotes a single method and its arguments. As an example, to call the method named foo with the arguments 42 and the string "bar" the SimpleCallSpec would be the compound term foo(42,'bar') or, as an alternative, foo(42,"bar").

The arguments of the compound term are treated as follows:

ComInArg
See above
variable
The argument is assumed to be an out argument. The variable is bound to the resulting value when the method returns.
mutable
The argument is assumed to be an in,out argument. The value of the mutable is passed to the method and when the method returns the mutable is updated with the corresponding return value.

CallSpec
Either a SimpleCallSpec or a list of CallSpecs. If it is a list then all but the last SimpleCallSpec are assumed to denote method calls that return a COM-object. So for instance the VB statement app.workbooks.add can be expressed either as:
comclient_invoke_method_proc(App, [workbooks, add])
or as
comclient_invoke_method_fun(App, workbooks, WorkBooks),
comclient_invoke_method_proc(WorkBooks, add),
comclient_release(WorkBooks)


Node:COM Client Predicates, Next:, Previous:Terminology, Up:COM Client

COM Client Predicates


comclient_is_object(+Object)

Succeeds if Object "looks like" an object. It does not check that the object is (still) reachable from SICStus, see comclient_valid_object/1. Currently an object looks like '$comclient_object'(stuff) where stuff is some prolog term. Do not rely on this representation!

comclient_valid_object(+Object)

Succeeds if Object is an object that is still available to SICStus.

comclient_create_instance(+CLSID/ProgID, -Object)

Create an instance of the Class identified by CLSID (or ProgID).

comclient_create_instance('Excel.Application', App)
Corresponds to CoCreateInstance.
comclient_get_active_object(+CLSID/ProgID, -Object)

Retrieves a running object of the Class identified by CLSID (or ProgID).

comclient_get_active_object('Excel.Application', App)
An exception is thrown if there is no suitable running object. Corresponds to GetActiveObject.
comclient_invoke_put(+Object, +CallSpec, +ComInArg)

Set the property denoted by CallSpec to ComValue. Example: comclient_invoke_put(App, visible, 1)

comclient_invoke_method_proc(+Object, +CallSpec)

Call a method that does not return a value. See the desciption of CallSpec above for an example.

comclient_invoke_method_fun(+Object, +CallSpec, -ComValue)

Call a method that returns a value. Also use this to get the value of properties. See the desciption of CallSpec above for an example.

comclient_release(+Object)

Release the object and free the datastructures used by SICStus to keep track of this object. After releasing an object the term denoting the object can no longer be used to access the object (any attempt to do so will raise an exception). Please note: The same COM-object can be represented by different prolog terms. A COM object is not released from SICStus until all such representations have been released, either explicitly by calling comclient_release/1 or by calling comclient_garbage_collect.

You cannot use Obj1 == Obj2 to determine if two COM-objects are in fact identical. Instead use comclient_equal/2.

comclient_equal(+Object1, +Object2)

Succeeds if Object1 and Object2 are the same object. (It succeeds if their IUnknown interfaces are identical)

comclient_garbage_collect

Release Objects that are no longer reachable from SICStus. To achieve this the predicate comclient_garbage_collect/0 performs an atom garbage collection, i.e. garbage_collect_atoms/0, so it should be used sparingly.

comclient_is_exception(+ExceptionTerm)

Succeeds if ExceptionTerm is an exception raised by the comclient module.

catch(<some code>,
      Exception,
      ( comclient_is_exception(E) ->
         handle_com_related_errors(E)
      ; otherwise -> % Pass other exceptions upwards
         throw(E)
      ))

comclient_exception_code(+ExceptionTerm, -ErrorCode)
comclient_exception_culprit(+ExceptionTerm, -Culprit)
comclient_exception_description(+ExceptionTerm, -Description)

Access the various parts of a comclient exception. The ErrorCode is the HRESULT causing the exception. Culprit is a term corresponding to the call that gave an exception. Description, if available, is either a term 'EXCEPINFO'(...) corresponding to an EXCEPINFO structure or 'ARGERR'(MethodName, ArgNumber).

The EXCEPINFO has six arguments corresponding to, and in the same order as, the arguments of the EXCEPINFO struct.

comclient_clsid_from_progid(+ProgID, -CLSID).

Obtain the CLSID corresponding to a particular ProgID. Uses the Win32 routine CLSIDFromProgID. You rarely need this since you can use the ProgID directly in most cases.

comclient_progid_from_clsid(+CLSID, -ProgID).

Obtain the ProgID corresponding to a particular CLSID. Uses the Win32 routine ProgIDFromCLSID. Rarely needed. The ProgID returned will typically have the version suffix appended.

Example, to determine what version of Excel.Application is installed:

| ?- comclient_clsid_from_progid('Excel.Application, CLSID),
     comclient_progid_from_clsid(CLSID, ProgID).
CLSID = '{00024500-0000-0000-C000-000000000046}',
ProgID = 'Excel.Application.8' ?

comclient_iid_from_name(+IName, -IID)

Look in the registry for the IID corresponding to a particular Interface. Currently of little use.

| ?- comclient_iid_from_name('IDispatch', IID).
IID = '{00020400-0000-0000-C000-000000000046}' ?

comclient_name_from_iid(+IID, -IName)

Look in the registry for the name corresponding to a particular IID. Currently of little use.


Node:COM Client Examples, Previous:COM Client Predicates, Up:COM Client

Examples

The following example launches Microsoft Excel, adds a new worksheet, fill in some fields and finally clears the worksheet and quits Excel

:- use_module(comclient).
:- use_module(library(lists)).

test :-
   test('Excel.Application').

test(ProgID) :-
   comclient_create_instance(ProgID, App),
   %% Visuall Basic: app.visible = 1
   comclient_invoke_put(App, visible, 1),
   %% VB: app.workbooks.add
   comclient_invoke_method_proc(App, [workbooks, add]),
   %% VB: with app.activesheet
   comclient_invoke_method_fun(App, activesheet, ActiveSheet),

   Rows = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],
   Cols = Rows,
   %% VB: .cells i,j . value = i+j/100
   (
     member(I, Rows),
     member(J, Cols),
     ValIJ is I+J/100,

     comclient_invoke_put(ActiveSheet, [cells(I,J),value], ValIJ),
     fail
   ; true
   ),
   (
     member(I, Rows),
     member(J, Cols),
     %% retrieve cell values
     comclient_invoke_method_fun(ActiveSheet, [cells(I,J), value],
     format(user_error, '~nCell(~w,~w) = ~w', [I,J,CellValue]),
     fail
   ; true
   ),

   Range = 'A1:O15',
   format(user_error, '~Npress return to clear range (~w)', [Range]),
   flush_output(user_error),
   get0(_),

   %% VB: .range A1:O15 .Clear
   comclient_invoke_method_proc(ActiveSheet, [range(Range),clear]),

   %% Avoid Excel query "do you want to save..."
   %%  VB: app.activeworkbook.saved = 1
   comclient_invoke_put(App, [activeworkbook,saved], 1),

   format(user_error, '~Npress return to quit \'~w\'', [ProgID]),
   flush_output(user_error),
   get0(_),

   %% VB: app.quit
   comclient_invoke_method_proc(App, quit),

   comclient_release(ActiveSheet),
   comclient_release(App).


Node:Visual Basic, Next:, Previous:COM Client, Up:Top

The Visual Basic Interface

SICStus Prolog provides an interface that lets you load and call SICStus Prolog programs from Visual Basic.


Node:An overview, Next:, Up:Visual Basic

An overview

SICStus Prolog provides an easy-to-use one-directional Visual Basic interface that lets you load and call SICStus Prolog programs from Visual Basic but not the other way around. The idea is that Visual Basic is used for creating the user interface while the Prolog program works as a knowledge server in the background.

The control structure of this interface is rather similar to that of the foreign language interface. However, in contrary to that interface, there is currently no way of handling pointers to Prolog terms or queries. The queries to be passed to Prolog have to be given as strings on the Visual Basic side and the terms output by Prolog are received as strings or integers in Visual Basic variables.

The interface provides functions for :


Node:How to call Prolog from Visual Basic, Next:, Previous:An overview, Up:Visual Basic

How to call Prolog from Visual Basic


Node:Opening and closing a query, Next:, Previous:How to call Prolog from Visual Basic, Up:How to call Prolog from Visual Basic

Opening and closing a query

Prolog queries are represented in Visual Basic in textual form, i.e. as a string containing the query, but not followed by a full stop.

For example, the following Visual Basic code fragments create valid Prolog queries:

   'Q1 is a query finding the first "good" element of the list [1,2,3]
   Q1 = "member(X,[1,2,3]), good(X)"

   'create a Q2 query finding the first "good" element of the list
   '[1,2,...,N]:
   Q2 = "member(X,["
   For i = 1 To N-1
      Q2 = Q2 & i & ","
   Next
   Q2 = Q2 & N & "]), good(X)"

Before executing a query, it has to be explicitly opened, via the PrologOpenQuery function, which will return a query identifier that can be used for successive retrieval of solutions.

The PrologCloseQuery procedure will close the query represented by a query identifier. The use of an invalid query identifier will result in undefined behavior.

Example:

   Dim qid As Long

   Q1 = "member(X,[1,2,3]), good(X)"
   qid = PrologOpenQuery(Q1)

      ... <execution of the query> ...

   PrologCloseQuery(qid)


Node:Finding the solutions of a query, Next:, Previous:Opening and closing a query, Up:How to call Prolog from Visual Basic

Finding the solutions of a query

Prolog queries can be executed with the help of the PrologNextSolution function: this retrieves a solution to the open query represented by the query identifier given as the parameter. Returns 1 on success, 0 on failure, -1 on error.


