Automatically Generating Web Applications from Requirements Via Multi-Agent Test-Driven Development
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912620280283136 |
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| author | Wan, Yuxuan Liang, Tingshuo Xu, Jiakai Xiao, Jingyu Huo, Yintong Lyu, Michael R. |
| author_facet | Wan, Yuxuan Liang, Tingshuo Xu, Jiakai Xiao, Jingyu Huo, Yintong Lyu, Michael R. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_25297 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automatically Generating Web Applications from Requirements Via Multi-Agent Test-Driven Development Wan, Yuxuan Liang, Tingshuo Xu, Jiakai Xiao, Jingyu Huo, Yintong Lyu, Michael R. Software Engineering Artificial Intelligence 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. |
| title | Automatically Generating Web Applications from Requirements Via Multi-Agent Test-Driven Development |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2509.25297 |