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Modeling Pairwise Test Generation from Cause-Effect Graphs as a Boolean Satisfiability Problem
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  • Modeling Pairwise Test Generation from Cause-Effect Graphs as a Boolean Satisfiability Problem
  • Modeling Pairwise Test Generation from Cause-Effect Graphs as a Boolean Satisfiability Problem
저자명
Chung. Insang
간행물명
International journal of contents
권/호정보
2014년|10권 3호|pp.41-46 (6 pages)
발행정보
한국콘텐츠학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

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.