Node:Retrieving variable values, Next:, Previous:Finding the solutions of a query, Up:How to call Prolog from Visual Basic

Retrieving variable values

After the successful return of PrologNextSolution, the values assigned to the variables of the query can be retrieved by specific functions of the interface. There are separate functions for retrieving the variable values in string, quoted string and integer formats.

The PrologGetLong function retrieves the integer value of a given variable within a query and assigns it to a variable. That is, the value of the given variable is converted to an integer. Returns 1 on success.

Example: The following code fragment assigns the value 2 to the variable v:

Dim qid As Long

Q = "member(X,[1,2,3]), X > 1"

qid = PrologOpenQuery(Q)
Call PrologNextSolution(qid)
Call PrologGetLong(qid,"X",v)

The PrologGetString function retrieves the value of a given variable in a query as a string. That is, the value of the variable is written out using the write/2 Prolog predicate, and the resulting output is stored in a Visual Basic variable. Retuns 1 on success.

Example: let us suppose we have the following clause in a Prolog program:

capital_of('Sweden'-'Stockholm').

The code fragment below assigns the string "Sweden-Stockholm" to the variable capital:

Dim qid As Long

Q = "capital_of(Expr)"

qid = PrologOpenQuery(Q)
If PrologNextSolution(qid) = 1 Then
  Call PrologGetString(qid,"Expr",capital)
End if
Call PrologCloseQuery(qid)

The PrologGetStringQuoted function is the same as PrologGetString, but the conversion uses the writeq/2 Prolog predicate. Returns 1 on success.

Example: if the function PrologGetStringQuoted is used in the code above instead of the PrologGetString function, then the value assigned to the variable capital is "'Sweden'-'Stockholm'".

The only way of transferring information from Prolog to Visual Basic is by the above three PrologGet... functions. This means that, although arbitrary terms can be passed to Visual Basic, there is no support for the transfer of composite data such as lists or structures. We will show examples of how to overcome this limitation later in the manual (see Examples).


Node:Evaluating a query with side effects, Next:, Previous:Retrieving variable values, Up:How to call Prolog from Visual Basic

Evaluating a query with side effects

If you are only interested in the side effects of a predicate you can execute it with the PrologQueryCutFail function call, which will find the first solution of the Prolog goal provided, cut away the rest of the solutions, and finally fail. This will reclaim the storage used by the call.

Example: this is how a Prolog file can be loaded into the Visual Basic program:

   ret = PrologQueryCutFail("load_files(myfile)")

This code will return 1 if myfile was loaded successfully, and -1 otherwise (this may indicate, for example, the existence_error exception if the file does not exist).


Node:Handling exceptions in Visual Basic, Previous:Evaluating a query with side effects, Up:How to call Prolog from Visual Basic

Handling exceptions in Visual Basic

If an exception has been raised during Prolog execution, the functions PrologQueryCutFail or PrologNextSolution return -1. To access the exception term, the procedure PrologGetException can be used. This procedure will deposit the exception term in string format into an output parameter, as if written via the writeq/2 predicate.

Example: when the following code fragment is executed, the message box will display the domain_error(_1268 is 1+a,2,expression,a) error string.

   Dim exc As String

   qid = PrologOpenQuery("X is 1+a")
   If PrologNextSolution(qid) < 0 Then
      PrologGetException(exc)
      Msg exc,48,"Error"
   End if


Node:How to use the interface, Next:, Previous:How to call Prolog from Visual Basic, Up:Visual Basic

How to use the interface

In this section we describe how to create a Visual Basic program which is to execute Prolog queries.


Node:Setting up the interface, Next:, Up:How to use the interface

Setting up the interface

See Visual Basic notes, for information about installing the Visual basic interface.


Node:Initializing the Prolog engine, Next:, Previous:Setting up the interface, Up:How to use the interface

Initializing the Prolog engine

The Visual Basic interface must be explicitly initialized: you must call PrologInit() before calling any other interface function. The PrologInit function loads and initializes the interface. It returns 1 if the initialization was successful, and -1 otherwise.


Node:Loading the Prolog code, Previous:Initializing the Prolog engine, Up:How to use the interface

Loading the Prolog code

Prolog code (source or object code) can be loaded by submitting normal Prolog load predicates as queries. Note that SICStus uses slashes '/' in file names where Windows uses backslash '\'.

Example:

PrologQueryCutFail("load_files('d:/xxx/myfile')")

To facilitate the location of Prolog files, two clauses of user:file_search_path/2 are predefined:

app
identifies the directory path of the Visual Basic project or the applications executable.

That is, you can load the file myfile located in the same directory as the project/executable, issuing the query
PrologQueryCutFail("load_files(app(myfile))").

vbsp
identifies the directory path of the vbsp.dll file.

That is, you can use the query PrologQueryCutFail("load_files(vbsp(myfile))") to load the file myfile if it is located in the same directory as vbsp.dll.


Node:Examples, Next:, Previous:How to use the interface, Up:Visual Basic

Examples


Node:Example 1 - Calculator, Next:, Up:Examples

The code for the following examples are available in the directory library\vbsp\examples in the SICStus installation directory.

Example 1 - Calculator

This example contains a simple program that allows you to enter an arithmetic expression (conforming to Prolog syntax) as a string and displays the value of the given expression, as shown in the following figure: images/vbspcalcspec.png

The calculation itself will be done in Prolog.

We now we will go through the steps of developing this program.

Step 1: Start a new project called calculator

Step 2: Add the vbsp.bas file to the project

Step 3: Create a form window called calculator

Edit the calculator form window, adding two textboxes txtExpr and txtValue, and two command buttons, cmdCalc and cmdQuit: images/vbspcalcform1.png

Save the form window to the calculator.frm file. Then the project will contain the following two files: images/vbspproject.png

Step 4: Write the Prolog code

Write the Prolog code in the file calc.pl, evaluating the given expression with the is/2 predicate, and providing a minimal level of exception handling:

prolog_calculate(Expr, Value) :-
   on_exception(Exc, Value is Expr, handler(Exc,Value)).

handler(domain_error(_,_,_,_),'Incorrect expression').
handler(Exc,Exc).

Note that this example focuses on a minimal implementation of the problem, more elaborate exception handling will be illustrated in the Train example (see Example 2 - Train).

Compile this file, and deposit the file calc in the directory where the calculator.vbp project is contained.

Step 5: Write the Visual Basic code with the Prolog calls

Now you have to write the Visual Basic code in which SICStus Prolog will be called at two points:


Node:Example 2 - Train, Next:, Previous:Example 1 - Calculator, Up:Examples

Example 2 - Train

This example provides a Visual Basic user interface to the Prolog program finding train routes between two points.

The Visual Basic program train contains the following form window: images/vbsptrainform.png

Clicking the cmdRun command button will display all the available routes between Stockholm and Orebro. These are calculated as solutions of the Prolog query places('Stockholm','Orebro',Way). For each solution, the value assigned to the variable Way is retrieved into the Visual Basic variable result and is inserted as a new item into the listConnection listbox.

The Visual Basic program consists of four parts:

Private Sub cmdRun_Click()
    Dim qid As Long
    Dim result As String
    Dim s As String
    Dim rc As Integer

    qid = -1 ' make it safe to PrologCloseQuery(qid) in Err:

    'load the train.pl Prolog file
    rc = PrologQueryCutFail("ensure_loaded(app(train))")
    If rc < 1 Then
        Msg = "ensure_loaded(train)"
        GoTo Err
    End If
    'open the query
    qid = PrologOpenQuery("places('Stockholm','Orebro',Way)")
    If qid = -1 Then
        rc = 0
        Msg = "Open places/3"
        GoTo Err
    End If
    'generate solutions
    Do
        rc = PrologNextSolution(qid)
        If rc = 0 Then Exit Do ' failed
        If rc < 0 Then
            Msg = "places/3"
            GoTo Err
        End If
        If PrologGetString(qid, "Way", result) < 1 Then
            rc = 0
            Msg = "PrologGetString Way"
            GoTo Err
        End If
        listConnections.AddItem result
    Loop While True
    'after all solutions are found, the query is closed
    Call PrologCloseQuery(qid)
    Exit Sub

Note that each part does elaborate error checking and passes control to the error display instructions shown below:

Err:
    Call PrologCloseQuery(qid) ' Always close opened queries

    'error message is prepared, adding either the - failed - or
    'the - raised exception - suffix to the Msg string specific
    'to the function called
    If rc = 0 Then
         Msg = Msg + " failed"
    Else
        Call PrologGetException(s)
        Msg = Msg + " raised exception: " + s
    End If
    MsgBox Msg, 48, "Error"
End Sub

The Prolog predicate places is defined in the train.pl file, as shown earlier (see Train)


Node:Example 3 - Queens, Previous:Example 2 - Train, Up:Examples

Example 3 - Queens

This example gives a Visual Basic user interface to an N-queens program. The purpose of this example is to show how to handle Prolog lists through the Visual Basic interface. The full source of the example is found in the distribution. [here]

The user interface shown in this example will allow the user to specify the number of queens, and, with the help of the Next Solution command button all the solutions of the N-Queens problem will be enumerated. A given solution will be represented in a simple graphical way as a PictureBox, using the basic Circle and Line methods. images/vbspqueens.png

The problem itself will be solved in Prolog, using a queens(+N,?PositionList) Prolog predicate, stored in the file queens.

We now present two solutions, using different techniques for retrieving Prolog lists.

Example 3a - N-Queens, generating a variable list into the Prolog call

The first implementation of the N-Queens problem is based on the technique of generating a given length list of Prolog variables into the Prolog query.

