Identifying Coincidental Correctness for Fault Localization by Clustering Test Cases

نویسندگان

  • Yi Miao
  • Zhenyu Chen
  • Sihan Li
  • Zhihong Zhao
  • Yuming Zhou
چکیده

Coverage-based fault localization techniques leverage coverage information to identify the faulty elements of a program. However, these techniques can be adversely affected by coincidental correctness, which occurs when faulty elements are executed but no failure is triggered. This paper proposes a clustering-based strategy to identify coincidental correctness. The key rationale behind this strategy is that test cases in the same cluster have similar behaviors. Therefore, a passed test case in a cluster, which contains failed test cases, is highly possible to be coincidental correctness. Our experimental results show that, by cleaning or relabeling these possibly coincidentally correct test cases, the effectiveness of coverage-based fault localization techniques can be effectively improved. Keywordscoincidental correctness; cluster analysis; fault localization

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تاریخ انتشار 2012