Baer M, Oster N, Philippsen M (2020)
Publication Language: English
Publication Status: Accepted
Publication Type: Conference contribution, Original article
Future Publication Type: Conference contribution
Publication year: 2020
Publisher: IEEE Xplore
Pages Range: 294-303
Conference Proceedings Title: 2020 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)
ISBN: 978-1-7281-1076-9
URI: https://mutation-workshop.github.io/2020/
DOI: 10.1109/ICSTW50294.2020.00055
Mutation testing can be used to measure the quality of a given test suite. However, it has two flaws that prevent it from being widely used. First, there are equivalent mutants - mutants that are semantically equivalent to the unmodified version and therefore unkillable. Manually identifying those mutants is time-consuming and error-prone. Second, initially there are often too few test cases. Mutation testing detects missing cases. But for productive use it is too time-consuming to manually write all the required test cases.
This paper shows how to use symbolic execution to tackle both problems, i.e., to detect equivalent mutants and exclude them from further analysis, and to automatically generate test cases that kill the remaining mutants.
Our evaluation uses a set of 252 publicly available mutants for which it is known that they are hard to classify. Despite the fact that detecting equivalent mutants is an undecidable problem, our fully automatic tool MutantDistiller correctly classifies all of them (13 equivalent, 239 non-equivalent). MutantDistiller also generates test cases that kill the non-equivalent mutants.
APA:
Baer, M., Oster, N., & Philippsen, M. (2020). MutantDistiller: Using Symbolic Execution for Automatic Detection of Equivalent Mutants and Generation of Mutant Killing Tests. In 2020 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) (pp. 294-303). Porto, PT: IEEE Xplore.
MLA:
Baer, Michael, Norbert Oster, and Michael Philippsen. "MutantDistiller: Using Symbolic Execution for Automatic Detection of Equivalent Mutants and Generation of Mutant Killing Tests." Proceedings of the 15th International Workshop on Mutation Analysis (Mutation 2020), Porto IEEE Xplore, 2020. 294-303.
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