The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Fine-grained and accurate source code differencing
Open accessAbstract
At the heart of software evolution is a sequence of edit actions, called an edit script, made to a source code file. Since software systems are stored version by version, the edit script has to be computed from these versions, which is known as a complex task. Existing approaches usually compute edit scripts at the text granularity with only add line and delete line actions. However, inferring syntactic changes from such an edit script is hard. Since moving code is a frequent action performed when editing code, it should also be taken into account. In this paper, we tackle these issues by introducing an algorithm computing edit scripts at the abstract syntax tree granularity including move actions. Our objective is to compute edit scripts that are short and close to the original developer intent. Our algorithm is implemented in a freely-available and extensible tool that has been intensively validated.
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CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Lu, S., Guo, D., Ren, S., Huang, J., Svyatkovskiy, A., Blanco, A., Clement, C., Drain, D., Jiang, D., Tang, D., et al. (2021) · arXiv · doi:10.48550/arxiv.2102.04664 · Cited by 536
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 Large-Scale Empirical Study on Code-Comment Inconsistencies
Wen, F., Nagy, C., Bavota, G., & Lanza, M. (2019) · 2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc.2019.00019 · Cited by 105
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
- Falleri, J.-R., Morandat, F., Blanc, X., Martinez, M., & Monperrus, M.
- Venue
- Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering
- Publisher
- ACM
- Published
- 2014-09-15
- Pages
- 313-324
- OpenAlex
- W2065489029
- Cited by
- 549
- References
- 24
- FWCI
- 15.10
- Type
- conference paper
- Language
- en
- Open access
- green
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- Falleri, J.-R., Morandat, F., Blanc, X., Martinez, M., & Monperrus, M. (2014). Fine-grained and accurate source code differencing. Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering. https://doi.org/10.1145/2642937.2642982
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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