What is Flaky Test?
A flaky test is an automated test that produces inconsistent results, passing sometimes and failing other times, without any change to the underlying code. This non-deterministic behaviour erodes trust in the test suite, masks real defects, and slows delivery as teams rerun pipelines and waste time chasing failures that may not reflect genuine bugs.
What causes flaky tests?
Flakiness usually stems from non-determinism in the test or its environment. Common culprits include timing and race conditions, such as a test that asserts before an asynchronous operation finishes, reliance on fixed waits, dependence on external services or network calls, and shared state that leaks between tests when they run in a different order or in parallel.
Other frequent causes are dependence on system time, randomness, locale, or test data that is not reset between runs. In UI and end-to-end testing, animations, dynamic content, and unstable element selectors add further sources of intermittent failure. Diagnosing flakiness means reproducing the inconsistency and isolating which of these factors is responsible.
Why are flaky tests harmful?
When a test fails unpredictably, developers stop trusting failures and start ignoring them or simply rerunning the pipeline until it passes. This conditioned blindness is dangerous, because a genuine regression hidden among flaky failures can slip straight through to production unnoticed.
Flaky tests also impose a steady tax on velocity: pipelines take longer, engineers spend time investigating phantom failures, and confidence in automation erodes. Left unmanaged, flakiness can undermine an entire continuous integration strategy, so disciplined teams quarantine, track, and fix flaky tests rather than tolerating them.
How Appsierra helps with flaky tests
Appsierra helps teams stabilize their automation by diagnosing the root causes of flakiness, replacing fixed waits with proper synchronization, isolating shared state, and hardening selectors so failures mean something again. Our expert-supervised pods build resilient frameworks and apply our own evaluation discipline to keep suites trustworthy as they scale. To restore confidence in your test results, explore our automation testing services.
Frequently asked questions
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