This dashboard provides an overview of the data from projects imported on the Keypup platform. It aims at providing an evaluation of the cleanness and consistency of data in the projects.
It can be used to break down engineering data by points of interest: projects, contributors, pull requests, and issues and allows to:
Understand the company’s habits in regard to its development processes (labeling convention, commits messages, issue scoping…)
Know what data you can work with to customize your Keypup metrics (e.g. adapt labels in insight filters, apply insights on specific projects or contributors, target repositories…)
Know how the engineering teams behave to fix potential deviations from development standards and processes.
Insights
Auto-closing ratio: This insight measures the ratio of pull requests resolving at least one issue, ensuring a consistent development process through the linking and closing issues through pull requests.
Commit keyword usage: This insight allows one to discover team habits when writing commit messages.
Contributors list: This insight lists all contributors across connected projects, based on the number of issues and pull requests they have created.
Issue labeling: This insight uncovers all used labels in issues and identifies their usage ratio as well as how they are used in combination with each other.
Issue labeling breakdown: This insight is best used to deep-dive into Issues labeling.
PR labeling: This insight uncovers all used labels in pull requests and identifies their usage ratio as well as how they are used in combination with each other.
PR labeling breakdown: This insight is best used to deep-dive into Pull requests labeling.
Projects overview: The report provides quantitative measures that help understand the project's mapping and how work is spread across various projects.
Scoped issues ratio: This insight counts the ratio of issues that have a description to ensure that all parties (product, support, marketing and engineering teams) have the same level of information and act consistently around feature delivery.