Byron DeVries

H-Net: Humanities & Social Sciences Online, Michigan State University, Grand Valley State University

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About

Byron DeVries is a researcher whose work lies at the intersection of requirements engineering, adaptive systems, and multi-robot coordination. His key contributions address how software-intensive systems—particularly cyber-physical systems like autonomous robots—can be designed to handle uncertainty during execution. His most cited work, "AutoRELAX: automatically RELAXing a goal model to address uncertainty" (2014, 34 citations), introduces a method for automatically softening goal specifications so that systems can adapt gracefully when environmental conditions change. This work has been influential in the requirements engineering community, providing a practical bridge between formal goal models and runtime adaptation. DeVries also explored how adaptive controllers can discover their own operational boundaries, as shown in his 2016 paper on evolutionary approaches to execution mode boundaries (7 citations). More recently, his 2022 paper on optimizing trade-offs between distance and coverage for facility location (3 citations) addresses a fundamental challenge in deploying multi-robot systems and sensor networks: balancing communication range with sensing coverage. Collectively, DeVries’ research demonstrates a sustained interest in making autonomous systems more robust, flexible, and practical—work that is increasingly relevant as robots and sensors become more prevalent in real-world applications.