TensorFlow

Mean and median duration (days) of all closed reviews

This heat map compares the responsiveness of a repository to reviews (pull requests and merge requests). The light blue indicates review response times that are fastest; the red indicates the time slots with slowest response times. White boxes indicate time slots in which no reviews were closed. The minimum and maximum are determined by the pool of repositories within the report. For GitHub repositories, both accepted and declined pull requests are taking into account. For GitLab repositories, only the declined are being shown.

Metric inspired by the report, and

# Issues created/closed

Number of issues shows activity in the issue tracking system, usually including bug reports, feature requests, and other tasks that are tracked with issues (tickets). We measure, for each week, the number of issues that were opened (created) or closed during it. Not only the absolute numbers, but also the relationship between open and closed issues is important in this chart: if many more issues are consistently being opened than closed, the report is not dealing with all the new stuff that is entering the issue tracking system.

Drive-through and repeat contributor counts

This graph shows the number of new contributors in the specified time period and indicates how may were drive-through or repeat contributors. Drive-through contributors are contributors who make less than the required 5 contributions in the specified time period. Repeat contributors are contributors who made 5 or more contributions in the specified time period and their first contribution is in the specified time period.

Metric inspired by the report, and

# Commits by hour and weekday

The heatmap shows what times of day contributors in their local time zone contribute. Activity that clusters between regular office hours on workdays can indicate activity by contributors who do this as part of their job. Activity during evenings and weekends can indicate volunteer activity.