The prediction of faulty classes using object-oriented design metrics

Contemporary evidence suggests that most field faults in software applicati ons are found in a small percentage of the software's components. This mean s that if these faulty software components can be detected early in the dev elopment project's life cycle, mitigating actions can be taken, such as a r edesign. For object-oriented applications, prediction models using design m etrics can be used to identify faulty classes early on. In this paper we re port on a study that used object-oriented design metrics to construct such prediction models. The study used data collected from one version of a comm ercial Java application for constructing a Prediction model. The model was then validated on a subsequent release of the same application. Our results indicate that the prediction model has a high accuracy. Furthermore, we fo und that an export coupling (EC) metric had the strongest association with fault-proneness, indicating a structural feature that may be symptomatic of a class with a high probability of latent faults. (C) 2001 Elsevier Scienc e Inc. All rights reserved.