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Smoke vs Full Regression Optimizer

Optimize QA runtime and release confidence with a risk-aware split between PR smoke, post-deploy, and nightly regression.

Smart Split Recommendation

PR smoke suite121 tests
Post-deploy suite325 tests
Nightly full regression826 tests
Expected PR runtime100.8 min

Weekly regression hours saved

0.0h

Bottleneck risk score

98/100

Smoke pass estimate

90.4%

Release Gate Recommendation

Block

Smoke reliability is too low for safe release decisions.

Top 5 Action Plan

  1. 1. Quarantine flaky tests above repeat-failure threshold.
  2. 2. Move non-critical E2E checks into integration/API tests.
  3. 3. Enforce stable selectors (`data-testid` + role-based locators).
  4. 4. Keep PR gate lean with critical smoke suite only.
  5. 5. Track weekly flaky trend and gate quality score in leadership review.

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# Smoke vs Full Regression Optimization Summary

- Total tests: 1200
- Avg test duration: 50s
- Releases per week: 4
- Flaky rate: 16%
- Critical flows: 40
- QA capacity (hours/sprint): 90

## Recommended split
- PR smoke suite: 121 tests (10.1%)
- Post-deploy suite: 325 tests (27.1%)
- Nightly full regression target: 826 tests (68.8%)

## Runtime forecast
- PR smoke runtime: 100.8 min
- Post-deploy runtime: 270.8 min
- Nightly runtime: 688.3 min
- Weekly hours saved: 0.0 h
- Bottleneck risk score: 98/100

## Release gate
- Decision: Block
- Reason: Smoke reliability is too low for safe release decisions.

## Action plan
1. Quarantine top flaky tests and remove from PR gate.
2. Keep only critical flow smoke tests in PR stage.
3. Move non-critical E2E checks to API/integration layers.
4. St...