CFaults: Model-Based Diagnosis for Fault Localization in C Programs with Multiple Test Cases
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866916935002750976 |
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| author | Orvalho, Pedro Janota, Mikoláš Manquinho, Vasco |
| author_facet | Orvalho, Pedro Janota, Mikoláš Manquinho, Vasco |
| contents | Debugging is one of the most time-consuming and expensive tasks in software development. Several formula-based fault localization (FBFL) methods have been proposed, but they fail to guarantee a set of diagnoses across all failing tests or may produce redundant diagnoses that are not subset-minimal, particularly for programs with multiple faults.
This paper introduces a novel fault localization approach for C programs with multiple faults. CFaults leverages Model-Based Diagnosis (MBD) with multiple observations and aggregates all failing test cases into a unified MaxSAT formula. Consequently, our method guarantees consistency across observations and simplifies the fault localization procedure. Experimental results on two benchmark sets of C programs, TCAS and C-Pack-IPAs, show that CFaults is faster than other FBFL approaches like BugAssist and SNIPER. Moreover, CFaults only generates subset-minimal diagnoses of faulty statements, whereas the other approaches tend to enumerate redundant diagnoses. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_09337 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | CFaults: Model-Based Diagnosis for Fault Localization in C Programs with Multiple Test Cases Orvalho, Pedro Janota, Mikoláš Manquinho, Vasco Software Engineering Artificial Intelligence Logic in Computer Science Debugging is one of the most time-consuming and expensive tasks in software development. Several formula-based fault localization (FBFL) methods have been proposed, but they fail to guarantee a set of diagnoses across all failing tests or may produce redundant diagnoses that are not subset-minimal, particularly for programs with multiple faults. This paper introduces a novel fault localization approach for C programs with multiple faults. CFaults leverages Model-Based Diagnosis (MBD) with multiple observations and aggregates all failing test cases into a unified MaxSAT formula. Consequently, our method guarantees consistency across observations and simplifies the fault localization procedure. Experimental results on two benchmark sets of C programs, TCAS and C-Pack-IPAs, show that CFaults is faster than other FBFL approaches like BugAssist and SNIPER. Moreover, CFaults only generates subset-minimal diagnoses of faulty statements, whereas the other approaches tend to enumerate redundant diagnoses. |
| title | CFaults: Model-Based Diagnosis for Fault Localization in C Programs with Multiple Test Cases |
| topic | Software Engineering Artificial Intelligence Logic in Computer Science |
| url | https://arxiv.org/abs/2407.09337 |