A critical review on the evaluation of automated program repair systems
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The problem of weak test suites has been well studied in test-based automatic program repair.
“The problem of weak test suites has been well studied in the area of test-based automatic program repair (APR) [37, 40, 46, 50].”
From Are “Solved Issues” in SWE-bench Really Solved Correctly? An Empirical Study (2026) · cites this paper as [37]
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Just, R., Jalali, D., & Ernst, M. D. (2014) · Proceedings of the 2014 International Symposium on Software Testing and Analysis · doi:10.1145/2610384.2628055 · Cited by 1,447 · see citing works
Shaping program repair space with existing patches and similar code
Jiang, J., Xiong, Y., Zhang, H., Gao, Q., & Chen, X. (2018) · Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis · doi:10.1145/3213846.3213871 · Cited by 329 · see citing works
The ManyBugs and IntroClass benchmarks for automated repair of C programs
Le Goues, C., Holtschulte, N., Smith, E. K., Brun, Y., Devanbu, P., Forrest, S., & Weimer, W. (2015) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2015.2454513 · Cited by 326 · cited 1× · see citing works
“…APR research has been initiated a decade ago, the current benchmarks have been proposed mid-way: Defects4J (Just et al., 2014), the widely used benchmark for Java bugs was released in 2014, while IntroClass and ManyBugs benchmarks (Le Goues et al., 2015) for C program bugs were published in 2015.”
MethodIs the cure worse than the disease? overfitting in automated program repair
Smith, E. K., Barr, E. T., Le Goues, C., & Brun, Y. (2015) · Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering · doi:10.1145/2786805.2786825 · Cited by 323 · see citing works
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The future of AI-driven software engineering
Terragni, V., Vella, A., Roop, P., & Blincoe, K. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3715003 · Cited by 62 · see citing works
Are “Solved Issues” in SWE-bench Really Solved Correctly? An Empirical Study
Wang, Y., Pradel, M., & Liu, Z. (2026) · Proceedings of the 2026 IEEE/ACM 48th International Conference on Software Engineering · doi:10.1145/3744916.3764576 · Cited by 3 · see citing works
“We first find that the validation process of SWE-bench overlooks non-modified test files, which leads to significant performance overestimation.”
Self-citation
- Authors
- Liu, K., Li, L., Koyuncu, A., Kim, D., Liu, Z., Klein, J., & Bissyandé, T. F.
- Affiliations
- Nanjing University of Aeronautics and Astronautics (CN)
- Monash University (AU)
- University of Luxembourg (LU)
- Kyungpook National University (KR)
- Corresponding author
- Li, Li
- Kim, Dongsun
- Venue
- Journal of Systems and Software
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 171
- Pages
- 110817
- ISSN
- 0164-1212 (ISSN-L)
- OpenAlex
- W3084918652
- Cited by
- 79
- References
- 5
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 20 · 2023: 11 · 2022: 21 · 2021: 11 · 2020: 1
- FWCI
- 19.12
- Type
- journal article
- Language
- en
- Open access
- green
- orbilu.uni.lu
- Licence
- Locations
- Journal of Systems and Software (publishedVersion)
- Open Repository and Bibliography (University of Luxembourg) (submittedVersion, cc-by-nc-sa)
- Funders
- Monash University
- Topics
- Physical Sciences › Computer Science › Software › Software Testing and Debugging Techniques
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Software Engineering Methodologies
- Keywords
- automated program repair, evaluation metrics, patch generation, overfitting, evaluation bias, benchmarking
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