用AI把自然语言合同自动转成代码并评估质量
An end-to-end agentic pipeline for smart contract translation and quality evaluation
- 用多智能体迭代生成代码，结构化输出带溯源信息
- 从五个维度评估代码质量，支持与真实实现比对
- 适合研究合约生成、安全检测或区块链开发的开发者
我们提出一个端到端框架，用于系统评估大模型从自然语言规范生成的智能合约。该系统将合同文本解析为结构化模式，生成Solidity代码，并通过编译和安全检查进行自动化质量评估。采用CrewAI风格的智能体团队，通过迭代优化生成带有完整溯源元数据的结构化成果。质量评估涵盖五个维度：功能完整性、变量保真度、状态机正确性、业务逻辑一致性以及代码质量，综合生成评分。框架支持与真实实现的配对评估，量化对齐程度并识别系统性错误模式，如逻辑遗漏和状态转移不一致。这为智能合约合成质量的实证研究提供了可复现基准，并支持扩展至形式化验证和合规检查。
原文摘要 · Abstract (English)
We present an end-to-end framework for systematic evaluation of LLM-generated smart contracts from natural-language specifications. The system parses contractual text into structured schemas, generates Solidity code, and performs automated quality assessment through compilation and security checks. Using CrewAI-style agent teams with iterative refinement, the pipeline produces structured artifacts with full provenance metadata. Quality is measured across five dimensions, including functional completeness, variable fidelity, state-machine correctness, business-logic fidelity, and code quality aggregated into composite scores. The framework supports paired evaluation against ground-truth implementations, quantifying alignment and identifying systematic error modes such as logic omissions and state transition inconsistencies. This provides a reproducible benchmark for empirical research on smart contract synthesis quality and supports extensions to formal verification and compliance checking.
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