Explorando a combinação de visualização de software com clusterização de dados em um processo de reconstrução de arquitetura

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. When there is absence of architectural documents, it is important to have a recovery process of architecture that allows the complete understanding of the software. Such process involves mapping of source code entities in high-level models. Previous work using visualization and clustering techniques has been proposed and extensively used. However, there is still important improvements that need to be addressed based on this theme. Thus, this work proposes 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 to empirically evaluate our investigation. The results indicated a statistically significant increase in the accuracy of the models produced.