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

Nowack, V. and Bowes, D. and Counsell, S. and Hall, T. and Haraldsson, S. and Winter, E. and Woodward, J. and SIGEVO, ACM (2020) Exploiting fault localisation for efficient program repair:2020 Genetic and Evolutionary Computation Conference, GECCO 2020. In: 2020 Genetic and Evolutionary Computation Conference, GECCO 2020, 2020-07-082020-07-12, Cancun; Mexico.

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Abstract

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.

Item Type:
Contribution to Conference (Paper)
Journal or Publication Title:
2020 Genetic and Evolutionary Computation Conference, GECCO 2020
Additional Information:
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
Subjects:
ID Code:
147021
Deposited By:
Deposited On:
09 Jun 2021 19:20
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jun 2021 12:39