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Software maintenance is a complex process that requires the understanding and comprehension of software project details. It involves the understanding of the evolution of the software project, hundreds of software components and the relationships among software items in the form of inheritance, interface implementation, coupling and cohesion. Consequently, the aim of evolutionary visual software analytics is to support software project managers and developers during software maintenance. It takes into account the mining of evolutionary data, the subsequent analysis of the results produced by the mining process for producing evolution facts, the use of visualizations supported by interaction techniques and the active participation of users. Hence, this paper proposes an evolutionary visual software analytics tool for the exploration and comparison of project structural, interface implementation and class hierarchy data, and the correlation of structural data with metrics, as well as socio-technical relationships. Its main contribution is a tool that automatically retrieves evolutionary software facts and represent them using a scalable visualization design.978-1-4577-0664-6/11/$26.00 ©2011 IEEE

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Visual analytics facilitates the creation of knowledge to interpret trends and relationships for better decision making. However, it has not being used widely for the understanding of software systems and the change process that takes place during their development and maintenance. This occurs despite the need of project managers and developers to analyze their systems to calculate the complexity, cohesion, direct, indirect and logical coupling, detect clones, defects and bad smells, and the comparison of individual revisions. This research considers the design of an extensible and scalable architecture to incorporate new and existing methods to retrieve source code from different versioning systems, to carry out the analysis of programs in different languages, to perform the calculation of software metrics and to present the results using visual representations, incorporated as Eclipse and Visual Studio extensions. Consequently, the aim of this work is to design a visual analytics architecture for the analysis and understanding of systems in different languages and its main contributions are the specification of the design and requirements of such architecture, taking as base the lessons learned in Maleku (A. González-Torres et al., 2016).