For example, if the N-Queens problem is to be solved for N = 4, i.e. with the query "queens(4,L)", then the problem of retrieving a list from Visual Basic will arise. However, if the query is presented as "queens(4,[X1,X2,X3,X4])", then instead of retrieving the list it is enough to access the X1,X2,X3,X4 values. Since the number of queens is not fixed in the program, this query has to be generated, and the retrieval of the Xi values must be done in a cycle.

This approach can always be applied when the format of the solution is known at the time of calling the query.

We now go over the complete code of the program.

Global declarations used in the program (General/declarations):

Dim nQueens As Long       'number of queens
Dim nSol As Long          'index of solution
Dim nActqid As Long       'actual query identifier
Dim nQueryOpen As Boolean 'there is an open query

The initialization of the program will be done when the form window is loaded:

Private Sub Form_Load()
    nQueens = 0
    nSol = 1
    nQueryOpen = False

    'initialize Prolog
    If PrologInit() <> 1 Then GoTo Err
    'Load queens.pl
    If PrologQueryCutFail("load_files(app(queens))") <> 1 Then GoTo Err
    Exit Sub

Err:
    MsgBox "Prolog initialization failed", 48, "Error"
    Unload Me
End Sub

When the number of queens changes (i.e. the value of the text box textSpecNo changes), a new query has to be opened, after the previous query, if there has been any, is closed.

Private Sub textSpecNo_Change()
    nQueens = Val(textSpecNo)
    nSol = 1

    If nQueryOpen Then PrologCloseQuery (nActqid)

    'create Prolog query in form: queens(4,[X1,X2,X3,X4])

    Q = "queens(" & Str(nQueens) & ", ["
    For i = 1 To nQueens - 1 Step 1
        Q = Q & "X" & i & ","
    Next
    Q = Q & "X" & nQueens & "])"

    nActqid = PrologOpenQuery(Q)
    nQueryOpen = True
End Sub

The Next command button executes and shows the next solution of the current query:

Private Sub cmdNext_Click()
    Dim nPos As Long
    Dim aPos(100) As Long

    If Not nQueryOpen Then
        MsgBox "Specify number of queens first!", 48, ""
        Exit Sub
    End If
    If PrologNextSolution(nActqid) < 1 Then
        MsgBox "No more solutions!", 48, ""
    Else
        For i = 1 To nQueens Step 1
           If PrologGetLong(nActqid, "X" & i, nPos) = 1 Then
               aPos(i - 1) = nPos
           End If
        Next i

        'display nth solution
        txtSolNo = "Solution number: " & Str(nSol)
        Call draw_grid(nQueens)

        nLine = 1
        For Each xElem In aPos
            Call draw_circle(nLine, xElem, nQueens)
            nLine = nLine + 1
        Next

        nSol = nSol + 1

    End If

End Sub

Drawing itself is performed by the draw_grid and draw_circle procedures.

Example 3b - N-Queens, converting the resulting Prolog list to an atom

The second variant of the N-Queens program uses the technique of converting the resulting Prolog list into a string via the PrologGetString function, and decomposing it into an array in Visual Basic. Here we show only those parts of the program which have changed with respect to the first version.

In the textSpecNo_Change routine the queens/2 predicate is called with a single variable in its second argument:

Q = "queens(" & Str(nQueens) & ",Queens)"
nActqid = PrologOpenQuery(Q)

In the cmdNext_Click routine the solution list is retrieved into a single string which is then split up along the commas, and deposited into the aPos array by the convert_prolog_list routine. (aPos is now an array of strings, rather than integers.)

Finally, we include the code of the routine for splitting up a Prolog list:

Private Sub convert_prolog_list(ByVal inList As String,
                                ByRef inArray() As String)
    'drop brackets
    xList = Mid(inList, 2, Len(inList) - 2)

    i = 0

    startPos = 1
    xList = Mid(xList, startPos)

    Do While xList <> ""
        endPos = InStr(xList, ",")
        If endPos = 0 Then
            xElem = xList
            inArray(i) = xElem
            Exit Do
        End If
        xElem = Mid(xList, 1, endPos - 1)
        inArray(i) = xElem
        i = i + 1
        xList = Mid(xList, endPos + 1)
        startPos = endPos + 1
    Loop
End Sub


Node:Summary of the interface functions, Previous:Examples, Up:Visual Basic

Summary of the interface functions

In this section you will find a summary of the functions and procedures of the Visual Basic interface:

Function PrologOpenQuery (ByVal Goal As String) As Long
This function will return a query identifier that can be used for successive retrieval of solutions. Returns -1 on error, e.g. a syntax error in the query.
Sub PrologCloseQuery (ByVal qid As Long)
This procedure will close the query represented by a query identifier qid. Important: if qid is not the innermost query (i.e. the one opened last), then all more recently opened queries are closed as well.
Function PrologNextSolution(ByVal qid As Long) As Integer
This function retrieves a solution to the open query represented by the query identifier qid. Returns 1 on success, 0 on failure, -1 on error. In case of an erroneous execution, the Prolog exception raised can be retrieved with the PrologGetException procedure. Important: Several queries may be open at the same time, however, if qid is not the innermost query, then all more recently opened queries are implicitly closed.
Function PrologGetLong(ByVal qid As Long, ByVal VarName As String, Value As Long) As Integer
Retrieves into Value the integer value bound to the variable VarName of the query identified by qid, as an integer. That is, the value of the given variable is converted to an integer. Returns 1 on success, i.e. if the given goal assigned an integer value to the variable; otherwise, it returns 0. If an error occurred it returns -1, e.g. if an invalid qid was used.
Function PrologGetString(ByVal qid As Long, Val VarName As String, Value As String) As Integer
Retrieves into Value the string value bound to a variable VarName of the query, as a string. That is, the value assigned to the given variable is written out into an internal stream by the write/2 Prolog predicate, and the characters output to this stream will be transferred to Visual Basic as a string. Retuns 1 on success, i.e. if the given goal assigned a value to the variable; otherwise, it returns 0. If an error occurred it returns -1, e.g. if an invalid qid was used.
Function PrologGetStringQuoted(ByVal qid As Long, ByVal VarName As String, Value As String) As Integer
Same as PrologGetString, but conversion uses Prolog writeq/2. Returns 1 on success, i.e. if the given goal assigned a value to the variable; otherwise, it returns 0. If an error occurred it returns -1, e.g. if an invalid qid was used.
Function PrologQueryCutFail (ByVal Goal As String) As Integer
This function will try to evaluate the Prolog goal, provided in string format, cut away the rest of the solutions, and finally fail. This will reclaim the storage used by the call. Returns 1 on success, 0 on failure and -1 on error.
Sub PrologGetException(ByRef Exc As String)
The exception term is returned in string format into the Exc string as if written by the writeq/2 predicate. If there is no exception available then the empty string is returned.
Function PrologInit() As Long
The function loads and initiates the interface. It returns 1 if initialization was successful, and -1 otherwise.


Node:Runtime Utilities, Next:, Previous:Visual Basic, Up:Top

Glue Code Generator

This chapter used to describe Prolog utilities for generating glue code for the Foreign Language Interface (see Interface Predicates). As of SICStus 3.9, this is only supported using the splfr tool (see The Foreign Resource Linker).

You can invoke splfr (as well as spld) with the flags --verbose and --keep, in addition to the ordinary arguments. This way you can see what is going on and you can also access any generated files. The steps performed by splfr and the files generated will change between releases so you should avoid depending on it. If, for some reason, splfr is not suitable for your purposes you should contact SICStus Support.


Node:Timeout, Next:, Previous:Runtime Utilities, Up:Top

Timeout Predicate

The timeout package, which may be loaded by the query

| ?- use_module(library(timeout)).

contains the predicate:

time_out(:Goal, +Time, ?Result)

The Goal is executed as if by call/1. If computing any solution takes more than Time milliseconds, the goal will fail and Result is unified with the atom time_out. If the goal succeeds within the specified time Result is unified with the atom success. Time must be a number between (not including) 0 and 2147483647.

The time is measured in process virtual time on UNIX. On Windows the time is currently measured in real time (wall time) but you should not rely on this as it may change in the future to use process time on Windows as well.

The precision of the time out interval is usually not better than several tens of milliseconds. This is due to limitations in the timing mechanisms used to implement library(timeout).

time_out/3 is implemented by raising and handling time_out exceptions, so any exception handler in the scope of Goal must be prepared to pass on time_out exceptions. The following incorrect example shows what can happen otherwise:

| ?- time_out(on_exception(Q,(repeat,false),true), 1000, Res).
Q = time_out,
Res = success


