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This lecture by the instructor from the University of Maryland discusses software correctness at scale through testing and verification. It covers topics such as property-based fuzzing, testing noninterference, and the use of QuickChick for property-based testing in Coq. The lecture delves into the challenges of dynamic information flow control, formal guarantees, and the practical aspects of property-based testing for Python. It also explores the concepts of semantic mutators, formal specifications, and the importance of formal verification in ensuring software correctness.
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