The goal of software visualization is to acquire sufficient knowledge about a software system by identifying program artifacts and understanding their relationships. Graphical representations have long been recognized as having an important impact in improving the comprehension of source code. In this paper, we present several visualization techniques that we combine with analytical source code analysis to reduce the amount and, therefore, the complexity of data that has to be displayed. In particular, we focus on static and dynamic program slicing and apply this source code analysis technique on treemaps, Hyperbolic trees, and UML based visualization techniques to support programmers in creating better mental models of the source code. We also introduce our CONCEPT prototype and describe how the presented approaches can be applied to reduce the information complexity for particular source code comprehension applications.