Node:Pred Summary, Next:, Previous:Timeout, Up:Top

Summary of Built-In Predicates


! [ISO]
Commits to any choices taken in the current predicate.
(+P,+Q) [ISO]
P and Q.
(Head --> Body) [Reserved]
Not a built-in predicate; reserved syntax for grammar rules.
(+P -> +Q ; +R) [ISO]
If P then Q else R, using first solution of P only.
(+P -> +Q) [ISO]
If P then Q else false, using first solution of P only.
[]
[:File|+Files]
Updates the program with interpreted clauses from File and Files.
(:- Directive) [Reserved]
Not a built-in predicate; reserved syntax for directives.
(?- Query) [Reserved]
Not a built-in predicate; reserved syntax for queries.
(Head :- Body) [Reserved]
Not a built-in predicate; reserved syntax for clauses.
(+P;+Q) [ISO]
P or Q.
?X = ?Y [ISO]
The terms X and Y are unified.
+Term =.. ?List [ISO]
?Term =.. +List [ISO]
The functor and arguments of the term Term comprise the list List.
+X =:= +Y [ISO]
X is numerically equal to Y.
?Term1 == ?Term2 [ISO]
The terms Term1 and Term2 are strictly identical.
+X =\= +Y [ISO]
X is not numerically equal to Y.
+X =< +Y [ISO]
X is less than or equal to Y.
+X > +Y [ISO]
X is greater than Y.
+X >= +Y [ISO]
X is greater than or equal to Y.
?X \= ?Y [ISO]
X and Y are not unifiable.
?X ^ :P
Executes the procedure call P.
\+ +P [ISO]
Goal P is not provable.
?Term1 \== ?Term2 [ISO]
The terms Term1 and Term2 are not strictly identical.
+X < +Y [ISO]
X is less than Y.
?Term1 @=< ?Term2 [ISO]
The term Term1 precedes or is identical to the term Term2 in the standard order.
?Term1 @> ?Term2 [ISO]
The term Term1 follows the term Term2 in the standard order.
?Term1 @>= ?Term2 [ISO]
The term Term1 follows or is identical to the term Term2 in the standard order.
?Term1 @< ?Term2 [ISO]
The term Term1 precedes the term Term2 in the standard order.
?=(?X,?Y)
X and Y are either syntactically identical or syntactically non-unifiable.
abolish(:Preds) [ISO]
Makes the predicate(s) specified by Preds undefined.
abolish(:Atom,+Arity)
Makes the predicate specified by Atom/Arity undefined.
abort
Aborts execution of the current query (returns to C in recursive calls to Prolog from C).
absolute_file_name(+RelativeName,?AbsoluteName)
absolute_file_name(+RelativeName,?AbsoluteName,+Options)
AbsoluteName is the absolute pathname of RelativeName.
add_breakpoint(:Conditions, ?BID)
Creates a breakpoint with Conditions and with identifier BID. (Not available in runtime systems).
arg(+ArgNo,+Term,?Arg) [ISO]
The argument ArgNo of the term Term is Arg.
ask_query(+QueryClass, +Query, +Help, -Answer) [Hookable]
Prints the question Query, then reads and processes user input according to QueryClass, and returns the result of the processing, the abstract answer term Answer. The Help message is printed in case of invalid input.
assert(:Clause)
assert(:Clause,-Ref)
Asserts clause Clause with unique identifier Ref.
asserta(:Clause) [ISO]
asserta(:Clause,-Ref)
Asserts Clause as first clause with unique identifier Ref.
assertz(:Clause) [ISO]
assertz(:Clause,-Ref)
Asserts Clause as last clause with unique identifier Ref.
at_end_of_line
at_end_of_line(Stream)
The end of stream or end of line has been reached for Stream or from the current input stream.
at_end_of_stream [ISO]
at_end_of_stream(Stream) [ISO]
The end of stream has been reached for Stream or from the current input stream.
atom(?X) [ISO]
X is currently instantiated to an atom.
atom_chars(+Atom,?CharList) [ISO only]
atom_chars(?Atom,+CharList) [ISO only]
The name of the atom Atom is the list of one-char atoms CharList.
atom_chars(+Atom,?CodeList) [SICStus only]
atom_chars(?Atom,+CodeList) [SICStus only]
The name of the atom Atom is the list of character codes CodeList.
atom_codes(+Atom,?CodeList) [ISO]
atom_codes(?Atom,+CodeList) [ISO]
The name of the atom Atom is the list of character codes CodeList.
atom_concat(+Atom1,+Atom2,?Atom12) [ISO]
atom_concat(?Atom1,?Atom2,+Atom12) [ISO]
Atom Atom1 concatenated with Atom2 gives Atom12.
atom_length(+Atom,?Length) [ISO]
Length is the number of characters of the atom Atom.
atomic(?X) [ISO]
X is currently instantiated to an atom or a number.
bagof(?Template,:Goal,?Bag) [ISO]
Bag is the bag of instances of Template such that Goal is satisfied (not just provable).
block Specs [Declaration]
Not a built-in predicate; block declaration.
bb_delete(+Key,?Term)
Delete from the blackboard Term stored under Key.
bb_get(+Key,?Term)
Get from the blackboard Term stored under Key.
bb_put(+Key,+Term)
Store the term Term under Key on the blackboard.
bb_update(:Key, ?OldTerm, ?NewTerm)
Replace the term OldTerm by the term NewTerm under Key on the blackboard.
break
Invokes a recursive top-level. (Not available in runtime systems).
breakpoint_expansion(+Macro, -Body) [Hook]
user:breakpoint_expansion(+Macro, -Body)
Defines debugger condition macros.
byte_count(+Stream,?N)
N is the number of bytes read/written on stream Stream.
'C'(?S1,?Terminal,?S2)
Grammar rules. S1 is connected by the terminal Terminal to S2.
call(:Term) [ISO]
(Module::Term)
Executes the procedure call Term in Module.
call_cleanup(:Goal,:Cleanup)
Executes the procedure call Goal. When Goal succeeds deterministically, is cut, fails, or raises an exception, Cleanup is executed.
call_residue(:Goal,?Residue)
Executes the procedure call Goal. Any floundered goals and the variables they are blocked on occur as VarSet-Goal pairs in Residue.
callable(?X)
X is currently instantiated to a compound term or an atom.
character_count(+Stream,?Count)
Count characters have been read from or written to the stream Stream.
catch(:ProtectedGoal,?Pattern,:Handler) [ISO]
Executes the procedure call ProtectedGoal. If during the execution throw(Exception) or raise_exception(Exception) is called, and Exception matches Pattern, the execution of ProtectedGoal aborts, Pattern is unified with a copy of Exception and Handler is called.
char_code(+Char,?Code) [ISO]
char_code(?Char,+Code) [ISO]
Code is the character code of the one-char atom Char.
char_conversion(+InChar, +OutChar) [ISO]
The mapping of InChar to OutChar is added to the character-conversion mapping.
clause(:Head,?Body) [ISO]
clause(:Head,?Body,?Ref)
clause(?Head,?Body,+Ref)
There is an interpreted clause whose head is Head, whose body is Body, and whose unique identifier is Ref.
close(+Stream) [ISO]
close(+Stream, +Options) [ISO]
Closes stream Stream, with options Options.
compare(?Op,?Term1,?Term2)
Op is the result of comparing the terms Term1 and Term2.
compile(:Files)
Compiles in-core the clauses in text file(s) Files.
compound(?X) [ISO]
X is currently instantiated to a term of arity > 0.
consult(:Files)
Updates the program with interpreted clauses from file(s) Files.
copy_term(?Term,?CopyOfTerm) [ISO]
CopyOfTerm is an independent copy of Term.
create_mutable(+Datum,-Mutable)
Mutable is a new mutable term with current value Datum.
current_atom(?Atom)
One of the currently defined atoms is Atom.
current_breakpoint(:Conditions, ?BID, ?Status, ?Kind)
There is a breakpoint with conditions Conditions, identifier BID, enabledness Status, and kind Kind. (Not available in runtime systems).
current_char_conversion(?InChar, ?OutChar) [ISO]

InChar is mapped to OutChar in the current character-conversion mapping.

current_input(?Stream) [ISO]
Stream is the current input stream.
current_key(?KeyName,?KeyTerm) [Obsolescent]
There is a recorded item in the internal database whose key is KeyTerm, the name of which is KeyName.
current_module(?Module)
Module is a module currently in the system.
current_module(?Module,?File)
Module is a module currently in the system, loaded from File.
current_op(?Precedence,?Type,?Op) [ISO]
Atom Op is an operator type Type precedence Precedence.
current_output(?Stream) [ISO]
Stream is the current output stream.
current_predicate(?Name/?Arity) [ISO]
A user defined or library predicate is named Name, arity Arity.
current_predicate(?Name,:Head)
current_predicate(?Name,-Head)
A user defined or library predicate is named Name, most general goal Head.
current_prolog_flag(?FlagName,?Value) [ISO]
Value is the current value of the Prolog flag FlagName.
current_stream(?AbsFileName,?Mode,?Stream)
There is a stream Stream associated with the file AbsFileName and opened in mode Mode.
debug
Switches on debugging in leap mode (not available in runtime systems).
debugger_command_hook(+DCommand,?Actions) [Hook]
user:debugger_command_hook(+DCommand,?Actions)
Allows the interactive debugger to be extended with user-defined commands.
debugging
Displays debugging status information
dif(?X,?Y)
The terms X and Y are different.
disable_breakpoints(+BIDs)
Disables the breakpoints specified by BIDs. (Not available in runtime systems).
discontiguous Specs [Declaration,ISO]
Not a built-in predicate; discontiguous declaration.
display(?Term)
Displays the term Term on the standard output stream.
dynamic Specs [Declaration,ISO]
Not a built-in predicate; dynamic declaration.
enable_breakpoints(+BIDs)
Enables the breakpoints specified by BIDs. (Not available in runtime systems).
ensure_loaded(:Files) [ISO]
Compiles or loads the file(s) Files if need be.
erase(+Ref)
Erases the clause or record whose unique identifier is Ref.
error_exception(+Exception) [Hook]
user:error_exception(+Exception)
Exception is an exception that traps to the debugger if it is switched on.
execution_state(:Tests)
Tests are satisfied in the current state of the execution. (Not available in runtime systems).
execution_state(+FocusConditions, :Tests)
Tests are satisfied in the state of the execution pointed to by FocusConditions. (Not available in runtime systems).
expand_term(+Term1,?Term2)
The term Term1 is a shorthand which expands to the term Term2.
fail [ISO]
false
False.
fcompile(:Files) [Obsolescent]
Compiles file-to-file the clauses in text file(s) Files (not available in runtime systems).
file_search_path(Alias,?Expansion) [Hook]
user:file_search_path(Alias,?Expansion)
Tells how to expand Alias(File) file names.
fileerrors
Enables reporting of file errors.
findall(?Template,:Goal,?Bag) [ISO]
findall(?Template,:Goal,?Bag,?Remainder)
A prefix of Bag is the list of instances of Template such that Goal is provable. The rest of Bag is Remainder or the empty list.
float(?X) [ISO]
X is currently instantiated to a float.
flush_output [ISO]
flush_output(+Stream) [ISO]
Flushes the buffers associated with Stream.
foreign(+CFunctionName,+Predicate) [Hook]
foreign(+CFunctionName,+Language,+Predicate) [Hook]
Tell Prolog how to define Predicate to invoke CFunctionName.
foreign_file(+ObjectFile,+Functions) [Hook,obsolescent]
Tells Prolog that foreign functions Functions are in file ObjectFile. Use foreign_resource/2 instead.
foreign_resource(+ResourceName,+Functions) [Hook]
Tells Prolog that foreign functions Functions are in resource ResourceName.
format(+Format,:Arguments)
format(+Stream,+Format,:Arguments)
Writes Arguments according to Format on the stream Stream or on the current output stream.
freeze(?Var,:Goal)
Blocks Goal until nonvar(Var) holds.
frozen(-Var,?Goal)
The goal Goal is blocked on the variable Var.
functor(+Term,?Name,?Arity) [ISO]
functor(?Term,+Name,+Arity) [ISO]
The principal functor of the term Term has name Name and arity Arity.
garbage_collect
Performs a garbage collection of the global stack.
garbage_collect_atoms
Performs a garbage collection of the atoms.
gc
Enables garbage collection of the global stack.
generate_message_hook(+Message, -L0, -L) [Hook]
user:generate_message_hook(+Message, -L0, -L)

