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A topology-shape-metrics approach for the automatic layout of UML class diagrams
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Proceedings of the 2003 ACM symposium on Software visualization table of contents
San Diego, California
SESSION: All things UML table of contents
Pages: 189 - ff  
Year of Publication: 2003
ISBN:1-58113-642-0
Authors
Markus Eiglsperger  Universität Tübingen
Michael Kaufmann  Universität Tübingen
Martin Siebenhaller  Universität Tübingen
Sponsors
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
SIGSOFT: ACM Special Interest Group on Software Engineering
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
SIGPLAN: ACM Special Interest Group on Programming Languages
Publisher
ACM  New York, NY, USA
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ABSTRACT

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.


REFERENCES

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Collaborative Colleagues:
Markus Eiglsperger: colleagues
Michael Kaufmann: colleagues
Martin Siebenhaller: colleagues

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