Calculate · Assess & Decide · Engineering
Defect removal efficiency
Defect Removal Efficiency from pre-delivery vs escaped defect counts, with an optional per-phase breakdown.
You receive: A reviewed DRE calculator + the passing test report, run on your defect counts.
Part of Ship MVP
Example
A sample of what this play produces. Your result is generated for your inputs.
By phase
| Phase | Dre |
|---|---|
| code review | 35 |
| gate (tests, lint, build) | 61.54 |
| preview verify | 40 |
Inputs
- Internal defects
- 34
- Escaped defects
- 6
- Per phase
- yes
- Phases
Phase Removed Escaped code review 14 26 gate (tests, lint, build) 16 10 preview verify 4 6 - Zero division policy
- undefined
Arithmetic recomputed against the tasks.py compute_defect_removal_efficiency oracle, 2026-08-08, on an illustrative release cycle for a code-first product like STUD's platform (the defect counts are illustrative, not published figures). Of 40 defects total, 34 were removed before delivery and 6 escaped to production, so overall DRE is 34 / (34 + 6) * 100 = 85.0. Per phase, each row divides that phase's removed count by removed plus the defects that slipped past it: code review caught 14 of the 40 it saw (14 / 40 * 100 = 35.0), the gate caught 16 of the 26 that reached it (16 / 26 * 100 = 61.54, rounded to 2 decimal places), and preview verification caught 4 of the remaining 10 (4 / 10 * 100 = 40.0), leaving the 6 that escaped. With defects present, the zero-defect policy (undefined) never fires.
Opens soon
STUD opens runs for everyone soon, on every play at once.
Scope of the check
What's verified: STUD verifies the calculator computes Defect Removal Efficiency on held-out cases: internal defects / (internal + escaped) * 100, an optional per-phase breakdown, and your chosen zero-defect policy (undefined reports null, perfect reports 100). STUD does NOT verify the defect counts are real or complete, nor judge whether the resulting efficiency is good enough; it checks the arithmetic on the counts you provide.
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