Use Of Constraint Logic Programming Research Articles

Applying Constraint Logic Programming to SQL Semantic Analysis

AbstractThis paper proposes the use of Constraint Logic Programming (CLP) to model SQL queries in a data-independent abstract layer by focusing on some semantic properties for signalling possible errors in such queries. First, we define a translation from SQL to Datalog, and from Datalog to CLP, so that solving this CLP program will give information about inconsistency, tautology, and possible simplifications. We use different constraint domains which are mapped to SQL types, and propose them to cooperate for improving accuracy. Our approach leverages a deductive system that includes SQL and Datalog, and we present an implementation in this system which is currently being tested in classroom, showing its advantages and differences with respect to other approaches, as well as some performance data.

An Investigation of Multi-Agent Planning in CLP

This paper explores the use of Constraint Logic Programming (CLP) as a platform for experimenting with planning problems in the presence of multiple interacting agents. The paper develops a novel constraint-based action language, B MAP, that enables the declarative description of large classes of multi-agent and multi-valued domains. B MAP supports several complex features, including combined effects of concurrent and interacting actions, concurrency control, and delayed effects. The paper presents a mapping of B MAP theories to CLP and it demonstrates the effectiveness of an implementation in SICStus Prolog on several benchmark problems. The effort is an evolution of previous research on using CLP for single-agent domains, demonstrating the flexibility of CLP technology to handle the more complex issues of multi-agency and concurrency.

Addressing The Facilities Layout Design Problem Through Constraint Logic Programming

One of the most difficult problems that face researchers experimenting with complex systems in real world applications is the Facility Layout Design Problem. It relies with the design and location of production lines, machinery and equipment, inventory storage and shipping facilities. In this work it is intended to address this problem through the use of Constraint Logic Programming (CLP) technology. The use of Genetic Algorithms (GA) as optimisation technique in CLP environment is also an issue addressed. The approach aims the implementation of genetic algorithm operators following the CLP paradigm.

Autonomous robot navigation using human spatial concepts

With the aim of automatically reasoning with spatial aspects in a cognitive way, several qualitative models have been developed in recent years. However, there is no model to reason with several spatial aspects in a uniform way. Moreover, most of these models simplify spatial objects to points. In this paper we present the use of constraint logic programming instantiated to finite domains extended with constraint handling rules as a tool for successfully integrating the qualitative concepts of orientation, distance, and cardinal directions, using points as well as extended objects as a primitive of reasoning. The resulting model has been applied to build a demonstrator: a qualitative navigation simulator on the structured environment of our city.

Constraint logic programming framework for integrated decision supports

Decision support systems provide decision-makers with an interactive environment for analyses of information with various models to help solve unstructured problems. Constraint logic programming as an improvement of logic programming can be used as a tool for the development of such decision support systems. Constraint logic programming is an integrated paradigm of logic modelling and mathematical programming. It has a modelling and analysis capacity for problems containing both qualitative and quantitative constraints; it has well-established declarative and procedural semantics, which reduce the model builder's burden to specify problem solving procedures as a part of a model. In this paper, we demonstrate the use of constraint logic programming as a potential decision support system tool, focusing on the model representation and analysis aspects.

Global Energy Minimization of Small Molecules Combining Constraint Logic Programming and Molecular Mechanics

The paper presents an approach to molecular energy minimization using Constraint Logic Programming (CLP) as a preprocessor to a molecular mechanics minimization program such as CHARMM. The use of CLP enables the definition of simple constraints that sufficiently describe relations in a molecule, thus limiting the search space of the globally optimal solution. The approach was used on the problem of minimizing the energy of the alanine dipeptide and N-methylalanylacetamide. An approximate 3-D structure produced by a CLP system was used as an initial structure for the CHARMM program that considers all relations in such a structure and performs energy optimization. With this initial structure, computed in about 1 min of CPU time, the optimal solution (global minimum) was found in only a few seconds, while calculating the same solution with CHARMM alone took 15 h. All calculations were performed on HP/735.

Transformations of CLP modules

We propose a transformation system for Constraint Logic Programming (CLP) aprograms and modules. The framework is inspired by the one of Tamaki and Sato (1984) for pure logic programs. However, the use of CLP allows us to introduce some new operations such as splitting and constraint replacement. We provide two sets of applicability conditions. The first one guarantees that the original and the transformed programs have the same computational behaviour, in terms of answer constraints. The second set contains more restrictive conditions that ensure compositionality: we prove that under these conditions the original and the transformed modules have the same answer constraints also when they are composed with other modules. This result is proved by first introducing a new formulation, in terms of trees, of a resultants semantics for CLP. As corollaries we obtain the correctness of both the modular and the nonmodular system w.r.t. the least model semantics.

Automatic test-generation for predicates [software testing

The authors propose a new technique for the automatic generation of test cases for predicates. Earlier, they proposed an efficient effective test generation strategy for Boolean expressions. They now extend this strategy to predicates. Their new strategy addresses several issues, including: analysis of dependencies between relational expressions in a predicate /spl Pscr/; generation of test constraints for /spl Pscr/ based on the detection of Boolean and relational operator faults in /spl Pscr/; and generation of actual tests according to the generated test constraints for /spl Pscr/. They propose: the use of constraint logic programming (CLP) to automate test-data generation for a predicate; and an incremental approach to apply CLP techniques to solve a constraint system. Since their technique is specification-based, it can facilitate generation of anticipated outputs for actual tests.