Understanding Escaped DefectsTrack and measure software quality
What are Escaped Defects?
Escaped Defects are bugs or issues that make it to production (live environment) despite testing efforts. These are 'escaped' from the quality assurance process and reached end users. Tracking escaped defects helps measure test effectiveness and software quality.
Why It Matters
Tracking escaped defects matters because: 1) Measures QA effectiveness - fewer escapes = better testing, 2) Customer impact - production bugs affect users and satisfaction, 3) Cost of defects - fixing in production is 10-100x more expensive, 4) Process improvement - identifies gaps in testing coverage, 5) Team accountability - encourages thorough testing before release.
Total Defects
13
Defect Density
4.5
Escape Rate
100%
Critical/High %
31%
By Severity
By Type
Defect Trend
Add Sprint Data
Sprint Defects
| Sprint | Defects | Story Points | Density | Severity | Type | |
|---|---|---|---|---|---|---|
| Sprint 1 | 3 | 45 | 6.7 | medium | bug | |
| Sprint 2 | 2 | 50 | 4.0 | high | regression | |
| Sprint 3 | 1 | 40 | 2.5 | critical | security | |
| Sprint 4 | 4 | 55 | 7.3 | low | bug | |
| Sprint 5 | 2 | 48 | 4.2 | medium | enhancement | |
| Sprint 6 | 1 | 52 | 1.9 | high | bug |
Quality Benchmarks
Defect Density
Escape Rate
Critical Defects
Escaped Defects Glossary
Escaped Defect
A defect that was not detected during testing and made it to production (live environment). These affect end users.
Defect Density
Number of defects per unit of work (typically per 100 story points or 1000 lines of code). Measures code/test quality.
Escape Rate
Percentage of total defects that escaped to production. Lower is better - indicates effective testing.
Defect Detection Percentage
Percentage of defects found before production. Formula: (Total - Escaped) / Total × 100. Target: 90%+.
Critical Defect
Defect causing system failure, data loss, or security breach. Requires immediate fix regardless of schedule.
Regression Defect
A bug in previously working functionality. Usually caused by new code changes breaking existing features.
DORA Metrics
DevOps Research and Assessment metrics: Deployment Frequency, Lead Time, MTTR, Change Failure Rate.
MTTR (Mean Time to Recovery)
Average time to recover from production failures. Lower is better. Elite: <1 hour.
Change Failure Rate
Percentage of deployments causing production failures. Lower is better. Elite: 0-15%.
Test Coverage
Percentage of code covered by automated tests. Higher is better. Industry target: 80%+.
Production Incident
An issue that occurs in production environment affecting users. Requires urgent response.
Root Cause Analysis
Process of identifying the fundamental cause of defects to prevent recurrence.