Class diagrams are among the most popular visualizations for object oriented software systems and have a broad range of applications. In many settings it is desirable that the placement of the diagram elements is determined automatically, especially when the diagrams are generated automatically which is usually the case in reverse engineering. For this reason the automatic layout of class diagram gained importance in the last years. Current approaches for the automatic layout of class diagrams are based on the hierarchic graph drawing paradigm. These algorithms produce good results for class diagrams with large and deep structural information, i.e., diagrams with a large and deep inheritance hierarchy. However, they do not perform satisfactorily in absence of this information. We propose in this work a new algorithm for automatic layout of class diagram which is based on the topology-shape-metrics approach. The algorithm is an adaption of sophisticated graph drawing algorithms which have proven their effectiveness in many applications. The algorithm works as well for class diagrams with rich structural information as for class diagrams with few or no structural information. It improves therefore the existing algorithms significantly. An implementation of the algorithm is used in the reverse engineering tool JarInspector.

In this paper, we present a new compaction algorithm which computes orthogonal drawings where the size of the vertices is given as input. This is a critical constraint for many practical applications like UML. The algorithm provides a drastic improvement on previous approaches. It has linear worst case running time and experiments show that it performs very well in practice.

We discuss the algorithm engineering aspects of AGD, a software library of algorithms for graph drawing. AGD represents algorithms as classes that provide one or more methods for calling the algorithm. There is a common base class, also called the type of an algorithm, for algorithms providing basically the same functionality. This enables us to exchange components and experiment with various algorithms and implementations of the same type. We give examples for algorithm engineering with AGD for drawing general non-hierarchical graphs and hierarchical graphs.