Using measurement-driven modeling to provide empirical feedback to software developers

Several authors have explored the application of classification methods to software development. These studies have concentrated on identifying modules that are difficult to develop or that have high fault density. While this information is important, it provides little help in determining appropriate corrective action. This article extends previous work by applying one classification method, classification tree analysis (CTA), to more a fine-grained problem routinely encountered by developers. In this article, we use CTA to identify software modules that have specific types of faults (e.g., logic, interface, etc.) We evaluate this approach using data collected from six actual software projects. Overall, CTA was able to correctly differentiate faulty modules from fault-free modules in 72% of cases. Furthermore, 82% of the faulty modules were correctly identified. We also show that CTA outperformed two simpler classification strategies.