What is defect removal efficiency?
Defect removal efficiency (DRE) measures how good your team is at catching bugs before users do. It's the percentage of total defects found during testing versus those that slip into production. It helps you understand if your testing process is actually working or just giving you false confidence.
Do you have any examples of defect removal efficiency?
Here’s an example calculation that shows DRE for a typical software release:
- Bugs found during testing: 85
- Bugs reported by users after release: 15
- Total bugs = 85 + 15 = 100
For formula for DRE is:
- DRE = (Bugs found in testing ÷ Total bugs) × 100
So:
- DRE = (85 ÷ 100) × 100 = 85%
This means your testing caught 85% of bugs before release, while 15% reached users.
Why is defect removal efficiency important?
DRE directly impacts your user experience and maintenance costs. Low DRE means users become your testers, damaging your reputation and forcing expensive emergency fixes. High DRE shows your testing process catches issues when they're cheaper and easier to fix.
What are the challenges with defect removal efficiency?
Calculating accurate DRE is problematic because you can't know about bugs users don't report. Some teams artificially inflate DRE by marking minor issues as bugs during testing, while ignoring serious production issues. The key is consistent bug classification and good user feedback channels to capture real production issues.
