Software Architecture Mining from Source Code with Dependency Graph Clustering and Visualization

Anthony Savidis, Anthony Savidis, Crystallia Savaki

2022

Abstract

The software architecture represents an important asset, constituting a shared vision amongst the software engineers of the various system components. Good architectures link to modular design, with loose coupling and cohesion defining which operations are grouped together to form a modular architectural entity. Modularity is achieved by practice otherwise we may observe a mismatch where the source code diverges from the primary architectural vision. In fact, class groups with dense interdependencies denote the real architectural entities as derived and implied directly from source code. In this work, we created a tool to assist in mining the actual system architecture. We extract all sorts of dependencies by processing all source files, and then using graph clustering, we capture and interactively visualize strongly coupled class groups with configurable weights. We also support forced clustering on namespaces, packages and folders.

Paper Citation

in Harvard Style

Savidis A. and Savaki C. (2022). Software Architecture Mining from Source Code with Dependency Graph Clustering and Visualization. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 3: IVAPP; ISBN 978-989-758-555-5, SciTePress, pages 179-186. DOI: 10.5220/0010896800003124

in Bibtex Style

@conference{ivapp22,
author={Anthony Savidis and Crystallia Savaki},
title={Software Architecture Mining from Source Code with Dependency Graph Clustering and Visualization},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 3: IVAPP},
year={2022},
pages={179-186},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010896800003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 3: IVAPP
TI - Software Architecture Mining from Source Code with Dependency Graph Clustering and Visualization
SN - 978-989-758-555-5
AU - Savidis A.
AU - Savaki C.
PY - 2022
SP - 179
EP - 186
DO - 10.5220/0010896800003124
PB - SciTePress