The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Bugs.jar: a large-scale, diverse dataset of real-world Java bugs
Abstract
We present Bugs.jar, a large-scale dataset for research in automated debugging, patching, and testing of Java programs. Bugs.jar is comprised of 1,158 bugs and patches, drawn from 8 large, popular open-source Java projects, spanning 8 diverse and prominent application categories. It is an order of magnitude larger than Defects4J, the only other dataset in its class. We discuss the methodology used for constructing Bugs.jar, the representation of the dataset, several use-cases, and an illustration of three of the use-cases through the application of 3 specific tools on Bugs.jar, namely our own tool, Elixir, and two third-party tools, Ekstazi and JaCoCo.
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Citations
Cites
Defects4J: a database of existing faults to enable controlled testing studies for Java programs
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
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×
“Research on automated debugging and patching of C programs has benefitted immensely from the several realistic datasets of C program bugs currently available, including ManyBugs [4], CoreBench [1], and IntroClass [4].”
Method
Cited by
Widyasari, R., Sim, S. Q., Lok, C., Qi, H., Phan, J., Tay, Q., Tan, C., Wee, F., Tan, J. E., Yieh, Y., et al. (2020) · Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3368089.3417943 · Cited by 150
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
(2020) · doi:10.1145/3379597.3387491 · Cited by 24
GitBug-Java: A Reproducible Benchmark of Recent Java Bugs
Silva, A., Saavedra, N., & Monperrus, M. (2024) · Proceedings of the 21st International Conference on Mining Software Repositories · doi:10.1145/3643991.3644884 · Cited by 23
Zhou, X., Weyssow, M., Widyasari, R., Zhang, T., He, J., Lyu, Y., Chang, J., Zhang, B., Huang, D., & Lo, D. (2025) · arXiv · doi:10.48550/arxiv.2502.06215 · Cited by 3
Self-citation
Metadata
- Authors
- Saha, R. K., Lyu, Y., Lam, W., Yoshida, H., & Prasad, M. R.
- Venue
- Proceedings of the 15th International Conference on Mining Software Repositories
- Publisher
- ACM
- Published
- 2018-05-28
- Pages
- 10-13
- OpenAlex
- W2883977877
- Cited by
- 168
- References
- 2
- FWCI
- 12.49
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Bugs.jar: a large-scale, diverse dataset of real-world Java bugs. https://app.cochat.ai/papers/10.1145/3196398.3196473
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- Saha, R. K., Lyu, Y., Lam, W., Yoshida, H., & Prasad, M. R. (2018). Bugs.jar: a large-scale, diverse dataset of real-world Java bugs. Proceedings of the 15th International Conference on Mining Software Repositories. https://doi.org/10.1145/3196398.3196473
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