Exploring the combination of software visualization and data clustering in the software architecture recovery process
Renato Paiva, Genaína Nunes Rodrigues, Rodrigo Bonifácio, Marcelo Ladeira · 2016
Modernizing a legacy system is a costly process that requires deep understanding of the system architecture and its components. Without an understanding of the software architecture that will be rewritten, the entire process of reengineering can fail. For this reason, semi-automatic and automatic techniques for architecture recovery have been active focuses of research. However, there are still important improvements that need to be addressed on this field of research w.r.t. achieving a more accurate architecture recovery process. In this work, we propose to explore if an approach where visualization and clustering applied together can provide a higher accuracy on the software architecture recovery process. An experimental study was conducted in a industrial environment to empirically evaluate our investigation in four commercial systems. Our results indicated a statistically significant increase in the accuracy of the recovered architectures in all cases.