A code quality dashboard that links PRs to the bugs they cause

Most code quality dashboards show you a wall of static scores: a coverage percentage, a complexity number, a linter grade. They tell you what a file looks like today, but nothing about whether the changes you merged last month held up. FeatureFactory reframes the question around outcomes - did this pull request stay stable, or did it come back as a bug, a revert, or an incident?

The dashboard tracks quality as a trend, not a snapshot. You watch escaped-defect rate, review depth, and change size move together over weeks and releases, so you can tell whether a new process or a new tool is genuinely helping. It is the difference between a report card and a control panel. If you care about the underlying signals, our engineering metrics and DORA metrics tracking pages show how these numbers connect.

Because the data is customer-owned and transparent, there are no vanity gates that punish engineers after the fact - just guardrails that surface risk early. That is the same measured, developer-led approach we take across the whole measure product.

The most valuable thing a quality dashboard can tell you is which change caused the problem you are firefighting right now. FeatureFactory correlates each merged pull request with the commits, hotfixes, reverts, and incidents that touch the same files and services afterward. When a fix traces back to an earlier merge, we attribute it - giving you a real escaped-defect rate per author, per team, and per tool.

This turns retrospectives from opinion into evidence. Instead of arguing about whether large PRs or thin reviews are risky, you can see the correlation in your own history. Pair it with PR quality analytics and pull request analytics to catch risky merges before they ship, and with cycle time analytics to make sure speed and quality move in the right direction together.

For AI-heavy teams, this attribution is essential. When agents and copilots are writing more of the code, you need to know whether that code stays stable in production - not just whether it compiled. That is why blast-radius mapping and author-type segmentation sit at the center of the dashboard.