CLIME: Command Line Metrics for Git Projects

Numerous efforts in repository mining have focused
on mining repositories and reporting basic metrics. Many efforts
are focused on being able to evaluate (or score) projects based
on these metrics. Yet little attention has been given to in-
process metrics, which are a critical tool for improving software
quality as agile projects become more established projects and
require regular maintenance. We present CLIME (Command Line
Metrics), a user-installable toolset for computing a wide variety
of classical and modern process metrics, including code size,
issue spoilage, issue/defect density, productivity, and bus factor.
CLIME also includes a tool to identify projects based on criteria
such as active issues, forks, stars, and topics to identify projects
for a prospective case study in science and engineering research
software projects. A key design goal of CLIME is to put users in
control by offering a lean toolset that places emphasis on sim-
simplicity over the speed with a serverless design that ingests computes,
and visualizes process metrics with a simple installation process
and minimal configuration. Users can run all software locally
and install it without administrative privileges in a Python virtual
environment. All code in CLIME is maintained on GitHub and
deployed to PyPI via GitHub Actions.