Knowledge-Based Multi-Agent Framework for Automated Software Architecture Design
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866913759918817280 |
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| author | Zhang, Yiran Li, Ruiyin Liang, Peng Sun, Weisong Liu, Yang |
| author_facet | Zhang, Yiran Li, Ruiyin Liang, Peng Sun, Weisong Liu, Yang |
| contents | Architecture design is a critical step in software development. However, creating a high-quality architecture is often costly due to the significant need for human expertise and manual effort. Recently, agents built upon Large Language Models (LLMs) have achieved remarkable success in various software engineering tasks. Despite this progress, the use of agents to automate the architecture design process remains largely unexplored. To address this gap, we envision a Knowledge-based Multi-Agent Architecture Design (MAAD) framework. MAAD uses agents to simulate human roles in the traditional software architecture design process, thereby automating the design process. To empower these agents, MAAD incorporates knowledge extracted from three key sources: 1) existing system designs, 2) authoritative literature, and 3) architecture experts. By envisioning the MAAD framework, we aim to advance the full automation of application-level system development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_20536 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Knowledge-Based Multi-Agent Framework for Automated Software Architecture Design Zhang, Yiran Li, Ruiyin Liang, Peng Sun, Weisong Liu, Yang Software Engineering Architecture design is a critical step in software development. However, creating a high-quality architecture is often costly due to the significant need for human expertise and manual effort. Recently, agents built upon Large Language Models (LLMs) have achieved remarkable success in various software engineering tasks. Despite this progress, the use of agents to automate the architecture design process remains largely unexplored. To address this gap, we envision a Knowledge-based Multi-Agent Architecture Design (MAAD) framework. MAAD uses agents to simulate human roles in the traditional software architecture design process, thereby automating the design process. To empower these agents, MAAD incorporates knowledge extracted from three key sources: 1) existing system designs, 2) authoritative literature, and 3) architecture experts. By envisioning the MAAD framework, we aim to advance the full automation of application-level system development. |
| title | Knowledge-Based Multi-Agent Framework for Automated Software Architecture Design |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2503.20536 |