Richard Delwin Myloth

Software Change Risk Prediction Using Supervised Machine Learning and Feature Impact Analysis

Predicting risky software changes before deployment can help prioritize code review and testing, particularly in continuous integration and continuous deployment (CI/CD) environments. This paper presents an interpretable supervised learning framework for commit-level software change risk prediction using structural, hi...