The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Scalable statistical bug isolation
Abstract
We present a statistical debugging algorithm that isolates bugs in programs containing multiple undiagnosed bugs. Earlier statistical algorithms that focus solely on identifying predictors that correlate with program failure perform poorly when there are multiple bugs. Our new technique separates the effects of different bugs and identifies predictors that are associated with individual bugs. These predictors reveal both the circumstances under which bugs occur as well as the frequencies of failure modes, making it easier to prioritize debugging efforts. Our algorithm is validated using several case studies, including examples in which the algorithm identified previously unknown, significant crashing bugs in widely used systems.
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Citations
Cites
Schleimer, S., S, W. D., & Aiken, A. (2003) · Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data · doi:10.1145/872757.872770 · Cited by 1,099
Self-citation
Cited by
A Survey on Software Fault Localization
Wong, W. E., Gao, R., Li, Y., Abreu, R., & Wotawa, F. (2016) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2016.2521368 · Cited by 1,110
Zhou, X., Peng, X., Xie, T., Sun, J., Ji, C., Li, W., & Ding, D. (2021) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2018.2887384 · Cited by 410
SOBER: statistical model-based bug localization
Liu, C., Yan, X., Fei, L., Han, J., & Midkiff, S. P. (2005) · Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering · doi:10.1145/1081706.1081753 · Cited by 357
A theoretical analysis of the risk evaluation formulas for spectrum-based fault localization
Xie, X., Chen, T. Y., Kuo, F.-C., & Xu, B. (2013) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/2522920.2522924 · Cited by 353
DeepFL: integrating multiple fault diagnosis dimensions for deep fault localization
Li, X., Li, W., Zhang, Y., & Zhang, L. (2019) · Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis · doi:10.1145/3293882.3330574 · Cited by 336
Metadata
- Authors
- Liblit, B., Naik, M., Zheng, A. X., Aiken, A., & Jordan, M. I.
- Venue
- ACM SIGPLAN Notices
- Published
- 2005-06-12
- Volume
- 40
- Issue
- 6
- Pages
- 15-26
- ISSN
- 0362-1340 (ISSN-L)
- 1558-1160
- OpenAlex
- W2162376048
- Cited by
- 729
- References
- 1
- FWCI
- 109.06
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liblit, B., Naik, M., Zheng, A. X., Aiken, A., & Jordan, M. I. (2005). Scalable statistical bug isolation. ACM SIGPLAN Notices. https://doi.org/10.1145/1064978.1065014
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
