Predicting fault-prone classes with design measures in object-oriented systems

Abstract

The paper aims at empirically exploring the relationships between existing object oriented coupling, cohesion, and inheritance measures and the probability of fault detection in system classes during testing. The underlying goal of such a study is to better understand the relationship between existing product measurement in OO systems and the quality of the software developed. It is shown that by using a subset of existing measures, accurate models can be built to predict in which classes most of the faults are likely to lie in. By inspecting 48% of the classes, it is possible to find 95% of the faults. Besides the size of classes, the frequency of method invocations and the depth of inheritance hierarchies seem to be the main driving factors of fault proneness.