Automatic Identification of Key Classes in a Software System Using Webmining Techniques

Software engineers new to a project are often stuck sorting through hundreds of classes in order to find those few classes that offer a significant insight into the inner workings of the software project. To help stimulate this process, we propose a technique which can identify the most important classes in a system, or the key classes of that system. Software engineers can use these classes to focus their understanding efforts when starting to work on a new software project. Those \emph{key classes} are typically characterized with having a lot of ``control'' within the application. In order to find these controlling classes, we present a detection approach that is based on dynamic coupling and webmining. We demonstrate the potential of our technique using two open source software systems, which have a rich documentation set. During the case studies we use dynamically gathered coupling information and vary between a number of coupling metrics. The case studies show that we are able to retrieve 90% of the classes deemed important by the orginal maintainers of the systems, while maintaining a level of precision of around 50%.