In software testing, the gold standard for evaluating test quality is mutation analysis, which evaluates a test's ability to detect synthetic bugs: If a set of tests fails to detect such mutations, it is expected to also fail to detect real bugs.
Jun 4, 2021 · This study identifies flaws in bug injection techniques and suggests a number of axes along which synthetic bugs should be improved.
Aug 23, 2022 · This study identifies flaws in bug injection techniques and suggests a number of axes along which synthetic bugs should be improved.
Jun 7, 2021 · These experiments test the selected fuzzers' ability to discover bugs injected by LAVA in its default configuration, alternative LAVA ...
Artificial bug injection methods often introduce shallow bugs that are amenable to fuzzers, and are generally no longer recommended for an evaluation [18] , [ ...
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Jan 15, 2024 · Our technique, called HyperPUT, builds C programs from a “seed” bug by incrementally applying program transformations.
Jul 11, 2016 · The researchers are inserting a specific number of synthetic bugs into software and then watching to see which ones are located by bug-finding ...
Sep 5, 2024 · To validate synthetic datasets, compare them to real-world data to verify accurate representation of patterns and distributions found in actual ...
Nov 4, 2023 · First, directed grey-box fuzzers are more prone to overfitting than undirected grey-box fuzzers as they are designed to explore specific paths ...
Mar 19, 2024 · We construct a synthetic benchmark and evaluate it against five prominent fuzzers. The experiments reveal that 391 out of 466 bugs were detected ...