  In this paper, we introduce an approach for improving the early exploration
of grey-box fuzzing campaigns; allowing the fuzzer to reach the interesting
coverage earlier. To do this, it leverages information from the system under
test's (SUT's) control flow graph in order to decide which inputs are likely to
lead to discovering most coverage when mutated.
