Scaling Lean Theorem Proving for Real-World Code Verification
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
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The paper reports that all 1,325 theorems from the VeriContest benchmark—comprising 1,007 competitive‑programming problems in Rust with Verus specifications—were successfully proved using Rust‑Prover, a Lean 4‑based verifier. The authors translated each Verus specification and Rust program into Lean, then used Lean’s kernel to confirm the proofs, achieving a 70% first‑iteration success rate and completing 1,259 proofs in under 32 hours on Claude Opus 5.5. The translated Lean programs matched the original Rust outputs on 21,413 benchmark test cases, and the study also compared performance across multiple large‑language‑model settings, noting that higher reasoning effort increased cost without improving proof counts.
The paper introduces agentic verified optimization, where an AI agent produces a faster implementation of a program along with a machine‑checked proof that it is behaviorally equivalent to the original. The authors implement this in Lean 4, creating Aqueduct to migrate C, C++, Go, and Rust code into Lean and validate the ports via differential testing. On 189 reference functions, agents achieved 156 faster, proved rewrites, and on 17 migrated applications, 92 rewrites improved 47 of 51 scenarios, demonstrating the feasibility of verified optimization for real‑world software.
arXiv:2602. 09464v2 Announce Type: replace-cross Abstract: Vericoding refers to the generation of formally verified code from rigorous specifications.
arXiv:2603. 18334v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) increasingly assist secure software development, their ability to meet the rigorous demands of Rust program verification remains unclear.
arXiv:2608. 09277v1 Announce Type: new Abstract: Verified code generation asks a large language model (LLM) to generate both an executable program and a machine-checkable proof that the program meets a formal specification, promising software that is correct by construction.
arXiv:2603. 19329v3 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate plausible code but offer limited guarantees of correctness.