Proceedings of International Conference on Applied Innovation in IT
2023/03/09, Volume 11, Issue 1, pp.81-87

Software Metrics Visualization


Vira Liubchenko


Abstract: Software engineering is an empirical field of study. To support managerial and technical decision-making, the engineer needs numerical measures closely connected with different software metrics. Visual representation of numerical data improves the effectiveness of human data processing and shows insights that humans may miss. This paper aims to provide a systematic review of the approaches for software metrics visualization and define the possible recommendation for their use. The study is based on the literature review of the papers from two text collections – IEEE Xplore and ACM Digital Library – and the scientometric database Scopus. After merging and filtering, the final set of publications contains 16 papers. Our study showed that there were the metrics used significantly more often; among them are lines-of-code, cyclomatic complexity, coupling, and cohesion. We were not able to identify such leaders for visualization means. Instead, there was a tendency to combine different metrics on one chart or dashboard to provide the whole process picture. Based on the results of empirical studies reported in the literature, we offered an analysis of simple charts’ properties and recommendations on their use for support decision-making in the software engineering process.

Keywords: Metrics, Software, Visualization, Data, Diagrams, Analysis, Decision Making, Effectiveness.

DOI: 10.25673/101921

Download: PDF

References:

  1. M. Balzer, O. Deussen, and C. Lewerentz, “Voronoi treemaps for the visualization of software metrics,” in Proceedings of the ACM symposium on Software visualization (SoftVis '05), pp. 165-172, 2005.
  2. H. Byelas and A. Telea, “The metric lens: visualizing metrics and structure on software diagrams,” in 15th Working Conference on Reverse Engineering, pp. 339-340, 2008.
  3. A. Gonzalez, R. Theron, A. Telea, and F. J. Garcia, “Combined visualization of structural and metric information for software evolution analysis,” in Proceedings of the joint international and annual ERCIM workshops on Principles of software evolution (IWPSE) and software evolution (Evol) workshops (IWPSE-Evol '09), pp. 25-30, 2009.
  4. R. Francese, M. Risi, and G. Scanniello, “Enhancing software visualization with information retrieval,” in 19th International Conference on Information Visualisation, pp. 189-194, 2015.
  5. B. Popović, A. Balota, and D. Strujić, “Visual representation of predictions in software development based on software metrics history data,” in 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 352-357, 2016.
  6. T. Brunner and Z. Porkoláb, “Two-dimensional visualization of software metrics,” in Proceedings of the Sixth Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, pp. 2:1-2:6, 2017.
  7. M. Alnabhan, A. Hammouri, M. Hammad, M. Atoum, and O. Al-Thnebat, “2D visualization for object-oriented software systems,” in International Conference on Intelligent Systems and Computer Vision (ISCV), pp. 1-6, 2018.
  8. J. Slater, C. Anslow, J. Dietrich, and L. Merino, “CorpusVis - visualizing software metrics at scale,” in Working Conference on Software Visualization (VISSOFT), pp. 99-109, 2019.
  9. G. Lacerda, F. Petrillo, and M. S. Pimenta, “DR-Tools: a suite of lightweight open-source tools to measure and visualize Java source code,” in IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 802-805, 2020.
  10. H. Mumtaz, F. Beck, and D. Weiskopf, “Detecting bad smells in software systems with linked multivariate visualizations,” in IEEE Working Conference on Software Visualization (VISSOFT), pp. 12-20, 2018.
  11. A. Yusuf and M. Hammad, “An approach to automatically measure and visualize class cohesion in object-oriented systems,” in International Conference on Decision Aid Sciences and Application (DASA), pp. 1174-1179, 2020.
  12. A. Yusuf and M. Hammad, “An automatic approach to measure and visualize coupling in object-oriented programs,” in International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICT), pp. 1-6, 2020.
  13. Y. Muto, K. Okano, and S. Kusumoto, “A visualization technique for unit testing and static checking with caller–callee relationships,” Journal of Convergence, vol. 2(2), pp. 1-8, 2011.
  14. M. Pinzger, H. Gall, M. Fischer, and M. Lanza, “Visualizing multiple evolution metrics,” in Proceedings of the ACM symposium on Software visualization (SoftVis '05), pp. 67-75, 2005.
  15. A. Kerren and I. Jusufi, “Novel visual representations for software metrics using 3D and animation,” in Software Engineering, J. Münch and P. Liggesmeyer, Hrsg. Bonn: Gesellschaft für Informatik e.V., 2009, pp. 147-154.
  16. S. R. Humayoun, S. M. Hasan, R. AlTarawneh, and A. Ebert, “Visualizing software hierarchy and metrics over releases,” in Proceedings of the International Conference on Advanced Visual Interfaces (AVI '18),” Article 40, pp. 1-5, 2018.
  17. X. Bai, D. White, and D. Sundaram, “Context adaptive visualization for effective business intelligence,” in 15th IEEE International Conference on Communication Technology, pp. 786-790, 2013.
  18. B. Saket, A. Endert, and Ç. Demiralp, “Task-Based Effectiveness of Basic Visualizations,” in IEEE Transactions on Visualization and Computer Graphics, vol. 25(7), pp. 2505-2512, 2019.
  19. G. J. Quadri and P. Rosen, “A survey of perception-based visualization studies by task,” in IEEE Transactions on Visualization and Computer Graphics, vol. 28(12), pp. 5026-5048, 2022.

