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An Evaluation of Similarity Coefficients for Software Fault Localization
Abstract
Automated diagnosis of software faults can improve the efficiency of the debugging process, and is therefore an important technique for the development of dependable software. In this paper we study different similarity coefficients that are applied in the context of a program spectral approach to software fault localization (single programming mistakes). The coefficients studied are taken from the systems diagnosis/automated debugging tools Pinpoint, Tarantula, and AMPLE, and from the molecular biology domain (the Ochiai coefficient). We evaluate these coefficients on the Siemens Suite of benchmark faults, and assess their effectiveness in terms of the position of the actual fault in the probability ranking of fault candidates produced by the diagnosis technique. Our experiments indicate that the Ochiai coefficient consistently outperforms the coefficients currently used by the tools mentioned. In terms of the amount of code that needs to be inspected, this coefficient improves 5% on average over the next best technique, and up to 30% in specific cases
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Cited by
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Self-citationA model for spectra-based software diagnosis
Naish, L., Lee, H. J., & Ramamohanarao, K. (2011) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/2000791.2000795 · Cited by 536
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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
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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
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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
Zhou, X., Peng, X., Xie, T., Sun, J., Ji, C., Liu, D., Xiang, Q., & He, C. (2019) · Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3338906.3338961 · Cited by 277
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Lou, Y., Zhu, Q., Dong, J., Li, X., Sun, Z., Hao, D., Zhang, L., & Zhang, L. (2021) · Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3468264.3468580 · Cited by 163
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Yang, A. Z. H., Le Goues, C., Martins, R., & Hellendoorn, V. (2024) · Proceedings of the IEEE/ACM 46th International Conference on Software Engineering · doi:10.1145/3597503.3623342 · Cited by 144
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Ye, Z., Chen, P., & Yu, G. (2021) · 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid) · doi:10.1109/ccgrid51090.2021.00051 · Cited by 19
A Trace-Log-Clusterings-Based Fault Localization Approach to Microservice Systems
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Metadata
- Authors
- Abreu, R., Zoeteweij, P., & Van Gemund, A.
- Venue
- 2006 12th Pacific Rim International Symposium on Dependable Computing (PRDC'06)
- Publisher
- IEEE
- Published
- 2006
- Pages
- 39-46
- OpenAlex
- W2128049346
- Cited by
- 563
- References
- 0
- FWCI
- 2.82
- Type
- conference paper
- Language
- en
- Open access
- closed
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