The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Angelix: scalable multiline program patch synthesis via symbolic analysis
Abstract
Since debugging is a time-consuming activity, automated program repair tools such as GenProg have garnered interest. A recent study revealed that the majority of GenProg repairs avoid bugs simply by deleting functionality. We found that SPR, a state-of-the-art repair tool proposed in 2015, still deletes functionality in their many "plausible" repairs. Unlike generate-and-validate systems such as GenProg and SPR, semantic analysis based repair techniques synthesize a repair based on semantic information of the program. While such semantics-based repair methods show promise in terms of quality of generated repairs, their scalability has been a concern so far. In this paper, we present Angelix, a novel semantics-based repair method that scales up to programs of similar size as are handled by search-based repair tools such as GenProg and SPR. This shows that Angelix is more scalable than previously proposed semantics based repair methods such as SemFix and DirectFix. Furthermore, our repair method can repair multiple buggy locations that are dependent on each other. Such repairs are hard to achieve using SPR and GenProg. In our experiments, Angelix generated repairs from large-scale real-world software such as wireshark and php, and these generated repairs include multi-location repairs. We also report our experience in automatically repairing the well-known Heartbleed vulnerability.
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Cites
An analysis of patch plausibility and correctness for generate-and-validate patch generation systems
Qi, Z., Long, F., Achour, S., & Rinard, M. (2015) · Proceedings of the 2015 International Symposium on Software Testing and Analysis · doi:10.1145/2771783.2771791 · Cited by 420
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×
“However, we note that the GenProg benchmark we used for our experiments is one of the most extensive one available in the literature (the Many-Bugs benchmark [15] has also been released very recently as an extension of the GenProg benchmark).”
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
Cited by
Automated Program Repair in the Era of Large Pre-trained Language Models
Xia, C. S., Wei, Y., & Zhang, L. (2023) · 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) · doi:10.1109/icse48619.2023.00129 · Cited by 433
Le Goues, C., Pradel, M., & Roychoudhury, A. (2019) · Communications of the ACM · doi:10.1145/3318162 · Cited by 410
Self-citationSEQUENCER: Sequence-to-Sequence Learning for End-to-End Program Repair
Chen, Z., Kommrusch, S. J., Tufano, M., Pouchet, L.-N., Poshyvanyk, D., & Monperrus, M. (2021) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2019.2940179 · Cited by 396
An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation
Tufano, M., Watson, C., Bavota, G., Penta, M. D., White, M., & Poshyvanyk, D. (2019) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3340544 · Cited by 370
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
Metadata
- Authors
- Mechtaev, S., Yi, J., & Roychoudhury, A.
- Venue
- Proceedings of the 38th International Conference on Software Engineering
- Publisher
- ACM
- Published
- 2016-05-14
- Pages
- 691-701
- ISSN
- 0270-5257 (ISSN-L)
- OpenAlex
- W2373227884
- Cited by
- 515
- References
- 3
- FWCI
- 47.53
- Type
- conference paper
- Language
- en
- Open access
- closed
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