Proposes the REAL framework for ML systems requirements engineering that weaves data/model/system requirements, uses failure-driven exploration, and supports iterative traceable refinement, shown via an autonomous driving example.
Simulator- based explanation and debugging of hazard-triggering events in dnn-based safety-critical systems,
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From Failure to Alignment: A Requirements Engineering Framework for Machine Learning Systems
Proposes the REAL framework for ML systems requirements engineering that weaves data/model/system requirements, uses failure-driven exploration, and supports iterative traceable refinement, shown via an autonomous driving example.