A way for the user to override the call to 'SU_messages':generate_message/3 in the message generation phase in print_message/2.

get(?C) [Obsolescent]
get(+Stream,?C) [Obsolescent]
The next printing character from the stream Stream or from the current input stream is C.
get0(?C) [Obsolescent]
get0(+Stream,?C) [Obsolescent]
The next character from the stream Stream or from the current input stream is C.
get_byte(?Byte) [ISO]
get_byte(+Stream,?Byte) [ISO]
Byte is the next byte read from the binary stream Stream.
get_char(?Char) [ISO]
get_char(+Stream,?Char) [ISO]
Char is the one-char atom naming the next character read from text stream Stream.
get_code(?Code) [ISO]
get_code(+Stream,?Code) [ISO]
Code is the character code of the next character read from text stream Stream.
get_mutable(?Datum,+Mutable)
The current value of the mutable term Mutable is Datum.
goal_expansion(+Goal,+Module,-NewGoal) [Hook]
user:goal_expansion(+Goal,+Module,-NewGoal)
Defines a transformation from Goal in module Module to NewGoal.
goal_source_info(+AGoal, ?Goal, ?SourceInfo)
Decomposes the annotated goal AGoal into a Goal proper and the SourceInfo descriptor term, indicating the source position of the goal.
ground(?X)
X is currently free of unbound variables.
halt [ISO]
Halts Prolog. (returns to C in recursive calls to Prolog from C).
halt(Code) [ISO]
Halts Prolog immediately, returning Code.
help [Hookable]
Prints a help message (not available in runtime systems).
if(+P,+Q,+R)
If P then Q else R, exploring all solutions of P.
include Specs [Declaration,ISO]
Not a built-in predicate; include declaration.
incore(+Term) [Obsolescent]
Executes the procedure call Term.
initialization :Goal [ISO]
Includes Goal to the set of goals which shall be executed after the file that is being loaded has been completely loaded.
instance(+Ref,?Term)
Term is a most general instance of the record or clause uniquely identified by Ref.
integer(?X) [ISO]
X is currently instantiated to an integer.
?Y is +X [ISO]
Y is the value of the arithmetic expression X.
is_mutable(?X)
X is currently instantiated to a mutable term.
keysort(+List1,?List2)
The list List1 sorted by key yields List2.
leash(+Mode)
Sets leashing mode to Mode (not available in runtime systems).
length(?List,?Length)
The length of list List is Length.
library_directory(?Directory) [Hook]
user:library_directory(?Directory)
Tells how to expand library(File) file names.
line_count(+Stream,?N)
N is the number of lines read/written on stream Stream.
line_position(+Stream,?N)
N is the number of characters read/written on the current line of Stream.
listing
listing(:Specs)
Lists the interpreted predicate(s) specified by Specs or all interpreted predicates in the type-in module. Any variables in the listed clauses are internally bound to ground terms before printing. Any attributes or blocked goals attached to such variables will be ignored. % If this causes any blocked goals to be executed, the behavior is undefined.
load(:Files) [Obsolescent]
Loads .ql file(s) Files.
load_files(:Files)
load_files(:Files, +Options)
Loads source, .po or .ql file(s) Files obeying Options.
load_foreign_files(:ObjectFiles,+Libraries) [Hookable,obsolescent]
Links object files ObjectFiles into Prolog. Use splfr and load_foreign_resource/1 instead.
load_foreign_resource(:Resource)
Loads foreign resource Resource into Prolog.
message_hook(+Severity, +Message, +Lines) [Hook]
user:message_hook(+Severity, +Message, +Lines)
Overrides the call to print_message_lines/3 in print_message/2. A way for the user to intercept the abstract message term Message of type Severity, whose translation is Lines, before it is actually printed.
meta_predicate Specs [Declaration]
Not a built-in predicate; meta-predicate declaration.
mode Specs [Declaration]
Not a built-in predicate; mode declaration.
module(+Module)
Sets the type-in module to Module.
module(+Module, +ExportList) [Declaration]
module(+Module, +ExportList, +Options) [Declaration]
Not a built-in predicate; module declaration.
multifile Specs [Declaration,ISO]
Not a built-in predicate; multifile declaration.
name(+Const,?CharList) [Obsolescent]
name(?Const,+CharList)
The name of atom or number Const is the string CharList. Subsumed by atom_chars/2 and number_chars/2.
nl [ISO]
nl(+Stream) [ISO]
Outputs a new line on stream Stream or on the current output stream.
nodebug
Switches off debugging (not available in runtime systems).
nofileerrors
Disables reporting of file errors.
nogc
Disables garbage collection of the global stack.
nonvar(?X) [ISO]
X is a non-variable.
nospy :Spec
Removes spypoints from the predicate(s) specified by Spec (not available in runtime systems).
nospyall
Removes all spypoints (not available in runtime systems).
notrace
nozip
Switches off debugging (not available in runtime systems).
number(?X) [ISO]
X is currently instantiated to a number.
number_chars(+Number,?CodeList) [SICStus only]
number_chars(?Number,+CodeList) [SICStus only]
The name of the number Number is the list of character codes CodeList.
number_chars(+Number,?CharList) [ISO only]
number_chars(?Number,+CharList) [ISO only]
The name of the number Number is the list of one-char atoms CharList.
number_codes(+Number,?CodeList) [ISO]
number_codes(?Number,+CodeList) [ISO]
The name of the number Number is the list of character codes CodeList.
numbervars(?Term,+N,?M)
Number the variables in the term Term from N to M-1.
once(+P) [ISO]
Finds the first solution, if any, of goal P.
on_exception(?Pattern,:ProtectedGoal,:Handler)
Executes the procedure call ProtectedGoal. If during the execution throw(Exception) or raise_exception(Exception) is called, and Exception matches Pattern, the execution of ProtectedGoal aborts, Pattern is unified with a copy of Exception and Handler is called.
op(+Precedence,+Type,+Name) [ISO]
Makes atom(s) Name an operator of type Type precedence Precedence.
open(+FileName,+Mode,-Stream) [ISO]
open(+FileName,+Mode,-Stream,+Options) [ISO]
Opens file FileName in mode Mode with options Options as stream Stream.
open_null_stream(-Stream)
Opens an output stream to the null device.
otherwise
True.
peek_byte(?N) [ISO]
peek_byte(+Stream,?N) [ISO]
N is the next byte peeked at from the binary stream Stream or from the current input stream.
peek_char(?N) [SICStus only]
peek_char(+Stream,?N) [SICStus only]
N is the character code of the next character peeked at from Stream or from the current input stream.
peek_char(?N) [ISO only]
peek_char(+Stream,?N) [ISO only]
N is the one-char atom of the next character peeked at from the text stream Stream or from the current input stream.
peek_code(?N) [ISO]
peek_code(+Stream,?N) [ISO]
N is the character code of the next character peeked at from Stream or from the current input stream.
phrase(:Phrase,?List)
phrase(:Phrase,?List,?Remainder)
Grammar rules. The list List can be parsed as a phrase of type Phrase. The rest of the list is Remainder or empty.
portray(+Term) [Hook]
user:portray(+Term)
Tells print/1 what to do.
portray_clause(?Clause)
portray_clause(+Stream,?Clause)
Pretty prints Clause on the stream Stream or on the current output stream.
portray_message(+Severity,+Message) [Hook]
user:portray_message(+Severity,+Message)
Tells print_message/2 what to do.
predicate_property(:Head,?Prop)
predicate_property(-Head,?Prop)
Head is the most general goal of a currently defined predicate that has the property Prop.
print(?Term) [Hookable]
print(+Stream,?Term) [Hookable]
Portrays or else writes the term Term on the stream Stream or on the current output stream.
print_message(+Severity,+Message) [Hookable]
Portrays or else writes Message of a given Severity on the standard error stream.
print_message_lines(+Stream, +Severity, +Lines)
Print the Lines to Stream, preceding each line with a prefix defined by Severity.
profile_data(:Spec,?Selection,?Resolution,-Data)
Data is the profiling data collected from the instrumented predicates covered by Spec with selection and resolution Selection and Resolution respectively (not available in runtime systems).
profile_reset(:Spec)
The profiling counters for the instrumented predicates covered by Spec are zeroed (not available in runtime systems).
prolog_flag(?FlagName,?Value)
Value is the current value of FlagName.
prolog_flag(+FlagName,?OldValue,?NewValue)
OldValue and NewValue are the old and new values of FlagName.
prolog_load_context(?Key,?Value)
Value is the value of the compilation/loading context variable identified by Key.
prompt(?Old,?New)
Changes the prompt from Old to New.
public Specs [Declaration,obsolescent]
Not a built-in predicate; public declaration.
put(+C) [Obsolescent]
put(+Stream,+C) [Obsolescent]
The next character code sent to the stream Stream or to the current output stream is C.
put_byte(+B) [ISO]
put(+Stream,+B) [ISO]
The next byte sent to the binary stream Stream or to the current output stream is B.
put_char(+C) [ISO]
put_char(+Stream,+C) [ISO]
The next one-char atom sent to the text stream Stream or to the current output stream is C.
put_code(+C) [ISO]
put_code(+Stream,+C) [ISO]
The next character code sent to the text stream Stream or to the current output stream is C.
query_hook(+QueryClass, +Query, +QueryLines, +Help, +HelpLines, -Answer) [Hook]
user:query_hook(+QueryClass, +Query, +QueryLines, +Help, +HelpLines, -Answer)
