Systematically Generated Formulas for Spectrum -Based Fault Localization
2023 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)(2023)
摘要
The basic element in Spectrum-Based Fault Localization (SBFL) are the risk evaluation formulas, which calculate a suspiciousness score for each program element based on test coverage and test case outcome information. This score can be used in debugging to identify the faulty element more efficiently. A large number of manually crafted formulas have been proposed, but a line of research tries to generate formulas (semi-)automatically. Some of these approaches are based on heuristic search (e.g., genetic algorithms), and researchers started only recently examining systematic ways to generate all possible formulas corresponding to a particular class of formula structures. In a recent work, we explored a very simple formula template as a proof of concept but this research failed to find a new formula that outperformed already published ones. In this paper, we take a next step and investigate a class of formula templates that are more elaborate but still feasible to explore fully for generating new formulas. Many of the generated formulas cover some well-known existing ones, but we were also able to find two new ones that are superior to the majority of the previously published formulas (evaluated on the Defects4J dataset) and are not present in literature.
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关键词
Terms Spectrum-Based Fault Localization,debugging,suspiciousness score formulas,systematic search
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