Towards Trustworthy Smart Contract Synthesis: A Multi-Agent Framework with Lean-Based Verification
Bowei Zhang, Hanbing Liu, Qixin Tian, Siyu Chen, Ziyuan Wang, Qi Qi
摘要
Smart Contracts are the foundation of Decentralized Finance (DeFi), executing financial logic without trusted intermediaries. Recent advances in large language models (LLMs) have substantially lowered the barrier to smart contract development by enabling code generation from natural language. However, because smart contracts are immutable and directly manage financial assets, this accessibility introduces a critical trust gap: generated contracts are easy to produce but hard to trust. To bridge this gap, We present LeVer, the first trustworthy smart contract synthesis framework that integrates LLM-based generation with Lean-based autoformalization and Verification. LeVer employs a closed-loop multi-agent architecture to iteratively generate, verify, attack, and repair contracts, providing both formal guarantees and empirical robustness. To facilitate the adoption of automated formal verification in smart contract generation and audition, we opensource our framework and datasets at: https: //github.com/gl-bowei/LeVer
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
相关 Paper
- LEVER: Learning to Verify Language-to-Code Generation with ExecutionAnsong Ni, Srini Iyer, Dragomir Radev, Veselin Stoyanov 等ICML 2023 · 被引用 318 次
- SmartCoder-R1: Towards Secure and Explainable Smart Contract Generation with Security-Aware Group Relative Policy OptimizationLei Yu, Jingyuan Zhang, Xin Wang, Li Yang 等FSE 2026 · 被引用 3 次
- FHE-Coder: Benchmarking Secure Agentic Code Generation for Fully Homomorphic EncryptionMayank Kumar, Jiaqi Xue, Mengxin Zheng, Qian LouICLR 2026
- Thought Is All You Need: Smart Contract Vulnerability Detection with Thought-Augmented Large Language ModelChaoyuan Peng, Muhui Jiang, Yajin Zhou, Lei WuFSE 2026
- AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and TreefinementPranjal Aggarwal, Bryan Parno, Sean WelleckICML 2025
