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RAIN: Agentic Proof Generation for Rocq-based Software Verification
Jinyi Zhou, Zenan Li, Yuan Yao, Jun Ma, Taolue Chen, Xiaoxing Ma

RAIN: Agentic Proof Generation for Rocq-based Software Verification

Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

Interactive theorem provers can provide strong correctness guarantees for software, but constructing the proofs remains a challenging and labor-intensive task. Inspired by the recent progress of modern coding agents, we present RAIN, a lightweight proof-specialized agent for Rocq proof generation. RAIN augments an LLM with proof engineering capabilities, including repository exploration, iterative refinement, and checker feedback. This design allows the agent to retrieve lemmas autonomously, revise complete proof scripts instead of isolated tactics, and iteratively refine its proof strategy using enriched proof-state information. Evaluated on a subset from CoqStoq, RAIN shows substantial improvements over the existing baselines, achieving over 90% prove success rate with at least 24.7% improvements. We also compare with general-purpose coding agents, the results show that RAIN maintains comparable prove success rate but with significant lower cost.

Indexed from repository: arXiv (arxiv.org)
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Document Information

Document Title RAIN: Agentic Proof Generation for Rocq-based Software Verification
Author / Organization Jinyi Zhou, Zenan Li, Yuan Yao, Jun Ma, Taolue Chen, Xiaoxing Ma
Subject & Discipline cs.LO
Categories Science & Mathematics
Publication Year 2026
License / Rights arXiv Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website arXiv (arxiv.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-265176
Original Source Link Visit Source Page on arxiv.org »