Software Forest: A Visualization of Semantic Similarities in Source Code using a Tree Metaphor

Daniel Atzberger, Tim Cech, Merlin de La Haye, Maximilian Söchting, Willy Scheibel, Daniel Limberger, Jürgen Döllner

2021

Abstract

Software visualization techniques provide effective means for program comprehension tasks as they allow developers to interactively explore large code bases. A frequently encountered task during software development is the detection of source code files of similar semantic. To assist this task we present Software Forest, a novel 2.5D software visualization that enables interactive exploration of semantic similarities within a software system, illustrated as a forest. The underlying layout results from the analysis of the vocabulary of the software documents using Latent Dirichlet Allocation and Multidimensional Scaling and therefore reflects the semantic similarity between source code files. By mapping properties of a software entity, e.g., size metrics or trend data, to visual variables encoded by various, figurative tree meshes, aspects of a software system can be displayed. This concept is complemented with implementation details as well as a discussion on applications.

Paper Citation

in Harvard Style

Atzberger D., Cech T., de La Haye M., Söchting M., Scheibel W., Limberger D. and Döllner J. (2021). Software Forest: A Visualization of Semantic Similarities in Source Code using a Tree Metaphor. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP; ISBN 978-989-758-488-6, SciTePress, pages 112-122. DOI: 10.5220/0010267601120122

in Bibtex Style

@conference{ivapp21,
author={Daniel Atzberger and Tim Cech and Merlin de La Haye and Maximilian Söchting and Willy Scheibel and Daniel Limberger and Jürgen Döllner},
title={Software Forest: A Visualization of Semantic Similarities in Source Code using a Tree Metaphor},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP},
year={2021},
pages={112-122},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010267601120122},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP
TI - Software Forest: A Visualization of Semantic Similarities in Source Code using a Tree Metaphor
SN - 978-989-758-488-6
AU - Atzberger D.
AU - Cech T.
AU - de La Haye M.
AU - Söchting M.
AU - Scheibel W.
AU - Limberger D.
AU - Döllner J.
PY - 2021
SP - 112
EP - 122
DO - 10.5220/0010267601120122
PB - SciTePress