用大模型和三元概念分析生成可复用的用户故事集
Variability-Driven User-Story Generation using LLM and Triadic Concept Analysis
- 结合三元概念分析与大模型提示，挖掘系统族中的可变逻辑
- 在67个相似用途网站数据上验证，可自动生成并校验用户故事集
- 适合敏捷开发中需快速构建新系统原型的团队使用
在软件产品线背景下，为一系列相似系统定义需求通常表现为多个用户故事集合，构成由（系统，角色，功能）三元组组成的三维数据集。本文提出一种结合三元概念分析（TCA）与大语言模型（LLM）提示的方法，基于已有系统族的可变逻辑，为新系统生成对应的用户故事集。流程包括：1）计算三维可变性并提取TCA蕴含关系；2）向设计者呈现可理解的设计选项；3）记录设计选择；4）生成初始用户故事集；5）根据步骤1的蕴含关系校验并补全故事集；6）利用LLM扩展生成更完整的网站内容。该方法在包含67个同类用途网站的用户故事集数据集上进行了评估。
原文摘要 · Abstract (English)
A widely used Agile practice for requirements is to produce a set of user stories (also called ``agile product backlog''), which roughly includes a list of pairs (role, feature), where the role handles the feature for a certain purpose. In the context of Software Product Lines, the requirements for a family of similar systems is thus a family of user-story sets, one per system, leading to a 3-dimensional dataset composed of sets of triples (system, role, feature). In this paper, we combine Triadic Concept Analysis (TCA) and Large Language Model (LLM) prompting to suggest the user-story set required to develop a new system relying on the variability logic of an existing system family. This process consists in 1) computing 3-dimensional variability expressed as a set of TCA implications, 2) providing the designer with intelligible design options, 3) capturing the designer's selection of options, 4) proposing a first user-story set corresponding to this selection, 5) consolidating its validity according to the implications identified in step 1, while completing it if necessary, and 6) leveraging LLM to have a more comprehensive website. This process is evaluated with a dataset comprising the user-story sets of 67 similar-purpose websites.
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