FauxPy: A Fault Localization Tool for Python
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929330120032256 |
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| author | Rezaalipour, Mohammad Furia, Carlo A. |
| author_facet | Rezaalipour, Mohammad Furia, Carlo A. |
| contents | This paper presents FauxPy, a fault localization tool for Python programs. FauxPy supports seven well-known fault localization techniques in four families: spectrum-based, mutation-based, predicate switching, and stack trace fault localization. It is implemented as plugin of the popular Pytest testing framework, but also works with tests written for Unittest and Hypothesis (two other popular testing frameworks). The paper showcases how to use FauxPy on two illustrative examples, and then discusses its main features and capabilities from a user's perspective. To demonstrate that FauxPy is applicable to analyze Python projects of realistic size, the paper also summarizes the results of an extensive experimental evaluation that applied FauxPy to 135 real-world bugs from the BugsInPy curated collection. To our knowledge, FauxPy is the first open-source fault localization tool for Python that supports multiple fault localization families. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_18596 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | FauxPy: A Fault Localization Tool for Python Rezaalipour, Mohammad Furia, Carlo A. Software Engineering This paper presents FauxPy, a fault localization tool for Python programs. FauxPy supports seven well-known fault localization techniques in four families: spectrum-based, mutation-based, predicate switching, and stack trace fault localization. It is implemented as plugin of the popular Pytest testing framework, but also works with tests written for Unittest and Hypothesis (two other popular testing frameworks). The paper showcases how to use FauxPy on two illustrative examples, and then discusses its main features and capabilities from a user's perspective. To demonstrate that FauxPy is applicable to analyze Python projects of realistic size, the paper also summarizes the results of an extensive experimental evaluation that applied FauxPy to 135 real-world bugs from the BugsInPy curated collection. To our knowledge, FauxPy is the first open-source fault localization tool for Python that supports multiple fault localization families. |
| title | FauxPy: A Fault Localization Tool for Python |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2404.18596 |