In this thesis we present a novel approach to the analysis of dependency graphs of object-oriented programs, and we describe a tool that has been implemented for this purpose. A graph-theoretical clustering algorithm is used in order to compute the modular structure of programs. This can be used to assist software engineers to redraw component boundaries in software in order to improve the level of reuse and maintainability. The analysis of the dependency graph of an object-oriented program is useful for assessing the quality of software design. The dependency graph can be extracted from a program using various different methods, including source code, byte code, and dynamic (behavioral) analysis. The nodes in the dependency graph are classes, members, packages and other artifacts, while the edges represent uses and extends relationships between those artifacts. Once the dependency graph has been extracted, it can be analysed in order to quantify certain characteristics of the respective program. Examples include the detection of circular dependencies and measurements of the responsibility or independence of units based on their relationships. Tools like JDepend1 implementing these principles have become very popular in recent years. Our work includes grouping types in dependency graphs using di erent clustering methods: Grouping into namespaces; Grouping into clusters using graph clustering algorithms; Grouping into clusters using rules. The detected mismatches are candidates for refactoring. We have developed a tool for processing dependency graphs clustering and producing results where users can outline possible design violations.