Science & Engineering Research Support soCiety (SERSC)
In this paper, the authors present an innovative metric based on a class abstraction to capture aspects of software complexity through combinations of class characteristics. The study also used software metrics effectiveness in finding the classes in different error categories for the three versions of Eclipse, the Java-based open-source integrated development environment. Many studies used logistic regression models to investigate the ability of OO software metrics to predict fault prone classes. They also used this method not only for binary but also multinomial categorization and empirically validate the ability of metrics to predict fault prone classes in different category using fault data.