  Fuzz Testing is a largely automated testing technique that provides random
and unexpected input to a program in attempt to trigger failure conditions.
Much of the research conducted thus far into Fuzz Testing has focused on
developing improvements to available Fuzz Testing tools and frameworks in order
to improve efficiency. In this paper however, we instead look at a way in which
we can reduce the amount of developer time required to integrate Fuzz Testing
to help maintain an existing codebase. We accomplish this with a new technique
for automatically generating Fuzz Targets, the modified versions of programs on
which Fuzz Testing tools operate. We evaluated three different Fuzz Testing
solutions on the codebase of our industry partner and found a fully automated
solution to result in significantly more bugs found with respect to the
developer time required to implement said solution. Our research is an
important step towards increasing the prevalence of Fuzz Testing by making it
simpler to integrate a Fuzz Testing solution for maintaining an existing
codebase.
