Martinez, Matias;
Kechagia, Maria;
Perera, Anjana;
Petke, Justyna;
Sarro, Federica;
Aleti, Aldeida;
(2024)
Test-based Patch Clustering for Automatically-Generated
Patches Assessment.
Empirical Software Engineering
, 29
, Article 116. 10.1007/s10664-024-10503-2.
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Abstract
Previous studies have shown that Automated Program Repair (apr) techniques suffer from the overfitting problem. Overfitting happens when a patch is run and the test suite does not reveal any error, but the patch actually does not fix the underlying bug or it introduces a new defect that is not covered by the test suite. Therefore, the patches generated by apr tools need to be validated by human programmers, which can be very costly, and prevents apr tool adoption in practice. Our work aims to minimize the number of plausible patches that programmers have to review, thereby reducing the time required to find a correct patch. We introduce a novel light-weight test-based patch clustering approach called xTestCluster, which clusters patches based on their dynamic behavior. xTestCluster is applied after the patch generation phase in order to analyze the generated patches from one or more repair tools and to provide more information about those patches for facilitating patch assessment. The novelty of xTestCluster lies in using information from execution of newly generated test cases to cluster patches generated by multiple APR approaches. A cluster is formed of patches that fail on the same generated test cases. The output from xTestCluster gives developers a) a way of reducing the number of patches to analyze, as they can focus on analyzing a sample of patches from each cluster, b) additional information (new test cases and their results) attached to each patch. After analyzing 902 plausible patches from 21 Java apr tools, our results show that xTestCluster is able to reduce the number of patches to review and analyze with a median of 50%. xTestCluster can save a significant amount of time for developers that have to review the multitude of patches generated by apr tools, and provides them with new test cases that expose the differences in behavior between generated patches. Moreover, xTestCluster can complement other patch assessment techniques that help detect patch misclassifications.
| Type: | Article |
|---|---|
| Title: | Test-based Patch Clustering for Automatically-Generated Patches Assessment |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s10664-024-10503-2 |
| Publisher version: | https://doi.org/10.1007/s10664-024-10503-2 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Automated program repair, Patch assessment, Patch overfitting, Test case generation, Java |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10192373 |
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