The Research Group is Moving!

During winter term 2021/22, we move to University of Bamberg. From Oct. 15, 2021, Fabian Beck holds a full professor position on Information Visualization.

New webpage of the research group: https://www.uni-bamberg.de/vis

Publications

Publications of the research group since 2016. For earlier publications, please visit Fabian Beck's Google Scholar or DBLP profile.

Identifying Modularization Patterns by Visual Comparison of Multiple Hierarchies

Type of Publication: Article in Collected Edition

Identifying Modularization Patterns by Visual Comparison of Multiple Hierarchies

Author(s):
Beck, Fabian; Melcher, Jan; Weiskopf, Daniel
Title of Anthology:
Proceedings of the 2016 IEEE 24th International Conference on Program Comprehension
pages:
1-10
Publisher:
IEEE
Publication Date:
2016
Digital Object Identifier (DOI):
doi:10.1109/ICPC.2016.7503712
Fulltext:
Identifying Modularization Patterns by Visual Comparison of Multiple Hierarchies (1.51 MB)
Citation:
Download BibTeX

Abstract

Software is modularized to make its high complexity manageable. However, a multitude of modularization criteria exists and is applied. Hence, to extend, reuse, or restructure a system, it is important for developers to understand which criteria have been used. To this end, we provide an interactive visualization approach that compares the current modularization of a system to several software clustering results. The visualization is based on juxtaposed icicle plot representations of the hierarchical modularizations, encoding similarity by color. A detailed comparison is facilitated by an advanced selection concept. Coupling graphs, which form the basis for software clustering, can be explored on demand in matrix representations. We discuss typical modularization patterns that indicate criteria used for structuring the software or suggest opportunities for partial remodularization of the system. We apply the approach to analyze 16 open source Java projects. The results show that identifying those modularization patterns provides valuable insights and can be done efficiently.