MutantDistiller: Using Symbolic Execution for Automatic Detection of Equivalent Mutants and Generation of Mutant Killing Tests

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)

Event location: Porto PT

ISBN: 978-1-7281-1076-9

URI: https://mutation-workshop.github.io/2020/

DOI: 10.1109/ICSTW50294.2020.00055

Abstract

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.

Authors with CRIS profile

Michael Baer Lehrstuhl für Informatik 2 (Programmiersysteme) Norbert Oster Lehrstuhl für Informatik 2 (Programmiersysteme) Michael Philippsen Lehrstuhl für Informatik 2 (Programmiersysteme)

Related research project(s)

Automatic Detection of Race-Conditions (AuDeRace) Jan. 1, 2016 - Sept. 30, 2021

How to cite

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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