Smell-ML: A Machine Learning Framework for Detecting Rarely Studied Code Smells

Smell-ML: A Machine Learning Framework for Detecting Rarely Studied Code Smells

Code smells are design flaws that reduce the software quality and maintainability. Machine learning classification models have been used to detect different code smells. However, such studies targeted code smells in depth, while leaving other under-explored smells; even so, such smells have a signif...

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Bibliographic Details
Main Authors: Esraa Hamouda, Abeer El-Korany, Soha Makady
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Code smell detection
machine learning
data balancing
ensemble learning
multi-level classification
Online Access:https://ieeexplore.ieee.org/document/10844273/
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https://ieeexplore.ieee.org/document/10844273/

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