LLM-Based Agents for Automating the Enhancement of User Story Quality: An Early Report

被引:2
作者
Zhang, Zheying [1 ]
Rayhan, Maruf [1 ]
Herda, Tomas [2 ]
Goisauf, Manuel [2 ]
Abrahamsson, Pekka [1 ]
机构
[1] Tampere Univ, Tampere, Finland
[2] Austrian Post, Rochuspl 1, A-1030 Vienna, Austria
来源
AGILE PROCESSES IN SOFTWARE ENGINEERING AND EXTREME PROGRAMMING, XP 2024 | 2024年 / 512卷
关键词
User Story Quality; Large language models; Agents;
D O I
10.1007/978-3-031-61154-4_8
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In agile software development, maintaining high-quality user stories is crucial, but also challenging. This study explores the application of large language models (LLMs) to improve the quality of user stories within the agile teams of Austrian Post Group IT. We developed an Autonomous LLM-based Agent System (ALAS) and evaluated its impact on user story quality with 11 participants from six agile teams. Our findings reveal the potential of LLMs in improving user story quality, provide a practical example, and lay the foundation for future research into the broad application of LLMs in a variety of industry settings.
引用
收藏
页码:117 / 126
页数:10
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