Software visualizations can provide a concise overview of a complex software system. Unfortunately, since software has no physical shape, there is no natural'' mapping of software to a two-dimensional space. As a consequence most visualizations tend to use a layout in which position and distance have no meaning, and consequently layout typical diverges from one visualization to another. We propose a consistent layout for software maps in which the position of a software artifact reflects its vocabulary, and distance corresponds to similarity of vocabulary. We use latent semantic indexing (LSI) to map software artifacts to a vector space, and then use multidimensional scaling (MDS) to map this vector space down to two dimensions.The resulting consistent layout allows us to develop a variety of thematic software maps that express very different aspects of software while making it easy to compare them. The approach is especially suitable for comparing views of evolving software, since the vocabulary of software artifacts tends to be stable over time.
Understanding complex software systems requires getting insight in how system properties, such as performance, trust, reliability, or structural attributes, correspond to the system architecture. Such properties can be seen as defining several 'areas of interest' over the system architecture. We visualize areas of interest atop of system architecture diagrams using a new technique that minimizes visual clutter for multiple, overlapping areas for large diagrams, yet preserves the diagram layout familiar to designers. We illustrate our proposed techniques on several UML diagrams of complex, real-world systems.