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

This 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. In this paper, 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.