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The History tab shows every execution of a single test case on the active branch. Use it to measure stability over time and confirm whether failures are new, recurring, or flaky.
Only runs from the active branch appear. Test runs from other branches are excluded.

What You See

Test case history KPI tiles showing stability percentage, total runs, and outcome counts

1. Test Metrics

Key metrics for this test on the active branch:
  • Stability: Percentage of runs that pass. A 100% stability score means the test passed in all tracked executions. Stability is calculated as (Passed Runs ÷ Total Runs) × 100
  • Total Runs: The total number of executions tracked on this branch. Provides context for all other metrics.
  • Passed / Failed / Flaky / Skipped: Counts for each outcome.

2. Last Status Tiles

Links to the most recent run for each outcome: Last Passed, Last Failed, Last Flaky. Each tile shows the Run # and timestamp. The current label appears when the tile matches the run you are viewing.

3. Execution History Table

Lists every execution on this branch in time order.
ColumnDescriptionWhy it matters
Executed atTimestamp when the test ranCorrelates failures with commits or deployments
RunUnique identifier for the test runNavigate to the exact run
StatusOutcome: Passed, Failed, Flaky, SkippedSpot trends and recurring issues
DurationTotal runtime of the executionIdentify performance regressions
RetriesNumber of retry attemptsSurfaces flaky or unstable tests
Run locationLink to the CI jobAccess to the original build and logs
ActionsLink to execution detailsInspect evidence and artifacts
Rows expand to show Error Details for failures or Console Logs if they were captured during execution.

How to Read Stability

Stability measures a test’s reliability on the current branch. The percentage reflects the entire history, not just the most recent run.
  • 100% Stability: Test passes in every tracked run on this branch.
  • < 100% Stability: At least one run failed or was flaky, even if the latest run passed.

Why It Matters

  • Confirm whether a failure is a regression or a recurring issue.
  • Track retry frequency as a stability signal.
  • Spot duration changes that indicate performance drift.
  • Use run links to inspect evidence and CI context.