“Fuzz testing is often automated, but also frequently augmented by experts who insert themselves into the workflow in a greedy search for bugs. In this paper, we propose Homo in Machina, or HM-fuzzing, in which analyses guide the manual efforts, maximizing benefit. As one example … we introduce compartment analysis. Compartment analysis uses a whole-program dominator analysis to estimate the utility of reaching new code, and combines this with a dynamic analysis indicating drastically under-covered edges guarding that code.”

Find the paper and full list of authors in the proceedings of the 2023 IEEE Conference on Software Testing, Verification and Validation.