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Enhancing Software Engineering Through Predictive Modeling and Empirical Research

Rick Selby is an accomplished member of the ISERN community, and an adjunct faculty member at the University of Southern California. His empirical research focuses on building predictive models that leverage early lifecycle metrics for identifying leading indicators. He also conducts tradeoff analyses for large-scale systems engineering, emphasizing error reduction, effort estimation, and software reuse. Selby aims to foster collaboration and idea exchange among colleagues, promote balanced views of software research, and facilitate common frameworks to advance the field.

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Enhancing Software Engineering Through Predictive Modeling and Empirical Research

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  1. Rick SelbySoftware Products, Northrop Grumman & Adjunct Faculty, University of Southern CaliforniaLos Angeles, CA Candidate member • Main empirical research areas: • Techniques for building and evaluating predictive models that use early lifecycle metrics to define leading indicators • Empirical tradeoff analyses for large-scale systems engineering for errors, effort, and reuse • Infrastructure for automated data collection and analysis • Integrating active measurement and executable architectures • Main motivation for joining ISERN: • Interact with colleagues and share ideas and feedback • Planned contributions to the community: • Share balanced view of software research and practice • Help facilitate common approaches and frameworks • Expectations • Open discussions accelerate maturation of new ideas, methods, and studies • Relationships • Barry Boehm, Vic Basili, Dieter Rombach, etc.

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