Software Requirements Prioritisation Using Machine Learning

Arooj Fatima, Anthony Fernandes, David Egan, Cristina Luca

2023

Abstract

Prioritisation of requirements for a software release can be a difficult and time-consuming task, especially when the number of requested features far outweigh the capacity of the software development team and difficult decisions have to be made. The task becomes more difficult when there are multiple software product lines supported by a software release, and yet more challenging when there are multiple business lines orthogonal to the product lines, creating a complex set of stakeholders for the release including product line managers and business line managers. This research focuses on software release planning and aims to use Machine Learning models to understand the dynamics of various parameters which affect the result of software requirements being included in a software release plan. Five Machine Learning models were implemented and their performance evaluated in terms of accuracy, F1 score and K-Fold Cross Validation (Mean).

Paper Citation

in Harvard Style

Fatima A., Fernandes A., Egan D. and Luca C. (2023). Software Requirements Prioritisation Using Machine Learning. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 893-900. DOI: 10.5220/0011796900003393

in Bibtex Style

@conference{icaart23,
author={Arooj Fatima and Anthony Fernandes and David Egan and Cristina Luca},
title={Software Requirements Prioritisation Using Machine Learning},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={893-900},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011796900003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Software Requirements Prioritisation Using Machine Learning
SN - 978-989-758-623-1
AU - Fatima A.
AU - Fernandes A.
AU - Egan D.
AU - Luca C.
PY - 2023
SP - 893
EP - 900
DO - 10.5220/0011796900003393