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Efficient Symbolic Execution and Reasoning for Low Level Code

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2025-01-17

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Lu, Eric Hanqing. 2025. Efficient Symbolic Execution and Reasoning for Low Level Code. Doctoral Dissertation, Harvard University Graduate School of Arts and Sciences.

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Systems should be correct, and automated reasoning promises to help construct correct systems. A common toolchain for automated reasoning about programs, used in program verification, program synthesis, and automated bug-finding, is symbolic execution and constraint solving. This dissertation describes the application and optimization of this toolchain in two projects. First, we discuss optimizing assembly program synthesis for OS porting with a deductive approach. Then, we introduce branch deferral, a way to optimize symbolic execution in bug-finding by reducing the number of paths explored when executing short-circuit control flow graphs.

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Computer science

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