  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~\cite{fedotov2020casr} crash
reports. We evaluated our tool on a set of crash reports that was collected
from fuzzing results.
