agent's quarantine threshold was computed from 3 samples - one failure quarantined a healthy test
Fixes test-healing agents quarantining healthy tests based on too few samples. Use when a test was quarantined after a single failure or a tiny sample. Covers requiring a minimum sample size before quarantine, using failure-rate thresholds instead of single events, and unquarantining thin-evidence decisions. Not for tests with long failure histories.
TL;DR
The agent quarantined a healthy test after one failure in three runs. Require a minimum sample size (e.g. 10+ runs) and a failure-rate threshold before quarantining; a single failure is a signal to investigate, not to quarantine. Re-run thin-evidence quarantines with proper sampling.
The symptom
agent's quarantine threshold was computed from 3 samples - one failure quarantined a healthy testSteps
1. Audit the quarantine decision
Check how many runs the quarantine was based on. Three runs with one failure is noise, not evidence of flakiness. Expected: The sample count that drove the decision (3 runs).
2. Unquarantine and resample properly
Remove the quarantine flag and run the test 10 or more times. A healthy test passes consistently; a flaky one shows a real failure rate. Expected: 10+ clean runs proving the test is healthy.
3. Set a statistical quarantine policy
Teach the healer: quarantine requires at least N runs (10 is a sane floor) AND a failure rate above a threshold (e.g. 20 percent), or a confirmed non-deterministic root cause. Single failures get investigation, not quarantine. Expected: No quarantine on fewer than N samples, ever.
4. Log the evidence with every quarantine
Each quarantine record must include the sample size, failure count, and the runs it was based on, so thin decisions are visible in review. Expected: Quarantine log entries that show their own statistical basis.
When to use
- A test was quarantined after very few runs
- A single failure triggered quarantine
- Quarantine records lack sample-size evidence
When not to use
- The test has a long history of intermittent failures (quarantine may be right)
- The root cause is proven non-deterministic (quarantine with the cause attached)
- The policy is already statistical (look for a different misfire)
Why it happens
With 3 samples, a single failure is statistically meaningless; even a 99-percent-reliable test fails once in a while. Quarantining on thin evidence removes healthy tests from the suite, shrinking coverage while the 'flakiness' dashboard fills with false positives.
Edge cases
- Expensive tests where 10 runs is costly: use fewer runs but require a reproduced root cause, not a bare failure.
- Newly added tests with no history: default to investigation, never auto-quarantine.
- Intermittent infrastructure noise: exclude infra-failed runs from the sample count.
Provenance
Resolved from the public thread: https://vectle.com/posts/pst_J63pW2MAyydpsZsGkHd3Sg