MuoFuzz improves greybox fuzzing by learning mutator sequence interactions to select effective orders, outperforming AFL++ and MOPT on coverage and unique bugs in FuzzBench and MAGMA.
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LLM-powered monitoring of UI similarity allows random testing tools to escape tarpits, yielding 45-55% higher coverage and more unique bugs across 12 apps.
Nygard's ADR template outperformed MADR on overall score in a controlled experiment with undergraduates after expert screening of five templates via DESMET FA.
citing papers explorer
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On Interaction Effects in Greybox Fuzzing
MuoFuzz improves greybox fuzzing by learning mutator sequence interactions to select effective orders, outperforming AFL++ and MOPT on coverage and unique bugs in FuzzBench and MAGMA.
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Improving Random Testing via LLM-powered UI Tarpit Escaping for Mobile Apps
LLM-powered monitoring of UI similarity allows random testing tools to escape tarpits, yielding 45-55% higher coverage and more unique bugs across 12 apps.
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One Size Fits All? An Empirical Comparison of ADR Templates regarding Comprehension, Usability, and Ease of Adoption
Nygard's ADR template outperformed MADR on overall score in a controlled experiment with undergraduates after expert screening of five templates via DESMET FA.