Improving defect prediction using temporal features and non linear models
Abraham Bernstein, Jayalath Bandara Ekanayake, Martin Pinzger · 2007
Predicting the defects in the next release of a large software system is a very valuable asset for the project manger to plan her resources. In this paper we argue that temporal features (or aspects) of the data are central to prediction performance. We also argue that the use of non-linear models, as opposed to traditional regression, is necessary to uncover some of the hidden interrelationships between the features and the defects and maintain the accuracy of the prediction in some cases.