Called by ask_query/4 before processing the query. If this predicate succeeds, it is assumed that the query has been processed and nothing further is done.
query_class_hook(+QueryClass, -Prompt, -InputMethod, -MapMethod, -FailureMode) [Hook]
user:query_class_hook(+QueryClass, -Prompt, -InputMethod, -MapMethod, -FailureMode)
Provides the user with a method of overriding the call to 'SU_messages':query_class/5 in the preparation phase of query processing. This way the default query class characteristics can be changed.
query_input_hook(+InputMethod, +Prompt, -RawInput) [Hook]
user:query_input_hook(+InputMethod, +Prompt, -RawInput)
Provides the user with a method of overriding the call to 'SU_messages':query_input/3 in the input phase of query processing. This way the implementation of the default input methods can be changed.
query_map_hook(+MapMethod, +RawInput, -Result, -Answer) [Hook]
user:query_map_hook(+MapMethod, +RawInput, -Result, -Answer)
Provides the user with a method of overriding the call to 'SU_messages':query_map/4 in the mapping phase of query processing. This way the implementation of the default map methods can be changed.
raise_exception(+Exception)
Causes the abortion of a part of the execution tree scoped by the closest enclosing catch/3 or on_exception/3 invocation with its first argument matching Exception.
read(?Term) [ISO]
read(+Stream,?Term) [ISO]
Reads the term Term from the stream Stream or from the current input stream.
read_term(?Term,+Options) [ISO]
read_term(+Stream,?Term,+Options) [ISO]
Reads the term Term from the stream Stream or from the current input stream with extra Options.
reconsult(:Files) [Obsolescent]
Updates the program with interpreted clauses from file(s) Files.
recorda(+Key,?Term,-Ref) [Obsolescent]
Makes the term Term the first record under key Key with unique identifier Ref.
recorded(?Key,?Term,?Ref) [Obsolescent]
The term Term is currently recorded under key Key with unique identifier Ref.
recordz(+Key,?Term,-Ref) [Obsolescent]
Makes the term Term the last record under key Key with unique identifier Ref.
reinitialise
Initializes Prolog (returns to C in recursive calls to Prolog from C).
remove_breakpoints(+BIDs)
Removes the breakpoints specified by BIDs. (Not available in runtime systems).
repeat [ISO]
Succeeds repeatedly.
require(:PredSpecs)
Tries to locate and load library files that export the specified predicates. Creates index files if necessary (not available in runtime systems).
restore(+File)
Restores the state saved in file File.
retract(:Clause) [ISO]
Erases repeatedly the next interpreted clause of form Clause.
retractall(:Head)
Erases all clauses whose head matches Head.
runtime_entry(+Message) [Hook]
user:runtime_entry(+Message)
The entry point of most runtime systems. Will be called with Message = start.
save_program(+File)
save_program(+File, :Goal)
Saves the current state of the Prolog data base in file File. Upon restore, Goal is executed.
save_modules(+Modules, +File)
Saves the current contents of the given Modules in the file File.
save_predicates(:Preds, +File)
Saves the current definitions of the given Preds in the file File.
save_files(+SourceFiles, +File)
Saves the modules, predicates and clauses and directives in the given SourceFiles in the file File.
see(+File)
Makes file File the current input stream.
seeing(?File)
The current input stream is named File.
seek(+Stream,+Offset,+Method,-NewLocation)
Sets the stream Stream to the byte offset Offset relative to Method, and NewLocation is the new byte offset from the beginning of the file after the operation.
seen
Closes the current input stream.
set_input(+Stream) [ISO]
Sets the current input stream to Stream.
set_output(+Stream) [ISO]
Sets the current output stream to Stream.
set_prolog_flag(+FlagName,?NewValue) [ISO]
NewValue becomes the new value of FlagName.
set_stream_position(+Stream,+Position) [ISO]
Position is a new stream position of Stream, which is then set to the new position.
setof(?Template,:Goal,?Set) [ISO]
Set is the set of instances of Template such that Goal is satisfied (not just provable).
simple(?X)
X is currently uninstantiated or atomic.
skip(+C) [Obsolescent]
skip(+Stream,+C) [Obsolescent]
Skips characters from Stream or from the current input stream until after character C.
skip_line
skip_line(+Stream)
Skips characters from Stream or from the current input stream until the next <LFD>.
sort(+List1,?List2)
The list List1 sorted into order yields List2.
source_file(?File)
source_file(:Pred,?File)
source_file(-Pred,?File)
The predicate Pred is defined in the file File.
spy :Spec
Sets spypoints on the predicate(s) specified by Spec (not available in runtime systems).
spy(:Spec, :Conditions)
Sets spypoints with condition Conditions on the predicates specified by Spec (not available in runtime systems).
statistics
Outputs various execution statistics.
statistics(?Key,?Value)
The execution statistics key Key has value Value.
stream_code(+Stream,?StreamCode)
stream_code(?Stream,+StreamCode)
StreamCode is an integer representing a pointer to the internal representation of Stream.
stream_position(+Stream,?Position)
Position is the current stream position of Stream.
stream_position_data(?Field,?Position,?Data)
The Field field of the stream position Pos term is Data.
stream_property(?Stream, ?Property)) [ISO]
Stream Stream has property Property.
sub_atom(+Atom,?Before,?Length,?After,?SubAtom) [ISO]
The characters of SubAtom form a sublist of the characters of Atom, such that the number of characters preceding SubAtom is Before, the number of characters after SubAtom is After, and the length of SubAtom is Length.
tab(+N) [Obsolescent]
tab(+Stream,+N) [Obsolescent]
Outputs N spaces to the stream Stream or to the current output stream.
tell(+File)
Makes file File the current output stream.
telling(?File)
The current output stream is named File.
term_expansion(+Term1,?TermOrTerms) [Hook]
term_expansion(+Term1,+Layout1,?TermOrTerms,?Layout2) [Hook]
user:term_expansion(+Term1,?TermOrTerms)
user:term_expansion(+Term1,+Layout1,?TermOrTerms,?Layout2)
Tell expand_term/2 what to do.
throw(+Exception) [ISO]
Causes the abortion of a part of the execution tree scoped by the closest enclosing catch/3 or on_exception/3 invocation with its first argument matching Exception.
told
Closes the current output stream.
trace
Switches on debugging in creep mode (not available in runtime systems).
trimcore
Reclaims and defragmentizes unused memory.
true [ISO]
Succeeds.
ttyflush [Obsolescent]
Flushes the standard output stream buffer.
ttyget(?C) [Obsolescent]
The next printing character input from the standard input stream is C.
ttyget0(?C) [Obsolescent]
The next character input from the standard input stream is C.
ttynl [Obsolescent]
Outputs a new line on the standard output stream.
ttyput(+C) [Obsolescent]
The next character output to the standard output stream is C.
ttyskip(+C) [Obsolescent]
Skips characters from the standard input stream until after character C.
ttytab(+N) [Obsolescent]
Outputs N spaces to the standard output stream.
undo(:Goal)
Goal is called on backtracking.
unify_with_occurs_check(?X, ?Y) [ISO]
True if X and Y unify to a finite (acyclic) term.
unknown(?OldState,?NewState)
Changes action on undefined predicates from OldState to NewState (not available in runtime systems).
unknown_predicate_handler(+Goal,+Module,-NewGoal) [Hook]
user:unknown_predicate_handler(+Goal,+Module,-NewGoal)
Defines an alternative goal to be called in place of a call to an unknown predicate.
unload_foreign_resource(:Resource)
Unloads foreign resource Resource from Prolog.
update_mutable(+Datum,+Mutable)
Updates the current value of the mutable term Mutable to become Datum.
use_module(:Files)
Loads the module-file(s) Files if necessary and imports all public predicates.
use_module(:File,+Imports)
Loads the module-file File if necessary and imports the predicates in Imports.
use_module(+Module,?File,+Imports)
use_module(?Module,:File,+Imports)
Imports Imports from an existing Module, or else the same as use_module/2 unifying Module to the module defined in File.
user_help [Hook]
user:user_help
Tells help/0 what to do.
var(?X) [ISO]
X is currently uninstantiated.
version
Displays introductory and/or system identification messages (not available in runtime systems).
version(+Message)
Adds the atom Message to the list of introductory messages (not available in runtime systems).
volatile Specs [Declaration]
Not a built-in predicate; volatile declaration.
when(+Condition,:Goal)
Blocks Goal until the Condition is true.
write(+Term) [ISO]
write(+Stream,+Term) [ISO]
Writes the term Term on the stream Stream or on the current output stream.
write_canonical(+Term) [ISO]
write_canonical(+Stream,+Term) [ISO]
Writes Term on the stream Stream or on the current output stream so that it may be read back.
write_term(+Term,+Options) [ISO]
write_term(+Stream,+Term,+Options) [ISO]
Writes the term Term on the stream Stream or on the current output stream with extra Options.
writeq(+Term) [ISO]
writeq(+Stream,+Term) [ISO]
Writes the term Term on the stream Stream or on the current output stream, quoting names where necessary.
zip
Switches on debugging in zip mode (not available in runtime systems).


