1,150 research outputs found
On the Implementation of GNU Prolog
GNU Prolog is a general-purpose implementation of the Prolog language, which
distinguishes itself from most other systems by being, above all else, a
native-code compiler which produces standalone executables which don't rely on
any byte-code emulator or meta-interpreter. Other aspects which stand out
include the explicit organization of the Prolog system as a multipass compiler,
where intermediate representations are materialized, in Unix compiler
tradition. GNU Prolog also includes an extensible and high-performance finite
domain constraint solver, integrated with the Prolog language but implemented
using independent lower-level mechanisms. This article discusses the main
issues involved in designing and implementing GNU Prolog: requirements, system
organization, performance and portability issues as well as its position with
respect to other Prolog system implementations and the ISO standardization
initiative.Comment: 30 pages, 3 figures, To appear in Theory and Practice of Logic
Programming (TPLP); Keywords: Prolog, logic programming system, GNU, ISO,
WAM, native code compilation, Finite Domain constraint
The Ciao clp(FD) library. A modular CLP extension for Prolog
We present a new free library for Constraint Logic Programming over Finite Domains, included with the Ciao Prolog system. The library is entirely written in Prolog, leveraging on Ciao's module system and code transformation capabilities in order to achieve a highly modular design without compromising performance. We describe the interface,
implementation, and design rationale of each modular component. The library meets several design goals: a high level of modularity, allowing the individual components to be replaced by different versions; highefficiency, being competitive with other TT> implementations; a glass-box
approach, so the user can specify new constraints at different levels; and a Prolog implementation, in order to ease the integration with Ciao's code analysis components. The core is built upon two small libraries which implement integer ranges and closures. On top of that, a finite domain
variable datatype is defined, taking care of constraint reexecution depending on range changes. These three libraries form what we call the TT> kernel of the library. This TT> kernel is used in turn to implement several higher-level finite domain constraints, specified using indexicals. Together with a labeling module this layer forms what we name the TT> solver. A final level integrates the CLP (J7©) paradigm with our TT> solver. This is achieved using attributed variables and a compiler from
the CLP (J7©) language to the set of constraints provided by the solver. It should be noted that the user of the library is encouraged to work in any of those levels as seen convenient: from writing a new range module to enriching the set of TT> constraints by writing new indexicals
Experiments with a Convex Polyhedral Analysis Tool for Logic Programs
Convex polyhedral abstractions of logic programs have been found very useful
in deriving numeric relationships between program arguments in order to prove
program properties and in other areas such as termination and complexity
analysis. We present a tool for constructing polyhedral analyses of
(constraint) logic programs. The aim of the tool is to make available, with a
convenient interface, state-of-the-art techniques for polyhedral analysis such
as delayed widening, narrowing, "widening up-to", and enhanced automatic
selection of widening points. The tool is accessible on the web, permits user
programs to be uploaded and analysed, and is integrated with related program
transformations such as size abstractions and query-answer transformation. We
then report some experiments using the tool, showing how it can be conveniently
used to analyse transition systems arising from models of embedded systems, and
an emulator for a PIC microcontroller which is used for example in wearable
computing systems. We discuss issues including scalability, tradeoffs of
precision and computation time, and other program transformations that can
enhance the results of analysis.Comment: Paper presented at the 17th Workshop on Logic-based Methods in
Programming Environments (WLPE2007
Logic programming in the context of multiparadigm programming: the Oz experience
Oz is a multiparadigm language that supports logic programming as one of its
major paradigms. A multiparadigm language is designed to support different
programming paradigms (logic, functional, constraint, object-oriented,
sequential, concurrent, etc.) with equal ease. This article has two goals: to
give a tutorial of logic programming in Oz and to show how logic programming
fits naturally into the wider context of multiparadigm programming. Our
experience shows that there are two classes of problems, which we call
algorithmic and search problems, for which logic programming can help formulate
practical solutions. Algorithmic problems have known efficient algorithms.
Search problems do not have known efficient algorithms but can be solved with
search. The Oz support for logic programming targets these two problem classes
specifically, using the concepts needed for each. This is in contrast to the
Prolog approach, which targets both classes with one set of concepts, which
results in less than optimal support for each class. To explain the essential
difference between algorithmic and search programs, we define the Oz execution
model. This model subsumes both concurrent logic programming
(committed-choice-style) and search-based logic programming (Prolog-style).
Instead of Horn clause syntax, Oz has a simple, fully compositional,
higher-order syntax that accommodates the abilities of the language. We
conclude with lessons learned from this work, a brief history of Oz, and many
entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic
Programming
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