Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Vision
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866915463420706816 |
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| author | Lu, Xu Sun, Weisong Zhang, Yiran Hu, Ming Tian, Cong Jin, Zhi Liu, Yang |
| author_facet | Lu, Xu Sun, Weisong Zhang, Yiran Hu, Ming Tian, Cong Jin, Zhi Liu, Yang |
| contents | Automated code generation has long been considered the holy grail of software engineering. The emergence of Large Language Models (LLMs) has catalyzed a revolutionary breakthrough in this area. However, existing methods that only rely on LLMs remain inadequate in the quality of generated code, offering no guarantees of satisfying practical requirements. They lack a systematic strategy for requirements development and modeling. Recently, LLM-based agents typically possess powerful abilities and play an essential role in facilitating the alignment of LLM outputs with user requirements. In this paper, we envision the first multi-agent framework for reliable code generation based on \textsc{re}quirements \textsc{de}velopment and \textsc{fo}rmalization, named \textsc{ReDeFo}. This framework incorporates three agents, highlighting their augmentation with knowledge and techniques of formal methods, into the requirements-to-code generation pipeline to strengthen quality assurance. The core of \textsc{ReDeFo} is the use of formal specifications to bridge the gap between potentially ambiguous natural language requirements and precise executable code. \textsc{ReDeFo} enables rigorous reasoning about correctness, uncovering hidden bugs, and enforcing critical properties throughout the development process. In general, our framework aims to take a promising step toward realizing the long-standing vision of reliable, auto-generated software. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2508_18675 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Vision Lu, Xu Sun, Weisong Zhang, Yiran Hu, Ming Tian, Cong Jin, Zhi Liu, Yang Software Engineering Automated code generation has long been considered the holy grail of software engineering. The emergence of Large Language Models (LLMs) has catalyzed a revolutionary breakthrough in this area. However, existing methods that only rely on LLMs remain inadequate in the quality of generated code, offering no guarantees of satisfying practical requirements. They lack a systematic strategy for requirements development and modeling. Recently, LLM-based agents typically possess powerful abilities and play an essential role in facilitating the alignment of LLM outputs with user requirements. In this paper, we envision the first multi-agent framework for reliable code generation based on \textsc{re}quirements \textsc{de}velopment and \textsc{fo}rmalization, named \textsc{ReDeFo}. This framework incorporates three agents, highlighting their augmentation with knowledge and techniques of formal methods, into the requirements-to-code generation pipeline to strengthen quality assurance. The core of \textsc{ReDeFo} is the use of formal specifications to bridge the gap between potentially ambiguous natural language requirements and precise executable code. \textsc{ReDeFo} enables rigorous reasoning about correctness, uncovering hidden bugs, and enforcing critical properties throughout the development process. In general, our framework aims to take a promising step toward realizing the long-standing vision of reliable, auto-generated software. |
| title | Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Vision |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2508.18675 |