The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Towards more accurate retrieval of duplicate bug reports
Open accessAbstract
In a bug tracking system, different testers or users may submit multiple reports on the same bugs, referred to as duplicates, which may cost extra maintenance efforts in triaging and fixing bugs. In order to identify such duplicates accurately, in this paper we propose a retrieval function (REP) to measure the similarity between two bug reports. It fully utilizes the information available in a bug report including not only the similarity of textual content in summary and description fields, but also similarity of non-textual fields such as product, component, version, etc. For more accurate measurement of textual similarity, we extend BM25F - an effective similarity formula in information retrieval community, specially for duplicate report retrieval. Lastly we use a two-round stochastic gradient descent to automatically optimize REP for specific bug repositories in a supervised learning manner. We have validated our technique on three large software bug repositories from Mozilla, Eclipse and OpenOffice. The experiments show 10-27% relative improvement in recall rate@k and 17-23% relative improvement in mean average precision over our previous model. We also applied our technique to a very large dataset consisting of 209,058 reports from Eclipse, resulting in a recall rate@k of 37-71% and mean average precision of 47%.
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Cites
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Manning, C. D., Raghavan, P., & Schütze, H. (2008) · doi:10.1017/cbo9780511809071 · Cited by 11,288
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Simple BM25 extension to multiple weighted fields
Robertson, S., Zaragoza, H., & Taylor, M. (2004) · Proceedings of the thirteenth ACM international conference on Information and knowledge management · doi:10.1145/1031171.1031181 · Cited by 701
Bettenburg, N., Just, S., Schröter, A., Weiss, C., Premraj, R., & Zimmermann, T. (2008) · Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering · doi:10.1145/1453101.1453146 · Cited by 617
An approach to detecting duplicate bug reports using natural language and execution information
Wang, X., Zhang, L., Xie, T., Anvik, J., & Sun, J. (2008) · Proceedings of the 13th international conference on Software engineering - ICSE '08 · doi:10.1145/1368088.1368151 · Cited by 539
Detection of Duplicate Defect Reports Using Natural Language Processing
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A discriminative model approach for accurate duplicate bug report retrieval
Sun, C., Lo, D., Wang, X., Jiang, J., & Khoo, S.-C. (2010) · Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1 · doi:10.1145/1806799.1806811 · Cited by 336
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Chen, Y., Yang, X., Dong, H., He, X., Zhang, H., Lin, Q., Chen, J., Zhao, P., Kang, Y., Gao, F., et al. (2020) · Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3368089.3409768 · Cited by 47
Metadata
- Authors
- Sun, C., Lo, D., Khoo, S.-C., & Jiang, J.
- Venue
- 2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011)
- Publisher
- IEEE
- Published
- 2011-11
- Pages
- 253-262
- OpenAlex
- W2167630669
- Cited by
- 334
- References
- 20
- FWCI
- 13.94
- Type
- conference paper
- Language
- en
- Open access
- green
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- Sun, C., Lo, D., Khoo, S.-C., & Jiang, J. (2011). Towards more accurate retrieval of duplicate bug reports. 2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011). https://doi.org/10.1109/ase.2011.6100061
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