Title :
SArF map: Visualizing software architecture from feature and layer viewpoints
Author :
Kobayashi, Kaoru ; Kamimura, Manabu ; Yano, Ken´ichi ; Kato, Kazuhiko ; Matsuo, Akihiko
Author_Institution :
Software Syst. Labs., Fujitsu Labs. Ltd., Kawasaki, Japan
Abstract :
To facilitate understanding the architecture of a software system, we developed SArF Map technique that visualizes software architecture from feature and layer viewpoints using a city metaphor. SArF Map visualizes implicit software features using our previous study, SArF dependency-based software clustering algorithm. Since features are high-level abstraction units of software, a generated map can be directly used for high-level decision making such as reuse and also for communications between developers and non-developer stakeholders. In SArF Map, each feature is visualized as a city block, and classes in the feature are laid out as buildings reflecting their software layer. Relevance between features is represented as streets. Dependency links are visualized lucidly. Through open source and industrial case studies, we show that the architecture of the target systems can be easily overviewed and that the quality of their packaging designs can be quickly assessed.
Keywords :
decision making; program visualisation; reverse engineering; software architecture; SArF dependency-based software clustering algorithm; SArF map; city block; city metaphor; dependency links; high-level abstraction units; high-level decision making; reuse; software architecture visualization; software feature viewpoints; software layer viewpoints; software system architecture understanding; Buildings; Cities and towns; Clustering algorithms; Layout; Software; Software algorithms; Visualization; Software visualization; city metaphor; dependency graph; program comprehension; software architecture; software clustering;
Conference_Titel :
Program Comprehension (ICPC), 2013 IEEE 21st International Conference on
Conference_Location :
San Francisco, CA
DOI :
10.1109/ICPC.2013.6613832