  We examine (directed) greybox fuzzing from a geometrical perspective, viewing
dissimilarities on inputs and on control flow graphs (with dynamical
statistics) as primitive objects of interest. We prototype and evaluate
GoExploreFuzz, a greybox fuzzer for time-intensive programs that incorporates
this perspective. The results indicate useful capabilities for greybox fuzzing
that have hitherto been underutilized, notably quantifying the diversity of
paths and autonomously tuning the "bandwidth" of mutations.
