Analyzing User Story Quality: A Systematic Review of Common Issues and Solutions

João Vitor Oliveira, Lisandra Fontoura

2025

Abstract

User stories are widely adopted in agile development, serving as a fundamental technique for capturing and communicating software requirements. This paper aims to conduct a systematic literature review (SLR) to identify and analyze studies that address issues found in user stories, as well as possible ways to solve them. The primary motivation for this study was the advancement in the use of Large Language Models (LLMs), particularly after the launch of ChatGPT in 2022 by OpenAI. The research identified the main issues and solutions related to user stories between 2020 and 2024, focusing on issues related to user story quality. The results indicate that the most common issue in user stories is quality problems, cited in 15 articles, followed by requirements management and task assignment (12) and the derivation and generation of the conceptual model (8). Estimation is the least mentioned issue, appearing only three times. Regarding solution methods, researchers most frequently used Natural Language Processing, Machine Learning, and other Artificial Intelligence techniques, citing them in 15 articles. This demonstrates the well-established application of AI methods to address these challenges.

Paper Citation

in Harvard Style

Oliveira J. and Fontoura L. (2025). Analyzing User Story Quality: A Systematic Review of Common Issues and Solutions. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 152-159. DOI: 10.5220/0013218300003929

in Bibtex Style

@conference{iceis25,
author={João Oliveira and Lisandra Fontoura},
title={Analyzing User Story Quality: A Systematic Review of Common Issues and Solutions},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2025},
pages={152-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013218300003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Analyzing User Story Quality: A Systematic Review of Common Issues and Solutions
SN - 978-989-758-749-8
AU - Oliveira J.
AU - Fontoura L.
PY - 2025
SP - 152
EP - 159
DO - 10.5220/0013218300003929
PB - SciTePress