Empirical analysis of entropy distance metric for UML class diagrams
Tong Yi, Fangjun Wu · ACM SIGSOFT Software Engineering Notes · 2004
Many software systems built in recent years have been developed using the UML and, in some cases, they already need adaptive maintenance in order to satisfy market and customer needs. Thus a strong emphasis on analysis metrics for software development is necessary. Analysis metrics play an important role in helping developers understand software and, hence, improve software quality and developer productivity. In this paper, we provide empirical evidence for supporting the role of the structure complexity metrics for UML class diagrams, specifically Zhou 's metric. Our results, based on data related with bank information system, indicate that the metric is basically consistent with human beings' intuitions.