SWI-Prolog

Wielemaker, Jan; Schrijvers, Tom; Triska, Markus; Lager, Torbjörn

doi:10.1017/s1471068411000494

Cited by 338 publications

(209 citation statements)

References 20 publications

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“…We implemented the analysis introduced in the paper, in our previous nontermination analyzer pT N T , which is written in SWI-Prolog [12] and can be downloaded from http://www.cs.kuleuven.be/˜dean/iclp2011.html. We tested our analysis on a benchmark of 14 programs similar to those in the paper.…”

Section: Discussionmentioning

confidence: 99%

Non-termination analysis of logic programs with integer arithmetics

Voets¹,

Schreye²

2011

Theory and Practice of Logic Programming

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In the past years, analyzers have been introduced to detect classes of non-terminating queries for definite logic programs. Although these non-termination analyzers have shown to be rather precise, their applicability on real-life Prolog programs is limited because most Prolog programs use non-logical features. As a first step towards the analysis of Prolog programs, this paper presents a nontermination condition for Logic Programs containing integer arithmetics. The analyzer is based on our non-termination analyzer presented at ICLP 2009. The analysis starts from a class of queries and infers a subclass of non-terminating ones. In a first phase, we ignore the outcome (success or failure) of the arithmetic operations, assuming success of all arithmetic calls. In a second phase, we characterize successful arithmetic calls as a constraint problem, the solution of which determines the non-terminating queries.Keywords : non-termination analysis, numerical computation, constraint-based approach. * Supported by the Fund for Scientific Research -FWO-project G0561-08 Abstract. In the past years, analyzers have been introduced to detect classes of non-terminating queries for definite logic programs. Although these non-termination analyzers have shown to be rather precise, their applicability on real-life Prolog programs is limited because most Prolog programs use non-logical features. As a first step towards the analysis of Prolog programs, this paper presents a non-termination condition for Logic Programs containing integer arithmetics. The analyzer is based on our non-termination analyzer presented at ICLP 2009. The analysis starts from a class of queries and infers a subclass of non-terminating ones. In a first phase, we ignore the outcome (success or failure) of the arithmetic operations, assuming success of all arithmetic calls. In a second phase, we characterize successful arithmetic calls as a constraint problem, the solution of which determines the non-terminating queries.

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Section: Discussionmentioning

confidence: 99%

Non-termination analysis of logic programs with integer arithmetics

Voets¹,

Schreye²

2011

Theory and Practice of Logic Programming

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“…Several Prolog systems that initially did not support tabling are, nowadays, converging to support some kind of tabling mechanism. Implementations of tabling are currently available in systems such as B-Prolog [33], Ciao Prolog [34], Mercury [5], SWI-Prolog [8], XSB Prolog [32] and YAP Prolog [35]. For our test bench environment, it is then particularly important to support the evaluation of tabled programs.…”

Section: Logic Programming Prolog and Tablingmentioning

confidence: 99%

On the Implementation of a Cloud-Based Computing Test Bench Environment for Prolog Systems

2017

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Software testing and benchmarking are key components of the software development process. Nowadays, a good practice in large software projects is the continuous integration (CI) software development technique. The key idea of CI is to let developers integrate their work as they produce it, instead of performing the integration at the end of each software module. In this paper, we extend a previous work on a benchmark suite for the YAP Prolog system, and we propose a fully automated test bench environment for Prolog systems, named Yet Another Prolog Test Bench Environment (YAPTBE), aimed to assist developers in the development and CI of Prolog systems. YAPTBE is based on a cloud computing architecture and relies on the Jenkins framework as well as a new Jenkins plugin to manage the underlying infrastructure. We present the key design and implementation aspects of YAPTBE and show its most important features, such as its graphical user interface (GUI) and the automated process that builds and runs Prolog systems and benchmarks.

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“…The Reasoner provides a generic json prolog [22] interface to two different sources of information, the Knowledge Base and the World Model.…”

Section: A Reasonermentioning

confidence: 99%

“…The Knowledge Base is a SWI-PL [22] The World Model [23] contains a sophisticated tracking and data association algorithm that quantifies streams of sequential measurements, called evidence, into unique objects. At its core, the World Model is a multiple-hypotheses filter, able to combine different forms of evidence into a common, dynamically updated world representation.…”

Section: A Reasonermentioning

confidence: 99%

Integrating planning and execution for ROS enabled service robots using hierarchical action representations

Janssen

Meijl

Marco

et al. 2013

2013 16th International Conference on Advanced Robotics (ICAR)

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Abstract-The aim of the RoboEarth project is to develop a globally accessible database, that enables service robots to share reusable information relevant to the execution of their daily tasks. Examples of this information are the hierarchical task descriptions, or action recipes, that represent typical household tasks as symbolic action sequences. By annotating these static action representations with hierarchical planner predicates, they can be interpreted by the Hierarchical Task Network planner SHOP2 to compose more flexible, optimized robot plans, based on the actual state of the environment and the available capabilities of the robot. To subsequently execute the composed plans in a typical household environment, the CRAM executive toolbox is adopted, allowing a tight integration between plan execution and run-time knowledge inference. This paper presents the integration of these two components into one cohesive planning and execution framework, tailored for the safe execution of abstract tasks in a challenging household environment. The resulting framework is implemented on the AMIGO service robot and a basic experiment is conducted to demonstrate the frameworks integral functionality.

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SWI-Prolog

Cited by 338 publications

References 20 publications

Non-termination analysis of logic programs with integer arithmetics

Non-termination analysis of logic programs with integer arithmetics

On the Implementation of a Cloud-Based Computing Test Bench Environment for Prolog Systems

Integrating planning and execution for ROS enabled service robots using hierarchical action representations

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