How to Reduce Flakiness?
Flaky tests can occur due to various reasons. Testers should work with their development teams to find the exact reason for the cause. Here are the 10 common causes of flaky tests:
1. Async wait:
Some tests are written in a way that requires waiting for something else to complete. Many flaky tests use sleep statements for this purpose. However, sleep statements are imprecise, and the test may fail if the waiting time exceeds expectations due to variations in processing time.
2. Concurrency issues:
Flaky tests can result from concurrency issues such as data races, atomicity violations, or deadlocks. These tests often make incorrect assumptions about the ordering of operations performed by different threads. To address this, synchronization blocks can be added or the test can be modified to accommodate a wider range of behaviors.
3. Test order dependency:
Certain tests may pass or fail depending on the order in which preceding tests were executed. A good test should be independent and able to run in any order with other tests. It should be properly isolated and set up its own expected state.
4. Timing issues:
Flaky tests can arise from timing inconsistencies when the test code relies on specific event timings. For example, if a test checks for a particular webpage element after a specific delay, network issues or differences in CPU performance between test runs can lead to intermittent failures.
5. Element locator issues:
Many automation tools use XPath to locate webpage elements, but XPath can be unstable as it is sensitive to changes in the page's DOM. Self-healing AI techniques can address challenging testing scenarios involving dynamic elements, iFrames, and pop-ups. This involves using multiple locator strategies to find an element, and switching to a backup strategy if the primary one fails. Modifications to an element's properties or the addition of similar elements can render the initial XPath invalid, resulting in false positives or negatives.
6. Test code issues:
Poorly written or ambiguous test code can contribute to flaky tests. If the test code lacks clarity regarding the expected application behavior, the test may fail or pass inconsistently. Additionally, complex test code or code relying on external dependencies may be more prone to failure.
7. Test data issues:
Tests that depend on inconsistent test data can become flaky. Corrupted test data or different test runs using the same data can lead to inconsistent results. Tests utilizing random data generators without considering the full range of possible results can also introduce flakiness. It is advisable to control the seed for random data generation and carefully consider all possible values.
8. Test configuration issues:
Inconsistent test configurations between runs can cause flaky tests. Incorrect test parameters or improper test settings setup can result in test failures.
9. Environment issues:
Flaky tests can be attributed to the execution environment. Network connectivity problems, improper handling of I/O operations, hardware differences between test runs, or variations in test environments can introduce nondeterminism, leading to flaky tests.
10. Resource leaks: Tests can become flaky if the application or tests do not adequately acquire and release resources, such as memory or database connections. To avoid such issues, it is recommended to use resource pools and ensure that resources are properly returned to the pool when no longer needed.