@inproceedings{d4b3bbad910d46f3bbcbe03f02a90a3e,
title = "LLM-Based Agents for Automating the Enhancement of User Story Quality: An Early Report",
abstract = "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.",
keywords = "Agents, Large language models, User Story Quality",
author = "Zheying Zhang and Maruf Rayhan and Tomas Herda and Manuel Goisauf and Pekka Abrahamsson",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.; International Conference on Agile Software Development ; Conference date: 04-06-2024 Through 07-06-2024",
year = "2024",
doi = "10.1007/978-3-031-61154-4_8",
language = "English",
isbn = "978-3-031-61153-7",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer",
pages = "117--126",
editor = "Darja {\v S}mite and Eduardo Guerra and Xiaofeng Wang and Michele Marchesi and Peggy Gregory",
booktitle = "Agile Processes in Software Engineering and Extreme Programming - 25th International Conference on Agile Software Development, XP 2024, Proceedings",
}