A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique.

Detecting code smells may be highly helpful for reducing maintenance costs and raising source code quality. Code smells facilitate developers or researchers to understand several types of design flaws. Code smells with high severity can cause significant problems for the software and may cause challenges for the system's maintainability.