Refining Fuzzed Crashing Inputs for Better Fault Diagnosis

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.

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Published
2025-06-23
DOI
https://doi.org/10.1145/3696630.3731436
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Refining Fuzzed Crashing Inputs for Better Fault Diagnosis

Shin Hong, K.H. Kim, Seongmin Lee
Software Testing and Debugging Techniques
article

Refining Fuzzed Crashing Inputs for Better Fault Diagnosis

Shin Hong, K.H. Kim, Seongmin Lee
article en

Abstract

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.

Chungbuk National University (KR), Max Planck Institute for Security and Privacy (DE)
Deutsche Forschungsgemeinschaft
Climate action
Openalex Percentile: Top 81%
Software Testing and Debugging Techniques
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