Key points are not available for this paper at this time.
Mutation-based greybox fuzzing---unquestionably the most widely-used fuzzing technique---relies on a set of non-crashing seed inputs (a corpus) to bootstrap the bug-finding process. When evaluating a fuzzer, common approaches for constructing this corpus include: (i) using an empty file; (ii) using a single seed representative of the target's input format; or (iii) collecting a large number of seeds (e.g., by crawling the Internet). Little thought is given to how this seed choice affects the fuzzing process, and there is no consensus on which approach is best (or even if a best approach exists).
Herrera et al. (Thu,) studied this question.