Node:Full Syntax, Next:, Previous:Pred Summary, Up:Top

Full Prolog Syntax

A Prolog program consists of a sequence of sentences or lists of sentences. Each sentence is a Prolog term. How terms are interpreted as sentences is defined below (see Sentence). Note that a term representing a sentence may be written in any of its equivalent syntactic forms. For example, the compound term Head :- Body could be written in standard prefix notation instead of as the usual infix operator.

Terms are written as sequences of tokens. Tokens are sequences of characters which are treated as separate symbols. Tokens include the symbols for variables, constants and functors, as well as punctuation characters such as brackets and commas.

We define below how lists of tokens are interpreted as terms (see Term Token). Each list of tokens which is read in (for interpretation as a term or sentence) has to be terminated by a full-stop token. Two tokens must be separated by a layout-text token if they could otherwise be interpreted as a single token. Layout-text tokens are ignored when interpreting the token list as a term, and may appear at any point in the token list.

We define below defines how tokens are represented as strings of characters (see Token String). But we start by describing the notation used in the formal definition of Prolog syntax (see Syntax Notation).


Node:Syntax Notation, Next:, Previous:Full Syntax, Up:Full Syntax

Notation

  1. Syntactic categories (or non-terminals) are written thus: item. Depending on the section, a category may represent a class of either terms, token lists, or character strings.
  2. A syntactic rule takes the general form
    C --> F1 | F2 | F3
    

    which states that an entity of category C may take any of the alternative forms F1, F2, F3, etc.

  3. Certain definitions and restrictions are given in ordinary English, enclosed in { } brackets.
  4. A category written as C... denotes a sequence of one or more Cs.
  5. A category written as ?C denotes an optional C. Therefore ?C... denotes a sequence of zero or more Cs.
  6. A few syntactic categories have names with arguments, and rules in which they appear may contain meta-variables looking thus: X. The meaning of such rules should be clear from analogy with the definite clause grammars (see Definite).
  7. In the section describing the syntax of terms and tokens (see Term Token) particular tokens of the category name are written thus: name, while tokens which are individual punctuation characters are written literally.


Node:Sentence, Next:, Previous:Syntax Notation, Up:Full Syntax

Syntax of Sentences as Terms

sentence          --> module : sentence
                   |  list
                         { where list is a list of sentence }
                   |  clause
                   |  directive
                   |  query
                   |  grammar-rule

clause            --> rule | unit-clause

rule              --> head :- body

unit-clause       --> head
                         { where head is not otherwise a sentence }

directive         --> :- body

query             --> ?- body

head              --> module : head
                   |  goal
                         { where goal is not a variable }

body             --> module : body
                   |  body -> body ; body
                   |  body -> body
                   |  \+ body
                   |  body ; body
                   |  body , body
                   |  goal

goal              --> term
                         { where term is not otherwise a body }

grammar-rule      --> gr-head --> gr-body

gr-head           --> module : gr-head
                   |  gr-head , terminals
                   |  non-terminal
                         { where non-terminal is not a variable }

gr-body           --> module : gr-body
                   |  gr-body -> gr-body ; gr-body
                   |  gr-body -> gr-body
                   |  \+ gr-body
                   |  gr-body ; gr-body
                   |  gr-body , gr-body
                   |  non-terminal
                   |  terminals
                   |  gr-condition

non-terminal      --> term
                         { where term is not otherwise a gr-body }

terminals         --> list | string

gr-condition      --> ! | { body }

module            --> atom


Node:Term Token, Next:, Previous:Sentence, Up:Full Syntax

Syntax of Terms as Tokens

term-read-in      --> subterm(1200) full-stop

subterm(N)        --> term(M)
                         { where M is less than or equal to N }

term(N)           --> op(N,fx) subterm(N-1)
                         { except in the case of a number }
                         { if subterm starts with a (,
                           op must be followed by layout-text }
                   |  op(N,fy) subterm(N)
                         { if subterm starts with a (,
                           op must be followed by layout-text }
                   |  subterm(N-1) op(N,xfx) subterm(N-1)
                   |  subterm(N-1) op(N,xfy) subterm(N)
                   |  subterm(N) op(N,yfx) subterm(N-1)
                   |  subterm(N-1) op(N,xf)
                   |  subterm(N) op(N,yf)

term(1000)        --> subterm(999) , subterm(1000)

term(0)           --> functor ( arguments )
                         { provided there is no layout-text between
                           the functor and the ( }
                   |  ( subterm(1200) )
                   |  { subterm(1200) }
                   |  list
                   |  string
                   |  constant
                   |  variable

op(N,T)           --> name
                         { where name has been declared as an
                           operator of type T and precedence N }

arguments         --> subterm(999)
                   |  subterm(999) , arguments

list              --> []
                   |  [ listexpr ]

listexpr          --> subterm(999)
                   |  subterm(999) , listexpr
                   |  subterm(999) | subterm(999)

constant          --> atom | number

number            --> unsigned-number
                   |  sign unsigned-number
                   |  sign inf
                   |  sign nan

unsigned-number   --> natural-number | unsigned-float

atom              --> name

functor           --> name


Node:Token String, Next:, Previous:Term Token, Up:Full Syntax

Syntax of Tokens as Character Strings

SICStus Prolog supports wide characters (up to 31 bits wide). It is assumed that the character code set is an extension of (7 bit) ASCII, i.e. that it includes the codes 0..127 and these codes are interpreted as ASCII characters.

Each character in the code set has to be classified as belonging to one of the character categories, such as small-letter, digit, etc. This classification is called the character-type mapping, and it is used for defining the syntax of tokens.

The user can select one of the three predefined wide character modes through the environment variable SP_CTYPE. These modes are iso_8859_1, utf8, and euc. The user can also define other wide character modes by plugging in appropriate hook functions; see Handling Wide Characters. In this case the user has to supply a character-type mapping for the codes greater than 127.

We first describe the character-type mapping for the fixed part of the code set, the 7 bit ASCII.


layout-char
These are character codes 0..32 and 127. This includes characters such as <TAB>, <LFD>, and <SPC>.
small-letter
These are character codes 97..122, i.e. the letters a through z.
capital-letter
These are character codes 65..90, i.e. the letters A through Z.
digit
These are character codes 48..57, i.e. the digits 0 through 9.
symbol-char
These are character codes 35, 36, 38, 42, 43, 45..47, 58, 60..64, 92, 94, and 126, i.e. the characters:
+-*/\^<>=~:.?@#$&
In sicstus execution mode, character code 96 (`) is also a symbol-char.
solo-char
These are character codes 33 and 59 i.e. the characters ! and ;.
punctuation-char
These are character codes 37, 40, 41, 44, 91, 93, and 123..125, i.e. the characters %(),[]{|}.
quote-char
These are character codes 34 and 39 i.e. the characters " and '. In iso execution mode character code 96 (`) is also a quote-char.
underline
This is character code 95 i.e. the character _.

We now provide the character-type mapping for the characters above the 7 bit ASCII range, for each of the built-in wide character modes.

The iso_8859_1 mode has the character set 0..255 and the following character-type mapping for the codes 128..255:


layout-char
the codes 128..159.
small-letter
the codes 223..246, and 248..255.
capital-letter
the codes 192..214, and 216..222.
symbol-char
the codes 160..191, 215, and 247.

The utf8 mode has the character set 0..(2^31-1). The character-type mapping for the codes 128..255 is the same as for the iso_8859_1 mode. All character codes above 255 are classified as small-letters.

The euc mode character set is described in Representation of EUC Wide Characters. All character codes above 127 are classified as small-letters.

token             --> name
                   |  natural-number
                   |  unsigned-float
                   |  variable
                   |  string
                   |  punctuation-char
                   |  layout-text
                   |  full-stop

name              --> quoted-name
                   |  word
                   |  symbol
                   |  solo-char
                   |  [ ?layout-text ]
                   |  { ?layout-text }

quoted-item       --> char  { other than ' or \ }
                   |  ''
                   |  \ escape-sequence  {unless character escapes have been switched off }

word              --> small-letter ?alpha...

symbol            --> symbol-char...
                         { except in the case of a full-stop
                           or where the first 2 chars are /* }

natural-number    --> digit...
                   |  base-prefix alpha...
                         { where each alpha must be digits of }
                         {the base indicated by base-prefix,
                         treating a,b,... and A,B,... as 10,11,... }
                   |  0 ' char-item
                         { yielding the character code for char }

unsigned-float    --> simple-float
                   |  simple-float exp exponent

simple-float      --> digit... . digit...

exp               --> e  |  E

exponent          --> digit... | sign digit...

sign              --> - | +

variable          --> underline ?alpha...
                   |  capital-letter ?alpha...

string            --> " ?string-item... "

string-item       --> char  { other than " or \ }
                   |  ""
                   |  \ escape-sequence {unless character escapes have been switched off }

layout-text             --> layout-text-item...

layout-text-item        --> layout-char | comment

comment           --> /* ?char... */
                         { where ?char... must not contain */ }
                   |  % ?char... <LFD>
                         { where ?char... must not contain <LFD> }

full-stop         --> .
                         { the following token, if any, must be layout-text}

char              --> { any character, i.e. }
                      layout-char
                   |  alpha
                   |  symbol-char
                   |  solo-char
                   |  punctuation-char
                   |  quote-char

alpha             --> capital-letter | small-letter | digit | underline

escape-sequence   --> b        { backspace, character code 8 }
                   |  t        { horizontal tab, character code 9 }
                   |  n        { newline, character code 10 }
                   |  v        { vertical tab, character code 11 }
                   |  f        { form feed, character code 12 }
                   |  r        { carriage return, character code 13 }
                   |  e        { escape, character code 27 }
                   |  d        { delete, character code 127 }
                   |  a        { alarm, character code 7 }
                   |  other-escape-sequence

There are differences between the syntax used in iso mode and in sicstus mode. The differences are described by providing different syntax rules for certain syntactic categories.

iso execution mode rules

quoted-name       --> ' ?quoted-item... '
                   |  backquoted-atom

backquoted-atom   -->
                   |  ` ?backquoted-item... `

backquoted-item   --> char  { other than ` or \ }
                   |  ``
                   |  \ escape-sequence  {unless character escapes have been switched off }

base-prefix       -->   0b { indicates base  2 }
                   |  0o { indicates base  8 }
                   |  0x { indicates base 16 }

char-item         --> quoted-item

other-escape-sequence  -->
                      x alpha... \
                         {treating a,b,... and A,B,... as 10,11,... }
                               { in the range [0..15], hex character code }
                   |  o digit... \
                               { in the range [0..7], octal character code }
                   |  c <LFD>    { ignored }
                   |  \
                   |  '
                   |  "
                   |  `
                               { represent themselves }

sicstus execution mode rules

quoted-name       --> ' ?quoted-item... '

base-prefix       --> base ' {indicates base base }

base              --> digit...  { in the range [2..36] }

char-item         --> char  { other than \ }
                   |  \ escape-sequence  {unless character escapes have been switched off }

other-escape-sequence  -->
                   |  x alpha alpha escape-terminator
                         {treating a,b,... and A,B,... as 10,11,... }
                               { in the range [0..15], hex character code }
                   |  digit ?digit ?digit escape-terminator
                               { in the range [0..7], octal character code }
                   |  ^ ?      { delete, character code 127 }
                   |  ^ capital-letter
                   |  ^ small-letter
                               { the control character alpha mod 32 }
                   |  c ?layout-char... { ignored }
                   |  layout-char  { ignored }
                   |  char    { other than the above, represents itself }


Node:Escape Sequences, Next:, Previous:Token String, Up:Full Syntax

Escape Sequences

A backslash occurring inside integers in 0' notation or inside quoted atoms or strings has special meaning, and indicates the start of an escape sequence. Character escaping can be turned off for compatibility with old code. The following escape sequences exist:

\b
backspace (character code 8)
\t
horizontal tab (character code 9)
\n
newline (character code 10)
\v
vertical tab (character code 11)
\f
form feed (character code 12)
\r
carriage return (character code 13)
\e
escape (character code 27)
\d
\^? [SICStus only]
delete (character code 127)
\a
alarm (character code 7)
\xhex-digit...\ [ISO only]
\xhex-digithex-digit [SICStus only]
the character code represented by the hexadecimal digits
\octal-digit...\ [ISO only]
\octal-digit?octal-digit?octal-digit [SICStus only]
the character code represented by the octal digits.
\^char [SICStus only]
the character code char mod 32, where char is a letter.
\layout-char [SICStus only]
A single layout character, for example a newline, is ignored.
\c
All characters up to, but not including, the next non-layout character are ignored in sicstus execution mode. In iso execution mode only a single newline character is ignored.
\\, \', \", \`
Stand for the character following the \.
\other [SICStus only]
A character not mentioned in this table stands for itself.


Node:Syntax Notes, Previous:Escape Sequences, Up:Full Syntax

Notes

  1. The expression of precedence 1000 (i.e. belonging to syntactic category term(1000)) which is written
    X,Y
    

    denotes the term ','(X,Y) in standard syntax.

  2. The parenthesized expression (belonging to syntactic category term(0))
    (X)
    

    denotes simply the term X.

  3. The curly-bracketed expression (belonging to syntactic category term(0))
    {X}
    

    denotes the term {}(X) in standard syntax.

  4. Note that, for example, -3 denotes a number whereas -(3) denotes a compound term which has - /1 as its principal functor.
  5. The character " within a string must be written duplicated. Similarly for the character ' within a quoted atom and for the character ` in backquoted atom (iso execution mode only).
  6. Unless character escapes have been switched off, backslashes in strings, quoted atoms, and integers written in 0' notation denote escape sequences.
  7. A name token declared to be a prefix operator will be treated as an atom only if no term-read-in can be read by treating it as a prefix operator.
  8. A name token declared to be both an infix and a postfix operator will be treated as a postfix operator only if no term-read-in can be read by treating it as an infix operator.
  9. The layout following the full stop is considered part of it, and so it is consumed by e.g. read/[1,2]) in sicstus execution mode, while in iso execution mode the layout remains in the input stream.


Node:Standard Operators, Next:, Previous:Full Syntax, Up:Top

Standard Operators

The following are the standard operators in iso execution mode.

:- op( 1200, xfx, [ :-, --> ]).
:- op( 1200,  fx, [ :-, ?- ]).
:- op( 1150,  fx, [ mode, public, dynamic, volatile, discontiguous,
                    multifile, block, meta_predicate,
                    initialization ]).
:- op( 1100, xfy, [ ; ]).
:- op( 1050, xfy, [ -> ]).
:- op( 1000, xfy, [ ',' ]).
:- op(  900,  fy, [ \+, spy, nospy ]).
:- op(  700, xfx, [ =, \=, is, =.., ==, \==, @<, @>, @=<, @>=,
                                =:=, =\=, <, >, =<, >= ]).
:- op(  550, xfy, [ : ]).
:- op(  500, yfx, [ +, -, #, /\, \/ ]).
:- op(  400, yfx, [ *, /, //, mod, rem, <<, >> ]).
:- op(  200, xfx, [ ** ]).
:- op(  200, xfy, [ ^ ]).
:- op(  200,  fy, [ +, -, \ ]).

The following operators differ in sicstus execution mode.

:- op(  500,  fx, [ +, - ]).
:- op(  300, xfx, [ mod ]).


Node:References, Next:, Previous:Standard Operators, Up:Top

References

[Aggoun & Beldiceanu 90]
A. Aggoun and N. Beldiceanu, Time Stamps Techniques for the Trailed Data in Constraint Logic Programming Systems, Actes du séminaires Programmation en Logique, Trégastel, France, May 1990.
[Aggoun & Beldiceanu 93]
A. Aggoun and N. Beldiceanu, Extending CHIP in order to Solve Complex Scheduling and Placement Problems, Mathl. Comput. Modelling, vol. 17, no. 7, pp. 57-73, Pergamon Press Ltd., 1993.
[Beldiceanu & Contejean 94]
N. Beldiceanu and E. Contejean, Introducing Global Constraints in CHIP, Mathl. Comput. Modelling, vol. 20, no. 12, pp. 97-123, Pergamon Press Ltd., 1994.
[Bryant 86]
R.E. Bryant, Graph-Based Logarithms for Boolean Function Manipulation, IEEE Trans. on Computers, August, 1986.
[Carlsson 90]
M. Carlsson, Design and Implementation of an OR-Parallel Prolog Engine, SICS Dissertation Series 02, 1990.
[Carreiro & Gelernter 89a]
N. Carreiro and D. Gelernter, Linda in Context, Comm. of the ACM, 32(4) 1989.
[Carreiro & Gelernter 89b]
N. Carreiro and D. Gelernter, How to Write Parallel Programs: A Guide to the Perplexed, ACM Computing Surveys, September 1989.
[Clocksin & Mellish 81]
W.F. Clocksin and C.S. Mellish, Programming in Prolog, Springer-Verlag, 1981.
[Colmerauer 75]
A. Colmerauer, Les Grammaires de Metamorphos, Technical Report, Groupe d'Intelligence Artificielle, Marseille-Luminy, November, 1975.
[Colmerauer 90]
Colmerauer A.: An Introduction to Prolog III, Communications of the ACM, 33(7), 69-90, 1990.
[Diaz & Codognet 93]
D. Diaz and P. Codognet, A Minimal Extension of the WAM for clp(FD), Proceedings of the International Conference on Logic Programming, MIT Press, 1993.
[Elshiewy 90]
N.A. Elshiewy, Robust Coordinated Reactive Computing in Sandra, SICS Dissertation Series 03, 1990.
[Fruehwirth 98]
Th. Fruehwirth, Theory and Practice of Constraint Handling Rules, Special Issue on Constraint Logic Programming (P. Stuckey and K. Marriot, Eds.), Journal of Logic Programming, Vol 37(1-3), pp 95-138, October 1998.
[Gorlick & Kesselman 87]
M.M. Gorlick and C.F. Kesselman, Timing Prolog Programs Without Clocks, Proc. Symposium on Logic Programming, pp. 426-432, IEEE Computer Society, 1987.
[Heintze et al. 87]
N. Heintze, J. Jaffar, S. Michaylov, P. Stuckey, R. Yap, The CLP(R) Programmers Manual, Monash University, Clayton, Victoria, Australia, Department of Computer Science, 1987.
[Holzbaur 90]
C. Holzbaur, Specification of Constraint Based Inference Mechanism through Extended Unification, dissertation, Dept. of Medical Cybernetics & AI, University of Vienna, 1990.
[Holzbaur 92a]
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