How to Reduce Flaky Tests: A Practical Guide
To reduce flaky tests, find the source of nondeterminism and remove it. Replace fixed sleeps with explicit waits that poll for a condition, make each test create and clean up its own data, control time and randomness, and isolate tests so order never matters. Quarantine flaky tests to unblock the build, then fix root causes rather than masking them with blanket retries.
What causes a test to be flaky?
A flaky test passes and fails without any code change, which makes it worse than useless, it trains the team to ignore red builds. Flakiness almost always comes from nondeterminism: timing races, shared mutable state, dependence on test order, uncontrolled randomness or dates, and unstable external dependencies.
The single most common cause is timing: a test asserts on an element or response before the system is ready. The second is shared data: tests that read or write the same records interfere with each other when run in parallel or in a different order.
How do deterministic waits eliminate timing flakiness?
Fixed sleeps ("wait 2 seconds") are the root of most timing flakiness, too short and the test races ahead, too long and the suite crawls. Replace them with explicit waits that poll for the actual condition you care about: element visible, element clickable, network request complete, or a specific value present.
Deterministic waits succeed as soon as the condition is met and fail only if it never becomes true within a generous timeout. This makes tests both faster and more reliable, and it removes the guesswork of tuning sleep durations across different machines and load levels.
How do you isolate data, time, and randomness?
Make every test self-sufficient: it creates the data it needs, uses it, and cleans up afterward. Tests that share fixtures or depend on a seeded database fail unpredictably when run in parallel or in a new order. Isolation lets you run tests in any order and across many workers safely.
Control nondeterministic inputs explicitly. Inject a fixed clock instead of reading the real time, seed random generators, and stub or mock unstable external services so a third-party outage cannot fail your suite. Anything the test does not control is a potential source of flakiness.
How should you triage and fix flaky tests?
When a flaky test surfaces, quarantine it immediately, move it out of the blocking suite so it stops failing builds, then create a ticket to fix the root cause. Leaving known-flaky tests in the gate erodes trust in every result.
Resist the urge to slap a retry on everything. Blanket retries hide real intermittent bugs (genuine race conditions in the product, not the test) and let them reach users. Reserve retries for documented external nondeterminism, and always investigate why a test needed one.
Who keeps the suite flake-free as it scales?
Flakiness creeps back in as suites grow unless someone actively hunts it down. Appsierra's managed pods treat suite reliability as part of owning the quality outcome, diagnosing root causes and keeping green builds meaningful, de-risked by Appsierra's own evaluation platform.
Frequently asked questions
What is a flaky test?
A test that produces different results (pass or fail) on the same code without any change, due to nondeterminism like timing races, shared data, or uncontrolled randomness. Flaky tests undermine trust in the whole suite.
Why are fixed sleeps bad in tests?
A fixed sleep is either too short (the test races ahead and fails intermittently) or too long (the suite slows down). Explicit waits that poll for a real condition succeed as soon as the system is ready, fixing both problems.
Should I use retries to fix flaky tests?
Only as a last resort for genuine external nondeterminism, and always investigate why. Blanket retries mask real intermittent bugs and let them reach production. Fixing the root cause is far more valuable than retrying.
How does shared test data cause flakiness?
When tests read or write the same records, they interfere with each other under parallel execution or a changed run order. Making each test create and clean up its own data removes this dependency and allows safe parallelism.
How do I deal with a flaky test right now?
Quarantine it so it stops blocking builds, file a ticket, and fix the root cause, deterministic waits, data isolation, controlled time and randomness. Never leave known-flaky tests in the blocking suite.
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