In this part of the book Data Science for Software Engineering: Sharing Data and Models, we offer some tutorial notes on commonly used software engineering applications of data mining, along with some tutorial material on data mining algorithms. Covered topics of SE problems include effort estimation and defect prediction. Covered aspects of data mining include discretization, column pruning (also known as feature selection), row pruning, clustering, contrast set learning, decision learning, and learning for continuous classes.
Defect prediction is the study of predicting which software “modules” are defective. Here “modules” means some primitive unit of a running system such as a function or a class. ...
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