Lemur: Integrating Large Language Models in Automated Program Verification
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Keywords: Large Language Models, Formal verification
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TL;DR: We present a general methodology for combining LLMs and formal verifiers for automated program verification.
Abstract: The demonstrated code-understanding capability of LLMs raises the question of whether they can be used for automated program verification, a task that demands high-level abstract reasoning about program properties that is challenging for verification tools. We propose a general methodology to combine the power of LLMs and automated reasoners for automated program verification. We formally describe this methodology as a set of derivation rules and prove its soundness. We instantiate the calculus as a sound automated verification procedure, which led to practical improvements on a set of synthetic and competition benchmarks.
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Primary Area: neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.)
Submission Number: 7652
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