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Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics
ASE '22: Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering
  • Nicholas Synovic, Loyola University Chicago
  • Matt Hyattt, Loyola University Chicago
  • Rohan Sethi, Loyola University Chicago
  • Sohini Thota, Loyola University Chicago
  • Shilpika, University of California, Davis
  • Allan J. Miller, Loyola University Chicago
  • Wenxin Jiang, Purdue University
  • Emmanuel S. Amobi, Loyola University Chicago
  • Austin Pinderski, Loyola University Chicago
  • Konstantin Läufer, Loyola University Chicago
  • Nicholas J Hayward, Loyola University Chicago
  • Neil Klingensmith, Loyola University Chicago
  • James C Davis, Purdue University
  • George K Thiruvathukal, Loyola University Chicago
Document Type
Conference Proceeding
Publication Date
1-5-2023
Pages
1-4
Publisher Name
Association for Computing Machinery
Publisher Location
New York, NY
Abstract

Software metrics capture information about software development processes and products. These metrics support decision-making, e.g., in team management or dependency selection. However, existing metrics tools measure only a snapshot of a software project. Little attention has been given to enabling engineers to reason about metric trends over time -- longitudinal metrics that give insight about process, not just product. In this work, we present PRiME (PRocess MEtrics), a tool for computing and visualizing process metrics. The currently-supported metrics include productivity, issue density, issue spoilage, and bus factor. We illustrate the value of longitudinal data and conclude with a research agenda. The tool's demo video can be watched at this https URL. The source code can be found at this https URL.

Identifier
ISBN: 978-1-4503-9475-8
Comments

Author Posting. © Association for Computing Machinery, 2022. This is the author's version of the work. It is posted here by permission of the Association for Computing Machinery for personal use, not for redistribution. The definitive version was published in ASE '22: Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, Article No. 167, January 5 2023. https://doi.org/10.1145/3551349.3559517

Creative Commons License
Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International
Citation Information
Nicholas Synovic, Matt Hyatt, Rohan Sethi, Sohini Thota, Shilpika, Allan J. Miller, Wenxin Jiang, Emmanuel S. Amobi, Austin Pinderski, Konstantin Läufer, Nicholas J. Hayward, Neil Klingensmith, James C. Davis, George K. Thiruvathukal, "Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics", Proceedings of Automated Software Engineering 2022.