LLM-based agents for automating the enhancement of user story quality: An early report
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866911298250342400 |
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| author | Zhang, Zheying Rayhan, Maruf Herda, Tomas Goisauf, Manuel Abrahamsson, Pekka |
| author_facet | Zhang, Zheying Rayhan, Maruf Herda, Tomas Goisauf, Manuel Abrahamsson, Pekka |
| contents | In agile software development, maintaining high-quality user stories is crucial, but also challenging. This study explores the use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams. We developed a reference model for an Autonomous LLM-based Agent System and implemented it at the company. The quality of user stories in the study and the effectiveness of these agents for user story quality improvement was assessed by 11 participants across six agile teams. Our findings demonstrate the potential of LLMs in improving user story quality, contributing to the research on AI role in agile development, and providing a practical example of the transformative impact of AI in an industry setting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_09442 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | LLM-based agents for automating the enhancement of user story quality: An early report Zhang, Zheying Rayhan, Maruf Herda, Tomas Goisauf, Manuel Abrahamsson, Pekka Software Engineering Artificial Intelligence In agile software development, maintaining high-quality user stories is crucial, but also challenging. This study explores the use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams. We developed a reference model for an Autonomous LLM-based Agent System and implemented it at the company. The quality of user stories in the study and the effectiveness of these agents for user story quality improvement was assessed by 11 participants across six agile teams. Our findings demonstrate the potential of LLMs in improving user story quality, contributing to the research on AI role in agile development, and providing a practical example of the transformative impact of AI in an industry setting. |
| title | LLM-based agents for automating the enhancement of user story quality: An early report |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2403.09442 |