TLA-Verus: Generating and Solving Temporal Proof Obligations with LLM Agents

Abstract:The TLA+ (temporal logic of actions) formal specification toolkit has seen widespread adoption in modeling modern distributed software systems including databases, storage systems, ledgers and coordination protocols. This popularity is despite its two significant limitations for software verification: Firstly, TLA+ offers no way to detect drift between software implementation and mathematical specification; secondly, TLC and TLAPS cannot provide satisfactory proofs of arbitrary temporal logic properties. We take a step towards addressing these shortcomings by translating TLA+ specifications into Verus, an auto-active verifier built for Rust, via both a deterministic transpiler and an agentic translator. We demonstrate that our LLM-based pipeline is able to generate proof obligations from TLA+ specifications at scale, and to produce fully machine checkable proofs of both safety and liveness properties. Since temporal logic reasoning in Verus is a largely new task for LLMs, our work yields a valuable evaluation dataset, which we use to map out current generation model capabilities in Verus theorem proving.

Machine Learning (cs.LG)

arXiv:2610.14923 [cs.LG]

(or arXiv:2610.14923v1 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2610.14923 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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