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P1 Certified Program Synthesis with a Multi-modal Verifier

基于多模态验证器的可认证程序合成
ASE Proceedings of the 41st IEEE/ACM International Conference on Automated Software Engineering2026匹配度 7/10 · 论文属于“LLM/Agent 改进形式化验证”方向,使用 Lean 多模态验证器 Velvet 构建 agentic 流水线来做可认证程序合成,并调用前沿 AI prover,与用户画像中 AI→PL 的兴趣高度相关;但核心任务是程序合成与证明生成,而非静态分析,也未涉及浮点程序分析或贝叶斯程序分析。引用 4 inbox
Yueyang Feng, Dipesh Kafle, Vladimir Gladshtein, Vitaly Kurin, George Pîrlea, Qiyuan Zhao, Peter Müller, Ilya Sergey
crossref: 2026-10-09

AI 速览

一句话:提出基于 Lean 多模态验证器 Velvet 的分阶段 agent 流水线 LeetProof,实现从自然语言到程序、规格与机器可检验证明的可认证合成。

可认证程序合成(vericoding)需从自然语言同时生成程序、形式规格与机器可检验的对齐证明,但合成的规格常过弱或过强而缺乏系统检测手段,且验证器按推理模式(自动主动式 vs 交互式)割裂,迫使方法局限于单一范式。作者以 Lean 中融合动态验证、自动证明与交互式证明脚本的多模态验证器 Velvet 为核心,构建分阶段 agent 流水线 LeetProof:先以随机化性质测试验证规格,再依验证条件分解合成子任务,最后将残余证明义务交给面向 Lean 的前沿 AI 证明器。在由既有工作扩充的可认证合成基准上,其规格验证发现参考基准中的缺陷,且在固定预算下 LeetProof 的完全认证成功率显著优于单模态基线,并在两种前沿 LLM 后端上保持一致。

问题
从自然语言任务描述同时合成程序、形式规格与机器可检验的对齐证明时,合成规格往往过弱或过强且缺乏系统的缺陷检测手段;同时验证器按推理模式(自动主动式或交互式)碎片化,使合成方法只能面向单一范式,限制了可处理的任务范围。
方法
以 Lean 中实现的多模态验证器 Velvet(在同一基础框架内结合动态验证、自动证明与交互式证明脚本)为核心,构建分阶段的 agent 流水线 LeetProof:先做随机化性质测试以验证规格,再依据验证条件将合成任务分解为子问题,并把残余证明义务委托给面向 Lean 的前沿 AI 证明器。
评估
在由先前可认证合成工作扩充而来的大规模基准套件上评估,其规格验证环节揭示了现有参考基准中的缺陷;在固定预算下,LeetProof 的分阶段流水线相比单模态基线取得显著更高的完全认证解决方案比例,且在两种不同前沿 LLM 后端上结果一致。
原文摘要(Abstract)

Certified program synthesis (a.k.a. vericoding) is the process of automatically generating a program, its formal specification, and a machine-checkable proof of program/specification alignment from a natural-language task description. Two key challenges make vericoding difficult. First, specifications synthesised from natural language descriptions are often either too weak to be meaningful or too strong to be implementable, yet existing approaches lack systematic means to detect such defects. Second, the program verifiers used to validate results are fragmented: each tool supports a particular reasoning mode—auto-active (e.g., Dafny, Verus) or interactive (e.g., Rocq, Lean)—with its own trade-off between automation and expressivity. This forces each synthesis methodology to target a single paradigm, limiting the tasks it can handle. We overcome both challenges by structuring the synthesis workflow in stages around a multi-modal verifier—a single tool that combines dynamic validation, automated proofs, and interactive proof scripting within one foundational framework. We realise this idea in LeetProof, a new agentic pipeline built on Velvet, a multi-modal program verifier built in the Lean theorem prover. Multi-modality enables LeetProof to validate generated specifications via randomised property-based testing before any code is synthesised, decompose the synthesis task into sub-problems guided by verification conditions, and delegate residual proof obligations to frontier AI provers specialised for Lean. We evaluate LeetProof on an extensive benchmark suite derived from prior work on certified synthesis. Our specification validation uncovers defects in existing reference benchmarks, and LeetProof's staged pipeline achieves a significantly higher rate of fully certified solutions than a single-mode baseline at the same fixed budget—consistently across two different frontier LLM backends.

链接与引用

DOI 原文 · arXiv · DBLP

BibTeX
@inproceedings{abs-2604-16584,
  title = {Certified Program Synthesis with a Multi-modal Verifier},
  author = {Yueyang Feng and Dipesh Kafle and Vladimir Gladshtein and Vitaly Kurin and George Pîrlea and Qiyuan Zhao and Peter Müller and Ilya Sergey},
  booktitle = {ASE},
  year = {2026},
  doi = {10.1145/3832783.3837559}
}