Trust enhancement issues in program repair
| Autor: | Yannic Noller, Ridwan Shariffdeen, Xiang Gao, Abhik Roychoudhury |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Proceedings of the 44th International Conference on Software Engineering. |
| Popis: | Automated program repair is an emerging technology that seeks to automatically rectify bugs and vulnerabilities using learning, search, and semantic analysis. Trust in automatically generated patches is necessary for achieving greater adoption of program repair. Towards this goal, we survey more than 100 software practitioners to understand the artifacts and setups needed to enhance trust in automatically generated patches. Based on the feedback from the survey on developer preferences, we quantitatively evaluate existing test-suite based program repair tools. We find that they cannot produce high-quality patches within a top-10 ranking and an acceptable time period of 1 hour. The developer feedback from our qualitative study and the observations from our quantitative examination of existing repair tools point to actionable insights to drive program repair research. Specifically, we note that producing repairs within an acceptable time-bound is very much dependent on leveraging an abstract search space representation of a rich enough search space. Moreover, while additional developer inputs are valuable for generating or ranking patches, developers do not seem to be interested in a significant human-in-the-loop interaction. Comment: To appear in 44th International Conference on Software Engineering (ICSE) 2022. The first two authors contributed equally and are joint "first authors" |
| Databáze: | OpenAIRE |
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