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About

Deborah Katz is a prominent researcher specializing in software testing, verification, and validation for robotics and autonomous systems. Her work sits at the critical intersection of simulation technology and software quality assurance, addressing how developers can ensure the reliability and safety of increasingly ubiquitous robotic systems. Katz's most influential contribution, "Simulation for Robotics Test Automation: Developer Perspectives" (2021, 65 citations), examines how simulation can serve as a cheaper, safer, and more effective alternative to traditional manual field testing. Her seminal 2018 paper, "Crashing Simulated Planes is Cheap: Can Simulation Detect Robotics Bugs Early?" (56 citations), challenged the field to rethink early-stage bug detection, demonstrating that simulation environments offer powerful opportunities to identify critical faults before real-world deployment. This work has proven particularly significant as autonomous systems move from industrial settings into consumer applications where safety failures carry serious consequences. Beyond detection, Katz has explored anomaly identification in autonomy software through execution profiling and clustering techniques, broadening the toolkit available to developers. With over 160 cumulative citations, her research has meaningfully shaped how the robotics engineering community approaches testing methodology, making complex systems both safer and more rigorously validated.