2021/12/27 by Georgy Savidov, Savidov, Georgy, Andrey Fedotov +1
Computer Science · #Advanced Malware Detection Techniques #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Software Engineering (cs.SE) #Software Reliability and Analysis Research #Software Testing and Debugging Techniques
paper · pdf · doi:10.48550/arxiv.2112.13719
openalex publication_date 2021/12/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Crash report analysis is a necessary step before developers begin fixing errors. Fuzzing or hybrid (with dynamic symbolic execution) fuzzing is often used in the secure development lifecycle. Modern fuzzers could produce many crashes and developers do not have enough time to fix them till release date. There are two approaches that could reduce developers' effort on crash analysis: crash clustering and crash severity estimation. Crash severity estimation could help developers to prioritize crashes and close security issues first. Crash clustering puts similar crash reports in one cluster what could speed up the analyzing time for all crash reports. In this paper, we focus on crash clustering. We propose an approach for clustering and deduplicating of crashes that occurred in Linux applications. We implement this approach as a tool that could cluster Casr~\citefedotov2020casr crash reports. We evaluated our tool on a set of crash reports that was collected from fuzzing results.