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An Investigation into the Use of Mutation Analysis for Automated Program Repair

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Book cover Search Based Software Engineering (SSBSE 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10452))

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Abstract

Research in Search-Based Automated Program Repair has demonstrated promising results, but has nevertheless been largely confined to small, single-edit patches using a limited set of mutation operators. Tackling a broader spectrum of bugs will require multiple edits and a larger set of operators, leading to a combinatorial explosion of the search space. This motivates the need for more efficient search techniques. We propose to use the test case results of candidate patches to localise suitable fix locations. We analysed the test suite results of single-edit patches, generated from a random walk across 28 bugs in 6 programs. Based on the findings of this analysis, we propose a number of mutation-based fault localisation techniques, which we subsequently evaluate by measuring how accurately they locate the statements at which the search was able to generate a solution. After demonstrating that these techniques fail to result in a significant improvement, we discuss why this may be the case, despite the successes of mutation-based fault localisation in previous studies.

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Notes

  1. 1.

    https://github.com/squaresLab/RepairBox.

  2. 2.

    Source code and a Docker image for the version of GenProg used by this study is publicly available at: https://bitbucket.org/ChrisTimperley/gp3.

  3. 3.

    Note, we do not measure how well these techniques localise the statement modified in the human repair, since the patterns observed in this data were used to design these techniques.

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Acknowledgements

This research was partially funded by AFRL (#FA8750-15-2-0075) and DARPA (#FA8750-16-2-0042), and an EPSRC DTG; the authors are grateful for their support. Any opinions, findings, or recommendations expressed are those of the authors and do not necessarily reflect those of the US Government. The authors additionally wish to thank the anonymous reviewers, whose comments were especially insightful and constructive.

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Authors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, USA

    Christopher Steven Timperley & Claire Le Goues

  2. University of York, York, UK

    Susan Stepney

Authors
  1. Christopher Steven Timperley
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  2. Susan Stepney
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  3. Claire Le Goues
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Corresponding author

Correspondence to Christopher Steven Timperley .

Editor information

Editors and Affiliations

  1. North Carolina State University, Morgantown, West Virginia, USA

    Tim Menzies

  2. Department of Computer Science, University College London, London, United Kingdom

    Justyna Petke

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Timperley, C.S., Stepney, S., Le Goues, C. (2017). An Investigation into the Use of Mutation Analysis for Automated Program Repair. In: Menzies, T., Petke, J. (eds) Search Based Software Engineering. SSBSE 2017. Lecture Notes in Computer Science(), vol 10452. Springer, Cham. https://doi.org/10.1007/978-3-319-66299-2_7

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  • DOI: https://doi.org/10.1007/978-3-319-66299-2_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66298-5

  • Online ISBN: 978-3-319-66299-2

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