CLPS–B – A constraint solver to animate a B specification

Bouquet, Fabrice; Legeard, Bruno; Peureux, Fabien

doi:10.1007/s10009-003-0123-8

Cited by 31 publications

(25 citation statements)

References 23 publications

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“…-to integrate the solver into BZTT like it was already done for the existing solver CLPS-B [4]; -to apply the solver as part of the BZTT to validation and verification of real-sized software with sequences.…”

Section: Discussionmentioning

confidence: 99%

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Constraint Solving for Sequences in Software Validation and Verification

Kosmatov

2006

Lecture Notes in Computer Science

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Abstract. Constraint programming techniques are successfully used in various areas of software engineering for industry, commerce, transport, finance etc. Constraint solvers for different data types are applied in validation and verification of programs containing data elements of these types. A general constraint solver for sequences is necessary to take into account this data type in the existing validation and verification tools. In this work, we present an original constraint solver for sequences implemented in CHR and based on T. Frühwirth's solver for lists with the propagation of two constraints: generalized concatenation and size. Experimental results show its better efficiency compared to the intuitive propagation algorithm based on subsequences. The applications of the solver (with the validation and verification tool BZTT) to different software engineering problems are illustrated by the example of a waiting room model.

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Section: Discussionmentioning

confidence: 99%

“…For example, the tool BZTT [5] uses the solver CLPS-B [4] and allows the animation and test generation for formal models containing integers, sets, functions and relations. BZTT was used to validate and verify software in different industrial projects for industry, transport, commerce and finance [4] (see also references in [4]), e.g.…”

Section: Introductionmentioning

confidence: 99%

Constraint Solving for Sequences in Software Validation and Verification

Kosmatov

2006

Lecture Notes in Computer Science

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“…Considering path [1,2,4,5,4,6,7]. We start with an initial state: x = X 1 , y = Y 1 , with associated constraints X 1 ∈ −32768..32767, Y 1 ∈ −32768..32767.…”

Section: Expressing Methods Code With Graphsmentioning

confidence: 99%

“…The evaluation of Java/JML programs is based on the constraint logic programming technology called CLPS-BZ [6]. CLPS-BZ is a constraint solver implemented in SICStus Prolog [7], and originally designed to evaluate and to generate functional test cases from B and Z formal models [9].…”

Section: A Using Constraint Solving To Evaluate Java/jml Programsmentioning

confidence: 99%

“…We propose here to reinvest constraint solving techniques that have been originally designed for the symbolic animation of B machines [6], in order to provide a flexible and expressive means for both verifying and validating a Java program annotated with JML constructs. This technique is based on a graph representation of the program structure/code.…”

Section: Introductionmentioning

confidence: 99%

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Grey-Box Testing and Verification of Java/JML

Dadeau

Peureux²

2011

2011 IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops

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International audienceWe present in this paper the application of constraint solving techniques to the validation and automated test cases generation for Java programs, annotated with JML specifications. The Java/JML code is translated into a constraint representation based on a subset of the set-theory, which is well-suited for modelling object-oriented programs. Symbolic code execution techniques can then be applied to produce test cases, using classical structural test selection criteria, or to detect possible runtime errors, and non-conformances between the Java code and its embedded JML model

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Scenario‐based testing using symbolic animation of B models

Dadeau

Castillos

Tissot

2012

Software Testing Verif & Rel

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SUMMARY This article presents a model‐based test generation technique, from user‐defined scenarios, for behavioral models expressed as B machines. Scenarios are expressed using a customized formalism, based on regular expressions, that makes it possible to describe sequences of operation calls possibly reaching specific states of the system. A symbolic animation engine, simulating the execution of a model using constraint logic programming, is then exploited to play the unfolded scenarios on the model and to instantiate the test cases, providing the expected results used to establish the conformance verdict. This approach is tool supported by a research prototype and has been successfully applied in an industrial context of a smart card applet. This tool is extended by a scenario generator, which automatically generates testing strategies for exercising user‐defined properties, written using specific patterns. Copyright © 2012 John Wiley & Sons, Ltd.

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CLPS–B – A constraint solver to animate a B specification

Cited by 31 publications

References 23 publications

Constraint Solving for Sequences in Software Validation and Verification

Constraint Solving for Sequences in Software Validation and Verification

Grey-Box Testing and Verification of Java/JML

Scenario‐based testing using symbolic animation of B models

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