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Modeling Pairwise Test Generation from Cause-Effect Graphs as a Boolean Satisfiability Problem
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  • Journal title : International Journal of Contents
  • Volume 10, Issue 3,  2014, pp.41-46
  • Publisher : The Korea Contents Association
  • DOI : 10.5392/IJoC.2014.10.3.041
 Title & Authors
Modeling Pairwise Test Generation from Cause-Effect Graphs as a Boolean Satisfiability Problem
Chung, Insang;
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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.
Cause-Effect Graph;Pairwise Testing;Alloy;SAT problem;Requirements-based Testing;
 Cited by
An Optimal Solution for Test Case Generation Using ROBDD Graph and PSO Algorithm, Quality and Reliability Engineering International, 2015, 32, 7, 2263  crossref(new windwow)
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