Refining Fuzzed Crashing Inputs for Better Fault Diagnosis
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866912361955196928 |
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| author | Kim, Kieun Lee, Seongmin Hong, Shin |
| author_facet | Kim, Kieun Lee, Seongmin Hong, Shin |
| contents | We present DiffMin, a technique that refines a fuzzed crashing input to gain greater similarities to given passing inputs to help developers analyze the crashing input to identify the failure-inducing condition and locate buggy code for debugging. DiffMin iteratively applies edit actions to transform a fuzzed input while preserving the crash behavior. Our pilot study with the Magma benchmark demonstrates that DiffMin effectively minimizes the differences between crashing and passing inputs while enhancing the accuracy of spectrum-based fault localization, highlighting its potential as a valuable pre-debugging step after greybox fuzzing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_02305 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Refining Fuzzed Crashing Inputs for Better Fault Diagnosis Kim, Kieun Lee, Seongmin Hong, Shin Software Engineering D.2.5 We present DiffMin, a technique that refines a fuzzed crashing input to gain greater similarities to given passing inputs to help developers analyze the crashing input to identify the failure-inducing condition and locate buggy code for debugging. DiffMin iteratively applies edit actions to transform a fuzzed input while preserving the crash behavior. Our pilot study with the Magma benchmark demonstrates that DiffMin effectively minimizes the differences between crashing and passing inputs while enhancing the accuracy of spectrum-based fault localization, highlighting its potential as a valuable pre-debugging step after greybox fuzzing. |
| title | Refining Fuzzed Crashing Inputs for Better Fault Diagnosis |
| topic | Software Engineering D.2.5 |
| url | https://arxiv.org/abs/2505.02305 |