Intelligent Lemma Selection for Formal Methods Proofs

Abstract

To help in formally verifying the correctness of various systems, NASA constructs mathematical proofs using the proof assistant PVS (Prototype Verification System). Throughout this effort, NASA has amassed a library of tens of thousands of proven lemmas. While these lemmas can often be applied to new problems, their abundance can make lemma selection a non-trivial task. This project focuses on creating a lemma selector for use in PVS based on existing systems MePo, MaSh, and MeSh, which were written for other proof assistants. An initial benchmark system makes selections based on symbol-level similarity while the final lemma selector is a hybrid system, combining the classical approach used in the benchmark with a machine learning approach which leverages the lemmas' past usage.