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AFAIK it's the first diverse corpus systematically used for fuzzer evaluation. Publishing results on that benchmark would make it much easier for potential users to evaluate Angora.
The text was updated successfully, but these errors were encountered:
Google has recently created a corpus to facilitate easy and reproducible comparison of fuzzing methodologies, see https://github.com/google/FuzzBench
AFAIK it's the first diverse corpus systematically used for fuzzer evaluation. Publishing results on that benchmark would make it much easier for potential users to evaluate Angora.
The text was updated successfully, but these errors were encountered: