Machine Learning Powered Code Smell Detection as a Business Improvement Tool

2023 IEEE 64th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2023): Proceedings 2023
Markuss Siksna, Ilze Berzina, Andrejs Romānovs

Code smell represents the level of human interpretability in a software project, which becomes increasingly challenging as modern-day software projects grow in complexity. Machine learning has promising signs of solving the problem of code smell detection but will ultimately be limited by the training dataset of the model. This paper investigates some machine learning approaches for code smell detection, the implications of using such a system, integration with business processes and how such a system would fit into IT governance using Latvia as an example.

Atslēgas vārdi
business improvement , code smells , machine learning , technical debt
DOI
10.1109/ITMS59786.2023.10317724
Hipersaite
https://ieeexplore.ieee.org/document/10317724

Siksna, M., Berzina, I., Romānovs, A. Machine Learning Powered Code Smell Detection as a Business Improvement Tool. No: 2023 IEEE 64th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2023): Proceedings, Latvija, Riga, 5.-6. oktobris, 2023. Piscataway, NJ: IEEE, 2023, 1.-6.lpp. ISBN 979-8-3503-7030-0. e-ISBN 979-8-3503-7029-4. ISSN 2771-6953. e-ISSN 2771-6937. Pieejams: doi:10.1109/ITMS59786.2023.10317724

Publikācijas valoda
English (en)