Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics

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...

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Bibliographic Details
Published inarXiv.org
Main Authors Synovic, Nicholas, Hyatt, Matt, Sethi, Rohan, Thota, Sohini, Shilpika, Miller, Allan J, Jiang, Wenxin, Amobi, Emmanuel S, Austin Pinderski, Läufer, Konstantin, Hayward, Nicholas J, Klingensmith, Neil, Davis, James C, Thiruvathukal, George K
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 24.07.2022
Subjects
Computer Science - Software Engineering
Decision making
Software
Software development
Source code
Spoilage
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Summary: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 https://youtu.be/YigEHy3_JCo. The source code can be found at https://github.com/SoftwareSystemsLaboratory/prime.
ISSN:2331-8422
DOI:10.48550/arxiv.2207.11767