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On the Accuracy of Spectrum-based Fault Localization
Open accessAbstract
Spectrum-based fault localization shortens the test- diagnose-repair cycle by reducing the debugging effort. As a light-weight automated diagnosis technique it can easily be integrated with existing testing schemes. However, as no model of the system is taken into account, its diagnostic accuracy is inherently limited. Using the Siemens Set benchmark, we investigate this diagnostic accuracy as a function of several parameters (such as quality and quantity of the program spectra collected during the execution of the system), some of which directly relate to test design. Our results indicate that the superior performance of a particular similarity coefficient, used to analyze the program spectra, is largely independent of test design. Furthermore, near- optimal diagnostic accuracy (exonerating about 80% of the blocks of code on average) is already obtained for low-quality error observations and limited numbers of test cases. The influence of the number of test cases is of primary importance for continuous (embedded) processing applications, where only limited observation horizons can be maintained.
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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
Self-citationAutomated Program Repair in the Era of Large Pre-trained Language Models
Xia, C. S., Wei, Y., & Zhang, L. (2023) · 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) · doi:10.1109/icse48619.2023.00129 · Cited by 433
Evaluating and Improving Fault Localization
Pearson, S., Campos, J., Just, R., Fraser, G., Abreu, R., Ernst, M. D., Pang, D., & Keller, B. (2017) · 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) · doi:10.1109/icse.2017.62 · Cited by 426
Self-citationA 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
- Abreu, R., Zoeteweij, P., & van Gemund, A. J. C.
- Venue
- Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (TAICPART-MUTATION 2007)
- Publisher
- IEEE
- Published
- 2007-09
- Pages
- 89-98
- OpenAlex
- W2153418968
- Cited by
- 736
- References
- 0
- FWCI
- 11.69
- Type
- conference paper
- Language
- en
- Open access
- green
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- Abreu, R., Zoeteweij, P., & van Gemund, A. J. C. (2007). On the Accuracy of Spectrum-based Fault Localization. Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (TAICPART-MUTATION 2007). https://doi.org/10.1109/taic.part.2007.13
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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