Search-Based Fault Localization
Many spectrum-based fault localization measures have been proposed in the literature. However, no single fault localization measure completely outperforms others: a measure which is more accurate in localizing some bugs in some programs is less accurate in localizing other bugs in other programs. Th...
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| Main Authors: | , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2011
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/1391 https://ink.library.smu.edu.sg/context/sis_research/article/2390/viewcontent/ase11faultsearch.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Many spectrum-based fault localization measures have been proposed in the literature. However, no single fault localization measure completely outperforms others: a measure which is more accurate in localizing some bugs in some programs is less accurate in localizing other bugs in other programs. This paper proposes to compose existing spectrum-based fault localization measures into an improved measure. We model the composition of various measures as an optimization problem and present a search-based approach to explore the space of many possible compositions and output a heuristically near optimal composite measure. We employ two search-based strategies including genetic algorithm and simulated annealing to look for optimal solutions and compare the effectiveness of the resulting composite measures on benchmark software systems. Compared to individual spectrum-based fault localization techniques, our composite measures perform statistically significantly better. |
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