Yunze Zhao, Wentao Guo, and Harrison Goldstein, University of Maryland; Daniel Votipka, Tufts University; Kelsey Fulton, Colorado School of Mines; Michelle Mazurek, University of Maryland
Fuzzing is a widely adopted technique for uncovering software vulnerabilities by generating random or mutated test inputs to trigger unexpected behavior. However, little is known about how developers actually use fuzzing tools in practice, the challenges they face, and where current tools fall short. This study investigates the human side of fuzzing via 18 semi-structured interviews with fuzzing users across diverse domains. These interviews explore participants’ workflows, frustrations, and expectations around fuzzing, revealing critical usability gaps and design opportunities. The results can inform the next generation of fuzzing tools to improve user experience, reduce manual effort, and enable more effective integration of fuzzing into real-world workflows.
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