The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Automatic inference of code transforms for patch generation
Open accessAbstract
We present a new system, Genesis, that processes human patches to automatically infer code transforms for automatic patch generation. We present results that characterize the effectiveness of the Genesis inference algorithms and the complete Genesis patch generation system working with real-world patches and defects collected from 372 Java projects. To the best of our knowledge, Genesis is the first system to automatically infer patch generation transforms or candidate patch search spaces from previous successful patches.
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Citations
Cites
Code completion with statistical language models
Raychev, V., Vechev, M., & Yahav, E. (2014) · Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation · doi:10.1145/2594291.2594321 · Cited by 555
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
Self-citation
Cited by
Le Goues, C., Pradel, M., & Roychoudhury, A. (2019) · Communications of the ACM · doi:10.1145/3318162 · Cited by 410
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
A critical review on the evaluation of automated program repair systems
Liu, K., Li, L., Koyuncu, A., Kim, D., Liu, Z., Klein, J., & Bissyandé, T. F. (2021) · Journal of Systems and Software · doi:10.1016/j.jss.2020.110817 · Cited by 79
Metadata
- Authors
- Long, F., Amidon, P., & Rinard, M.
- Venue
- Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering
- Publisher
- ACM
- Published
- 2017-08-21
- Pages
- 727-739
- OpenAlex
- W2740130372
- Cited by
- 175
- References
- 2
- FWCI
- 17.37
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Long, F., Amidon, P., & Rinard, M. (2017). Automatic inference of code transforms for patch generation. Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering. https://doi.org/10.1145/3106237.3106253
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