Comprehension of software analysis data using 3D visualization

The paper presents a software visualization application-framework that utilizes a variety of 3D metaphors to represent large software system and related analysis data. The 3D representation is based on the SeeSoft pixel representation and extends that original metaphor by rendering the visualization in a 3D space. Object-based manipulation methods and simultaneous alternative mappings are available to the user. The visual elements, mappings, and user interactions implemented and used by the framework are described with respect to their support for software understanding tasks. Examples are presented and discussed to demonstrate how the system's current features support the needs of the user.

[1]  Stephen G. Eick,et al.  Visual Discovery and Analysis , 2000, IEEE Trans. Vis. Comput. Graph..

[2]  Andrian Marcus,et al.  A task oriented view of software visualization , 2002, Proceedings First International Workshop on Visualizing Software for Understanding and Analysis.

[3]  Blaine A. Price,et al.  A Principled Taxonomy of Software Visualization , 1993, J. Vis. Lang. Comput..

[4]  Colin Ware,et al.  Viewing a graph in a virtual reality display is three times as good as a 2D diagram , 1994, Proceedings of 1994 IEEE Symposium on Visual Languages.

[5]  Geoffrey S. Hubona,et al.  3D object recognition with motion , 1997, CHI Extended Abstracts.

[6]  Steven F. Roth,et al.  SDM: selective dynamic manipulation of visualizations , 1995, UIST '95.

[7]  William G. Griswold,et al.  Exploiting the map metaphor in a tool for software evolution , 2001, Proceedings of the 23rd International Conference on Software Engineering. ICSE 2001.

[8]  Cristina Russo Dos Santos,et al.  Mapping information onto 3D virtual worlds , 2000, 2000 IEEE Conference on Information Visualization. An International Conference on Computer Visualization and Graphics.

[9]  Jason Leigh,et al.  Visualizing object-oriented software in virtual reality , 2001, Proceedings 9th International Workshop on Program Comprehension. IWPC 2001.

[10]  Gruia-Catalin Roman,et al.  A taxonomy of program visualization systems , 1993, Computer.

[11]  Martin Graham,et al.  A comparison of set-based and graph-based visualisations of overlapping classification hierarchies , 2000, AVI '00.

[12]  Daniel A. Keim,et al.  Pixel bar charts: a visualization technique for very large multi-attribute data sets? , 2002, Inf. Vis..

[13]  Jean-Marie Favre.  A Flexible Approach to Visualize Large Software Products , 2001 .

[14]  Stephen G. Eick,et al.  Seesoft-A Tool For Visualizing Line Oriented Software Statistics , 1992, IEEE Trans. Software Eng..

[15]  Margaret-Anne D. Storey,et al.  SHriMP views: an interactive environment for exploring Java programs , 2001, Proceedings 9th International Workshop on Program Comprehension. IWPC 2001.

[16]  Gregor Kiczales,et al.  Overcoming the Prevalent Decomposition in Legacy Code , 2001 .

[17]  Steven P. Reiss.  Bee/Hive: A Software Visualization Back End , 2001 .

[18]  Mats Lind,et al.  2D vs 3D, implications on spatial memory , 2001, IEEE Symposium on Information Visualization, 2001. INFOVIS 2001..

[19]  Malcolm Munro,et al.  Comprehension with[in] virtual environment visualisations , 1999, Proceedings Seventh International Workshop on Program Comprehension.

[20]  Colin Ware,et al.  Visualizing object oriented software in three dimensions , 1993, CASCON.

[21]  Ben Shneiderman,et al.  Readings in information visualization - using vision to think , 1999 .

[22]  John Stasko,et al.  Visualization for Fault Localization , 2003 .

[23]  Thomas Ball,et al.  Software Visualization in the Large , 1996, Computer.