Making Formal Verification Trustworthy via Proof Generation

semanticscholar(2021)

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摘要
Formal deductive verification aims at proving the correctness of programs via logical deduction. However, the fact that it is usually based on complex program logics makes it error-prone to implement. This paper addresses the important research question of how we can make a deductive verifier trustworthy through a practical approach. We propose a novel technique to generate machine-checkable proof objects to certify each verification task performed by the language-agnostic deductive verifier of K—a semanticsbased language framework. These proof objects encode formal proofs in matching logic—the logical foundation of K. They have a small 240-line trust base and can be directly verified by third-party proof checkers. Our preliminary experiments show promising performance in generating correctness proofs for deductive verification in different programming languages.
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