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Results and Imports

This page covers result entry, bulk updates, JUnit XML import into an existing run, and dataset rows.

Add Run Result

Add Result opens the result modal.

Result Fields

Field Used When
Select Status Required for every result.
Time Execution time such as 10m, 1h, or 00:15:00.
Failed Step Required for Failure when the case has steps.
Actual Result Required for Failure.
Defect ID / Link Useful for Error, Failure, Blocked, and XPassed.
Auto-create Jira issue on failure Creates a Jira issue when status is Failure and no defect field is provided.
Comment Required for Error, Failure, Blocked, and XPassed.

Status Guidance

Status Use When
Passed Actual behavior matches expected behavior.
Failure Product behavior is wrong and needs triage.
Error The test could not run correctly because of tooling, data, or execution error.
Blocked External dependency, environment issue, or upstream defect prevents execution.
Skipped The case is intentionally skipped for this scope.
XFailed A known expected failure is confirmed.
XPassed A scenario expected to fail unexpectedly passed and needs review.
In Progress Execution started but is not final.
Untested No result has been recorded.

The current UI applies one payload to all rows of a run item. Row-level updates are available through the API.

Bulk Update Run Items

When users select multiple run items, the bulk toolbar can edit selected items, delete selected items, or clear selection.

Bulk edit uses the same result modal and applies the result to every selected item. For bulk failures, users can add a shared comment, defect reference, or Jira auto-create setting.

JUnit XML Import into Existing Run

For not_started and in_progress runs:

  1. Click Import JUnit.
  2. Choose an .xml file.
  3. Optionally enable Create missing test cases.
  4. Run Dry Run to preview matching.
  5. Review matched, unmatched, ambiguous, and error lists.
  6. Click Import Results.

Dataset Rows in Runs

When a test case is linked to datasets, the backend creates Run Case Rows:

  • cases without datasets get one Default scenario row;
  • one dataset creates one row per selected dataset row;
  • multiple datasets create combinations;
  • each row stores dataset alias, dataset id/name, revision, row key, scenario label, and values.

Row snapshots make results reproducible even if the dataset changes later.