Software metrics capture information about software development products and processes. 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 Internal 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 demo video can be found at https://youtu.be/YigEHy3_JCo. The source code can be found at https://github.com/SoftwareSystemsLaboratory/prime.

Nicholas Synovic

Loyola University Chicago

United States

Matt Hyatt

Loyola University Chicago

Rohan Sethi

Loyola University Chicago

Sohini Thota

Loyola University Chicago

Shilpika

University of California at Davis

Allan J. Miller

Loyola University Chicago

Wenxin Jiang

Purdue University

Emmanuel S. Amobi

Loyola University Chicago

Austin Pinderski

Duke University, Loyola University Chicago

Konstantin Läufer

Loyola University Chicago

United States

Nicholas J. Hayward

Loyola University Chicago

Neil Klingensmith

Loyola University Chicago

James C. Davis

Purdue University, USA

United States

George K. Thiruvathukal

Loyola University Chicago and Argonne National Laboratory