A Comprehensive Empirical Validation of Product Measures for 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. Results show that many of the measures capture similar dimensions in the dataset, thus reflecting the fact that many of them are based on similar principles and hypotheses. However, it is shown that by using a subset of measures, accurate models can be built to predict in which classes most of the faults are likely to lie in. By inspecting an amount of code comparable to the one contained in faulty classes, it is possible to find between 90% and 95% of the faults, depending on the type of model validation considered. Besides the size of classes, the frequency of method invocation and the depth of inheritance hie rarchies seem to be the main driving factors of fault proneness