Lecture

Learning-aided Program Reasoning

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Description

This lecture by the instructor covers the fundamental challenges in program reasoning, such as bug-finding and verification, using examples like the Heartbleed bug. It explores the use of static analysis tools like Clang Static Analyzer and the application of differential Bayesian reasoning to prioritize true alarms over false alarms. The lecture also delves into the automation and accuracy challenges in program verification, showcasing research contributions leveraging machine learning. The talk outlines differential Bayesian reasoning frameworks and deep reinforcement learning frameworks for program verification, emphasizing the importance of learning-aided approaches in addressing these challenges.

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