用AI自动造网页应用，能自测自改，效果比现有方法提升14.4%。
Automatically Generating Web Applications from Requirements Via Multi-Agent Test-Driven Development
- 基于测试驱动的多智能体框架，从需求自动生成前后端代码
- 在多个场景中实现14.4%准确率提升，无需人工干预
- 适合想快速开发全栈应用的开发者或团队
开发全栈网页应用复杂且耗时，需掌握多种技术。尽管多模态大模型可自动生成前端页面，但现有方案仍局限于前端，无法产出完整可用的应用。本文提出TDDev，首个支持测试驱动开发（TDD）的LLM智能体框架，实现从自然语言描述或设计图到全栈应用的端到端生成。该框架自动推导可执行测试用例，生成前后端代码，模拟用户交互，并迭代优化直至满足所有需求。针对需求模糊、文件间依赖复杂、功能与视觉一致性等挑战，通过多场景实验验证，相比最先进基线，整体准确率提升14.4%，证明其在无需人工干预下生成可靠高质量应用的有效性。
原文摘要 · Abstract (English)
Developing full-stack web applications is complex and time-intensive, demanding proficiency across diverse technologies and frameworks. Although recent advances in multimodal large language models (MLLMs) enable automated webpage generation from visual inputs, current solutions remain limited to front-end tasks and fail to deliver fully functional applications. In this work, we introduce TDDev, the first test-driven development (TDD)-enabled LLM-agent framework for end-to-end full-stack web application generation. Given a natural language description or design image, TDDev automatically derives executable test cases, generates front-end and back-end code, simulates user interactions, and iteratively refines the implementation until all requirements are satisfied. Our framework addresses key challenges in full-stack automation, including underspecified user requirements, complex interdependencies among multiple files, and the need for both functional correctness and visual fidelity. Through extensive experiments on diverse application scenarios, TDDev achieves a 14.4% improvement on overall accuracy compared to state-of-the-art baselines, demonstrating its effectiveness in producing reliable, high-quality web applications without requiring manual intervention.
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