How to Detect Flaky Tests?

Flaky tests are tests that pass or fail inconsistently without changes to the code or environment. Detecting them early is essential to maintain trust in your test automation pipeline. Here's how to identify them effectively:

• Repeated and isolated test execution:
• Run tests multiple times on the same codebase: If a test passes sometimes and fails other times without any code change, it’s likely flaky.
• Run tests in isolation: If a test passes when run alone but fails within the full suite, it may be affected by shared state or order dependencies.
• Run tests in parallel: Flakiness during parallel runs often indicates race conditions or resource conflicts.
• Analyze historical test data:
• Maintain detailed test history across CI runs: Track pass/fail patterns over time.
• Monitor time-based failure patterns: Tests that fail during specific hours or system loads may point to environmental instability.
• Leverage automation and analytics tools:
• Use observability platforms like LambdaTest Test Intelligence or CI features to:
• Visualize flaky test trends
• Assign “flaky scores” to prioritize fixes
• Automatically detect inconsistent test behavior
• Many CI tools support tagging or quarantining flaky tests to isolate their impact on pipelines.
• Use retry results as diagnostic signals:
  • Enable limited automatic retries in your test runs.
  • Tests that often fail initially but pass on retries are strong candidates for flakiness.
  • Use retry patterns to identify instability not as a permanent fix.
• Engage your team for proactive detection:
  • Encourage developers and testers to report inconsistent or flaky test behavior observed during local or manual runs.
  • Real-world insights often catch flaky scenarios automated tools miss.

Detecting flaky tests is about combining automated data analysis with human insights and catching instability early. Addressing flaky tests proactively maintains trust in your test suite and keeps your release cycles smooth.