VeriBase: Automated Construction of Theorem Libraries for Software Verification
Zihao Zhang, Zenan Li, Taolue Chen, Zhe Zhou, Tao Xie, Yuan Yao
Abstract
Software verification is typically more challenging than coding. Software developers routinely build on mature libraries and APIs, but turning successful verification solutions into reusable libraries still requires substantial expert effort. In this paper, we propose VeriBase, a framework for automatically constructing software-verification libraries by jointly generalizing code and its associated theorems from successful verification solutions. The key challenge is to generalize implementations together with the theorem statements and proofs that depend on these implementations, and reconcile overlapping components across verification tasks. To this end, VeriBase treats code and its associated theorems as declaration families, and designs a three-phase pipeline, which proves seed tasks, generalizes code and associated theorems, and harvests the resulting families into shared interfaces. VeriBase updates dependent declarations as interface change and uses Lean to check the resulting code and proofs. We evaluate VeriBase across four benchmarks with three backend LLMs. The results show that the general-purpose library built from independent 4,191 programs increases the average task success rate by up to 17.0% and meanwhile reduces the proof completion time by up to 21.4%. When VeriBase constructs a benchmark-specific library, further improvement can be observed.
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