In the current information technology society we are relying more and more on software systems. Maintenance has been identified to be the primary factor of the total cost of large software systems (more than 90% of the total cost). One of the key difficulties encountered in software maintenance is given by the intrinsic complexity of those systems, whose size can easily reach the tens of millions of lines of source code. Software complexity is recognized as one of the major challenges to the development and maintenance of industrial size software projects.
To that respect, the key aspect of software is that it is a virtual product. In other words, it is difficult to grasp the full complexity of a system that one cannot see or touch. However, many attempts to visually represent the structure of software systems have been proposed, essentially through flat representations. However, the quantity of information that can be represented in 2D drawings is limited. Handling the complexity and observing the evolution of very large software systems needs the analysis of large complex data models and the creation of condensed views of the system. In the context of visualization, software metrics have been used to compute and enrich such condensed views. However, current techniques concentrate on visualizing data of one particular software release, providing insufficient support for visualizing data of several releases. The goal of this project is to exploit multi-dimensional navigation spaces to efficiently visualize evolving software systems.