What Are the Most Common Causes of Flaky Tests, and How Do You Fix Each One?

Nearly all flaky tests trace back to a small set of root causes: race conditions and bad waits, test interdependence and shared state, non-deterministic data, unstable locators, animation and rendering timing, and unreliable external dependencies. If you can recognise which one you are looking at, the fix is almost always well established. The reason flakiness feels mysterious is that the failures are intermittent, not that the causes are exotic.

Here is each cause, how to spot it, and how to fix it properly.

## Race conditions and improper waiting

This is the dominant cause of flakiness. The test checks for a result before the application has finished producing it.

- **Signs:** the test fails more often on slower CI machines, or under heavy parallelism.

- **Anti-pattern:** fixed sleeps like "wait 2 seconds". They are too short on a bad day and waste time on a good one.

- **Fix:** use explicit, condition-based waits. Wait for the specific element to be visible, the network to be idle, or the exact text to appear. Assert on a state, never on the clock.

## Test interdependence and shared state

A test passes alone but fails in the suite, because another test left the database, cache, or session in an unexpected state.

- **Signs:** failures change when you reorder or shard tests.

- **Fix:** make every test fully self-contained. Create its own data in setup and remove it in teardown. Never assume execution order. Where possible, isolate tests with separate accounts or namespaces so they cannot collide.

## Non-deterministic data and time

Tests that use random values, the current date, or unsorted query results will eventually fail by chance.

- **Signs:** failures cluster around month boundaries, midnight, time zones, or specific random seeds.

- **Fix:** freeze the system clock during tests, seed any random generators, and explicitly sort results before asserting on them. Avoid asserting on values you do not control.

## Unstable element locators

Locators tied to DOM position or auto-generated class names break when the UI shifts, producing failures that look intermittent because the UI changes intermittently.

- **Signs:** failures correlate with front-end deployments.

- **Fix:** use stable, semantic selectors such as dedicated test IDs or ARIA roles. Self-healing locators can provide a safety net, but the primary defence is choosing durable attributes in the first place.

## Animation and rendering timing

An element can be present in the DOM but not yet interactable because a transition is still running, so a click silently misses.

- **Signs:** failures on clicks or inputs that "should" work, often only in headed mode or on faster machines.

- **Fix:** wait for the element to be stable and actionable, not merely present. Where feasible, disable non-essential animations in the test environment.

## Unreliable external dependencies

When a test hits a real third-party API, its reliability is now hostage to that service.

- **Signs:** failures with network errors, timeouts, or rate-limit responses that have nothing to do with your code.

- **Fix:** mock or stub external services in your main suite so tests are deterministic. Keep a small, separate, clearly-labelled integration suite for genuinely testing the live connection, and accept that it will be less stable.

## Infrastructure and resource contention

Underpowered or overloaded CI agents cause timeouts that masquerade as application bugs.

- **Signs:** failures spike during busy build periods and vanish when run locally.

- **Fix:** right-size CI resources, cap parallelism to what the hardware supports, and apply retries only at the infrastructure boundary, never around assertions about behaviour.

## A practical prioritisation

Not all causes are equally common. If you are starting from scratch, attack them in this order:

1. Replace every fixed sleep with a condition-based wait.

2. Make tests self-contained and order-independent.

3. Remove non-determinism from data and time.

4. Harden locators.

5. Mock external dependencies.

6. Tune infrastructure last.

This order front-loads the fixes that resolve the largest share of flakiness for the least effort. neart.ai builds enterprise-grade quality products that help teams attribute failures to these categories automatically, which is the step most teams find hardest to do by hand.

## Takeaway

Flaky tests are not random; they are a short list of recognisable causes wearing the disguise of intermittency. Learn to identify the category from the failure pattern, apply the matching fix, and resist the temptation to paper over the problem with blanket retries that hide real bugs.