用大模型自动生成软件用例模型，提速60%且质量相当。
Leveraging Large Language Models for Use Case Model Generation from Software Requirements
- 结合提示工程与开源大模型，从需求文本中自动提取参与者和用例。
- 实测显示建模时间减少60%，模型质量与人工相当。
- 适合需快速迭代的团队，尤其助于新手理解需求场景。
用例建模通过用户中心的场景来描述系统需求，有助于利益相关方达成共识。然而，手动构建用例模型费时费力，实践中常被跳过。本研究探索大语言模型（LLM）在该过程中的辅助潜力。所提方法利用开源权重大模型，结合先进的提示工程，系统性地从软件需求中提取参与者和用例。通过五名专业软件工程师开展的探索性研究，对比传统人工建模与基于LLM的方法，结果显示建模时间减少60%，模型质量保持一致。此外，参与者反馈该方法在过程中提供了有价值的指导。
原文摘要 · Abstract (English)
Use case modeling employs user-centered scenarios to outline system requirements. These help to achieve consensus among relevant stakeholders. Because the manual creation of use case models is demanding and time-consuming, it is often skipped in practice. This study explores the potential of Large Language Models (LLMs) to assist in this tedious process. The proposed method integrates an open-weight LLM to systematically extract actors and use cases from software requirements with advanced prompt engineering techniques. The method is evaluated using an exploratory study conducted with five professional software engineers, which compares traditional manual modeling to the proposed LLM-based approach. The results show a substantial acceleration, reducing the modeling time by 60\%. At the same time, the model quality remains on par. Besides improving the modeling efficiency, the participants indicated that the method provided valuable guidance in the process.
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