The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Boa: A language and infrastructure for analyzing ultra-large-scale software repositories
Abstract
In today's software-centric world, ultra-large-scale software repositories, e.g. SourceForge (350,000+ projects), GitHub (250,000+ projects), and Google Code (250,000+ projects) are the new library of Alexandria. They contain an enormous corpus of software and information about software. Scientists and engineers alike are interested in analyzing this wealth of information both for curiosity as well as for testing important hypotheses. However, systematic extraction of relevant data from these repositories and analysis of such data for testing hypotheses is hard, and best left for mining software repository (MSR) experts! The goal of Boa, a domain-specific language and infrastructure described here, is to ease testing MSR-related hypotheses. We have implemented Boa and provide a web-based interface to Boa's infrastructure. Our evaluation demonstrates that Boa substantially reduces programming efforts, thus lowering the barrier to entry. We also see drastic improvements in scalability. Last but not least, reproducing an experiment conducted using Boa is just a matter of re-running small Boa programs provided by previous researchers.
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Cites
Awareness and coordination in shared workspaces
Dourish, P., & Bellotti, V. (1992) · Proceedings of the 1992 ACM conference on Computer-supported cooperative work - CSCW '92 · doi:10.1145/143457.143468 · Cited by 2,550 · cited 1×
“Scientists and engineers alike are interested in analyzing this wealth of information both for curiosity as well as for testing such important hypotheses as: “how people perceive and consider the potential impacts of their own and others’ edits as they write together?”
Background
Cited by
ATOM: Commit Message Generation Based on Abstract Syntax Tree and Hybrid Ranking
Liu, S., Gao, C., Chen, S., Nie, L. Y., & Liu, Y. (2022) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2020.3038681 · Cited by 93
CCT5: A Code-Change-Oriented Pre-trained Model
Lin, B., Wang, S., Liu, Z., Liu, Y., Xia, X., & Mao, X. (2023) · Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3611643.3616339 · Cited by 69
FIRA: fi ne-grained g ra ph-based code change representation for automated commit message generation
Dong, J., Lou, Y., Zhu, Q., Sun, Z., Li, Z., Zhang, W., & Hao, D. (2022) · Proceedings of the 44th International Conference on Software Engineering · doi:10.1145/3510003.3510069 · Cited by 61
Ma, Y., Dey, T., Bogart, C., Amreen, S., Valiev, M., Tutko, A., Kennard, D., Zaretzki, R., & Mockus, A. (2021) · Empirical Software Engineering · doi:10.1007/s10664-020-09905-9 · Cited by 49
RACE: Retrieval-augmented Commit Message Generation
Shi, E., Wang, Y., Tao, W., Du, L., Zhang, H., Han, S., Zhang, D., & Sun, H. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2022.emnlp-main.372 · Cited by 42
Metadata
- Authors
- Dyer, R., Nguyen, H. A., Rajan, H., & Nguyen, T. N.
- Venue
- 2013 35th International Conference on Software Engineering (ICSE)
- Publisher
- IEEE
- Published
- 2013-05
- Pages
- 422-431
- ISSN
- 0270-5257 (ISSN-L)
- OpenAlex
- W4232691406
- Cited by
- 255
- References
- 1
- FWCI
- 11.57
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Dyer, R., Nguyen, H. A., Rajan, H., & Nguyen, T. N. (2013). Boa: A language and infrastructure for analyzing ultra-large-scale software repositories. 2013 35th International Conference on Software Engineering (ICSE). https://doi.org/10.1109/icse.2013.6606588
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