tldr: When to stop testing depends on coverage, defect rate, risk, and deadlines. Specific exit criteria beat time-based ("we tested for two weeks") or count-based ("we ran 1,000 tests") rules.
Why "stop" matters
Testing has diminishing returns. The first 100 tests find most bugs. The next 100 find fewer. The next 1,000 find a handful. At some point, more testing produces marginal value while still consuming engineering time.
Knowing when to stop is a real decision, and "we tested enough" without specific criteria leads to two failures: stopping too early (bugs in production) or stopping too late (slow releases).
Useful exit criteria
Specific, measurable, agreed in advance.
Coverage criteria. 100% of P0 acceptance criteria pass. 95% of planned test cases executed. Code coverage above threshold.
Defect criteria. Zero open P0 defects. Fewer than 3 open P1 defects. No critical defects untriaged for over 24 hours.
Trend criteria. Defect arrival rate decreasing over the last several days. Critical-flow regression suite passing for several consecutive runs.
Sign-off criteria. Stakeholder approval captured in writing. UAT sign-off received.
A useful exit policy combines several. Coverage alone misses the late-breaking critical defect. Defect-only misses untested areas.
Time-based "stop" criteria
"We will test until the end of the sprint" is a time-box, not exit criteria. It is sometimes useful (when the schedule is non-negotiable) but it is not the same thing.
If you must use a time-box, pair it with: at the end of the time-box, evaluate exit criteria. If unmet, you ship with documented risk or extend the time-box.
What ships with the build
Three categories of defect at the time of stopping:
Fixed and verified. No issue at release.
Open with workarounds documented. Ship with release notes describing the issue and workaround.
Open without workarounds. Either fix before release or block the release. Not optional.
The team must agree in advance on which category each defect falls into. Vagueness produces release-day arguments.
Risk-based stopping
Some teams use risk thresholds: stop testing when remaining unknown risk is below a defined level.
Implementations vary. A practical version: list the most-likely-to-fail areas. Stop when each has been tested at the appropriate depth.
This approach pairs well with continuous testing: if the regression suite has been green on every commit, the systemic risk is low even if specific tests are still pending.
How AI testing fits
When E2E testing is continuous and cheap, the question shifts from "did we test enough" to "is the suite green?" If the suite is green and coverage is in place, stopping is straightforward.
Bug0 provides continuous coverage with reproduction artifacts as a forward-deployed QA team, which removes the ambiguity from release decisions.
FAQs
What are the most common stopping mistakes?
Stopping based on test count rather than test coverage. Stopping based on time without checking exit criteria. Stopping when the team gets tired.
Should I keep testing if I am still finding bugs?
Depends on severity and trend. If the bugs are critical and the rate is rising, keep testing. If they are minor and the rate is dropping, you may be at the right stopping point.
How do I know if I stopped too early?
The escaped defect rate tells you over time. See escaped defects.
How does Bug0 inform stopping decisions?
Bug0 gives you a constant signal on regression status. Combined with explicit exit criteria, the stopping decision becomes a checklist instead of a debate.