Software Testing Tools

Test Suite Health Calculator

Enter flakiness percentage, run duration, coverage, and maintenance time to compute a test suite health score with recommendations.

No data is transmitted — everything runs locally

Example — Representative default scenario — pass rate 96.5 · flaky rate 4.2 · avg runtime min 18.

Flakiness score
20/100
8% flaky — Needs work
Speed score
60/100
22 min total run
Overall health
55/100
Needs improvement
Top priority
Fix flaky tests

Test Suite Health Calculator

The Test Suite Health Calculator scores test suite health from flakiness rate, total run time, coverage, and maintenance burden with prioritized improvement recommendations.

• Score test suite health for a quarterly engineering health review

• Identify the single highest-impact area for test quality improvement

• Track test suite health trend over quarters

• Build a business case for a test quality investment sprint

Uptime, incident, and on-call management. Better Stack provides status pages, incident management, and on-call scheduling for engineering teams.
View test health with Better Stack
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What does this tool tell you?
The Test Suite Health Calculator scores test suite health from flakiness rate, total run time, coverage, and maintenance burden with prioritized improvement recommendations.
What affects the result most?
Test suite health: coverage + flakiness + speed + pyramid shape + maintenance burden. Healthy signals: <5% flaky, <10 min total run, >80% coverage, pyramid-shaped, <10% maintenance time. Sick signals: >10% flaky, >30 min run, <60% coverage, ice-cream-cone shaped, >30% maintenance time.
How should I use the result?
The calculation is deterministic — the same inputs always produce the same output — so the most useful workflow is to vary one input at a time and see which factor moves the result most. That tells you where to focus your attention before committing to a decision.
Unhealthy tests ship unhealthy products. Unhealthy products churn customers. The Churn Defense Pack traces quality signals back to account retention — surfaces where test failures correlate with customer complaints.
View quality-churn analysis →
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