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ICLR2024顶会

Lemur: Integrating Large Language Models in Automated Program Verification

Haoze Wu, Clark W. Barrett, Nina Narodytska

2024年份
67被引次数
15顶会引用

摘要

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 transition rules and prove its soundness. We instantiate the calculus as a sound automated verification procedure and demonstrate practical improvements on a set of synthetic and competition benchmarks.

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