    HOME

       - Call for Papers
       - Paper Submission
       - For authors
       - Important Dates
       - Conference Committee
       - Editorial Board
       - Reviewers
       - Last Proceedings


    PROCEEDINGS

       - Volume 12, Issue 1 (ICAIIT 2024)        - Volume 11, Issue 2 (ICAIIT 2023)
       - Volume 11, Issue 1 (ICAIIT 2023)
       - Volume 10, Issue 1 (ICAIIT 2022)
       - Volume 9, Issue 1 (ICAIIT 2021)
       - Volume 8, Issue 1 (ICAIIT 2020)
       - Volume 7, Issue 1 (ICAIIT 2019)
       - Volume 7, Issue 2 (ICAIIT 2019)
       - Volume 6, Issue 1 (ICAIIT 2018)
       - Volume 5, Issue 1 (ICAIIT 2017)
       - Volume 4, Issue 1 (ICAIIT 2016)
       - Volume 3, Issue 1 (ICAIIT 2015)
       - Volume 2, Issue 1 (ICAIIT 2014)
       - Volume 1, Issue 1 (ICAIIT 2013)


    PAST CONFERENCES

       ICAIIT 2024
         - Photos
         - Reports

       ICAIIT 2023
         - Photos
         - Reports

       ICAIIT 2021
         - Photos
         - Reports

       ICAIIT 2020
         - Photos
         - Reports

       ICAIIT 2019
         - Photos
         - Reports

       ICAIIT 2018
         - Photos
         - Reports

    ETHICS IN PUBLICATIONS

    ACCOMODATION

    CONTACT US

 

DOI: http://dx.doi.org/10.25673/115729


        

         Proceedings of the International Conference on Applied Innovations in IT by Anhalt University of Applied Sciences is licensed under CC BY-SA 4.0


                                                   This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License


           ISSN 2199-8876
           Publisher: Edition Hochschule Anhalt
           Location: Anhalt University of Applied Sciences
           Email: leiterin.hsb@hs-anhalt.de
           Phone: +49 (0) 3496 67 5611
           Address: Building 01 - Red Building, Top floor, Room 425, Bernburger Str. 55, D-06366 Köthen, Germany

        site traffic counter

Creative Commons License
Except where otherwise noted, all works and proceedings on this site is licensed under Creative Commons Attribution-ShareAlike 4.0 International License.