Considerations in Prioritizing for Efficiently Refactoring the Data Clumps Model Smell: A Preliminary Study

Nils Baumgartner, Padma Iyenghar, Padma Iyenghar, Elke Pulvermüller

2024

Abstract

This paper delves into the importance of addressing the data clumps model smell, emphasizing the need for prioritizing them before refactoring. Qualitative and quantitative criteria for identifying data clumps are outlined, accompanied by a systematic, simple but effective approach involving a weighted attribute system with threshold-based priority assignment. The paper concludes with an experimental evaluation of the proposed method, offering insights into critical areas for developers and contributing to improved code maintenance practices and overall quality. The approach presented provides a practical guide for enhancing software system quality and sustainability.

Paper Citation

in Harvard Style

Baumgartner N., Iyenghar P. and Pulvermüller E. (2024). Considerations in Prioritizing for Efficiently Refactoring the Data Clumps Model Smell: A Preliminary Study. In Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE; ISBN 978-989-758-696-5, SciTePress, pages 144-155. DOI: 10.5220/0012698000003687

in Bibtex Style

@conference{enase24,
author={Nils Baumgartner and Padma Iyenghar and Elke Pulvermüller},
title={Considerations in Prioritizing for Efficiently Refactoring the Data Clumps Model Smell: A Preliminary Study},
booktitle={Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE},
year={2024},
pages={144-155},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012698000003687},
isbn={978-989-758-696-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE
TI - Considerations in Prioritizing for Efficiently Refactoring the Data Clumps Model Smell: A Preliminary Study
SN - 978-989-758-696-5
AU - Baumgartner N.
AU - Iyenghar P.
AU - Pulvermüller E.
PY - 2024
SP - 144
EP - 155
DO - 10.5220/0012698000003687
PB - SciTePress