Skip to Main content Skip to Navigation
Conference papers

Empirical review of Java program repair tools: a large-scale experiment on 2,141 bugs and 23,551 repair attempts

Abstract : In the past decade, research on test-suite-based automatic program repair has grown significantly. Each year, new approaches and implementations are featured in major software engineering venues. However, most of those approaches are evaluated on a single benchmark of bugs, which are also rarely reproduced by other researchers. In this paper, we present a large-scale experiment using 11 Java test-suite-based repair tools and 2,141 bugs from 5 benchmarks. Our goal is to have a better understanding of the current state of automatic program repair tools on a large diversity of benchmarks. Our investigation is guided by the hypothesis that the repairability of repair tools might not be generalized across different benchmarks. We found that the 11 tools 1) are able to generate patches for 21% of the bugs from the 5 benchmarks, and 2) have better performance on Defects4J compared to other benchmarks, by generating patches for 47% of the bugs from Defects4J compared to 10-30% of bugs from the other benchmarks. Our experiment comprises 23,551 repair attempts, which we used to find causes of non-patch generation. These causes are reported in this paper, which can help repair tool designers to improve their approaches and tools.
Document type :
Conference papers
Complete list of metadata
Contributor : Mylène Delrue Connect in order to contact the contributor
Submitted on : Monday, April 25, 2022 - 11:14:54 AM
Last modification on : Wednesday, April 27, 2022 - 11:34:22 AM
Long-term archiving on: : Tuesday, July 26, 2022 - 6:51:31 PM


Files produced by the author(s)




Thomas Durieux, Fernanda Madeiral, Matias Martinez, Rui Abreu. Empirical review of Java program repair tools: a large-scale experiment on 2,141 bugs and 23,551 repair attempts. ESEC/FSE '19: 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Aug 2019, Tallinn, Estonia. pp.302-313, ⟨10.1145/3338906.3338911⟩. ⟨hal-03522732⟩



Record views


Files downloads