Modeling Pairwise Test Generation from Cause-Effect Graphs as a Boolean Satisfiability Problem

A cause-effect graph considers only the desired external behavior of a system by identifying input-output parameter relationships in the specification. When testing a software system with cause-effect graphs, it is important to derive a moderate number of tests while avoiding loss in fault detection...

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Veröffentlicht in:International JOURNAL OF CONTENTS 2014, 10(3), , pp.41-46
1. Verfasser: Chung, Insang
Format: Artikel
Sprache:eng
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Zusammenfassung:A cause-effect graph considers only the desired external behavior of a system by identifying input-output parameter relationships in the specification. When testing a software system with cause-effect graphs, it is important to derive a moderate number of tests while avoiding loss in fault detection ability. Pairwise testing is known to be effective in determining errors while considering only a small portion of the input space. In this paper, we present a new testing technique that generates pairwise tests from a cause-effect graph. We use a Boolean Satisbiability (SAT) solver to generate pairwise tests from a cause-effect graph. The Alloy language is used for encoding the cause-effect graphs and its SAT solver is applied to generate the pairwise tests. Using a SAT solver allows us to effectively manage constraints over the input parameters and facilitates the generation of pairwise tests, even in the situations where other techniques fail to satisfy full pairwise coverage. KCI Citation Count: 0
ISSN:1738-6764
2093-7504
DOI:10.5392/IJoC.2014.10.3.041