Fuzzing, the method of generating inputs to run on a target program while monitoring its execution, is a widely adopted and pragmatic methodology for bug hunting as a means of software hardening. Technical improvements in throughput have shown to be critical to increasing the rate at which new bugs can be discovered time and time again. Persistent fuzzing, which keeps the fuzz target alive via looping, provides increased throughput at the cost for manual development of harnesses to account for invalid states and coverage of the programs code base, while relying on forking to reset the state accrued by looping over the same piece of code multiple times. Stale state can lead to wasted fuzzing efforts as certain areas of code may be conditionally ignored due to a stale global. I propose Closure, a toolset which enables programs to run at persistent speeds while avoiding the downsides of stale state and other bottlenecks associated with persistent fuzzing. / Master of Science / The process of program testing to find bugs is becoming increasingly automated. A current method called "Fuzzing", is a widely adopted means for finding bugs and is required in the life cycle of program development by major companies and the US Government. I look at current improvements in fuzzing, and expand the use case of the cutting edge method called persistent fuzzing to a wider array of applications with my tool Closure. With Closure, fuzzing practitioners can experience faster fuzzing performance with less manual effort.