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Exploiting fault localisation for efficient program repair: 2020 Genetic and Evolutionary Computation Conference, GECCO 2020

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

Publication date8/07/2020
Number of pages2
<mark>Original language</mark>English
Event2020 Genetic and Evolutionary Computation Conference, GECCO 2020 - Cancun; Mexico, Cancun, Mexico
Duration: 8/07/202012/07/2020
Conference number: 161684


Conference2020 Genetic and Evolutionary Computation Conference, GECCO 2020


Search-based program repair generates variants of a defective program to find its repair. This could reduce the time and effort necessary for the manual software development and maintenance. However, applying even a limited set of mutations on a small piece of code (that repairs only trivial defects) generates a huge number of possible program variants (also called a search space). The reduction of the search space, while preserving the number and quality of repairs, would make these tools more efficient and practical. We present an end-to-end repair tool for Java programs. It localises lines of source code that introduced a defect into the history of the program's development and applies a set of mutations targeting only these lines. In the reduced search space, our tool repaired defects covered by failing tests in an open-source Java program. © 2020 Owner/Author.

Bibliographic note

Conference code: 161684 Export Date: 2 September 2020 References: Bowes, D., Counsell, S., Hall, T., Petric, J., Shippey, T., Getting defect prediction into industrial practice: The elff tool (2017) 2017 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), pp. 44-47. , https://doi.org/10.1109/ISSREW.2017.11; Brownlee, I.A.E., Petke, J., Alexander, B., Barr, E.T., Wagner, M., White, D.R., Gin: Genetic improvement research made easy (2019) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ' 19), pp. 985-993. , https://doi.org/10.1145/3321707.3321841, ACM, New York, NY, USA; Langdon, W., Veerapen, N., Ochoa, G., (2017) Visualising the Search Landscape of the Triangle Program, pp. 96-113. , https://doi.org/10.1007/978-3-319-55696-3-7; Mehne, B., Yoshida, H., Prasad, M.R., Sen, K., Gopinath, D., Khurshid, S., Accelerating search-based program repair (2018) 2018 IEEE 11th International Conference on Software Testing, Verification and Validation (ICST), pp. 227-238. , https://doi.org/10.1109/ICST.2018.00031; White, D.R., Gi in no time (2017) Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO ' 17), pp. 1549-1550. , https://doi.org/10.1145/3067695.3082515, ACM, New York, NY, USA