Software development teams can now ship code more quickly as well as confidently thanks to automated testing, which has become an essential component of the process. But even when the code being tested hasn’t changed, flaky tests—tests that pass along with fail randomly—remain one of the largest problems teams have to deal with. By reducing developer time spent debugging false failures as well as lowering confidence in test results, flaky test reduces the value of automated testing. This post will examine the reasons behind test flakiness, along with its effects as well as various tactics teams can use to lessen flakiness and raise test quality.
1. Causes of Flaky Tests
Some automated tests may yield inconsistent or unreliable results for a few common reasons. Network latency or outages can cause tests interacting with external dependencies, such as databases, APIs, or networks, to occasionally fail. Due to timing problems, tests with multiple asynchronous operations may encounter race conditions. Each run of a test that includes non-deterministic components like dates or random numbers may differ. If a test shares resources or state between test cases without appropriate isolation, it may also be considered flaky. Lastly, certain tests may be more brittle than others due to differences in environments between various machines.
2. Impact of Flaky Tests
Flaky tests have a detrimental effect on development teams in a number of ways. As failures are not always reproducible, it causes a loss of confidence in the test results. This implies that rather than depending on automation, along with developers must manually verify each as well as every test failure. Investigating failures that prove to be non-reproducible also results in a significant amount of debugging effort being wasted. Productivity is lowered as a result. Flaky tests also impede the overall development cycle by disguising actual bugs as well as delaying feedback on code changes. Additionally, they may result in unstable, unpredictable, as well as sporadic failures in continuous integration builds. Flakiness gradually reduces trust in the test suite, which deters additional test automation using techniques like test-driven development.
3. Strategies to Reduce Flakiness
Development teams can use several primary tactics to lessen the number of flaky tests. First, by using dependency injection as well as mocking external components when feasible, tests should be written to reduce shared dependencies along with external interactions. Tests become more deterministic as a result, increasing isolation. Second, in order to avoid race conditions in tests that involve concurrent operations, appropriate synchronization must be implemented using strategies like locks. Thirdly, resilience needs to be incorporated into tests that depend on external systems by using stubs, along with timeouts, as well as retries. When tests show signs of flakiness, they should also be annotated so that refactoring can be done in a priority manner. Teams should use metrics as well as logs to track test execution in order to identify the underlying causes of non-determinism. Lastly, reducing complexity along with flaws that can lead to flakiness can be achieved by splitting complex tests, along with simplifying test code, as well as adhering to test best practices.
Conclusion
Automated testing is made less valuable by squandering developer time as well as lowering confidence due to faulty tests. Teams can take steps to identify what is flaky test, comprehend the underlying causes, as well as refactor tests to remove non-determinism as much as possible, even though some flakiness may always occur. The impact of faulty tests can be reduced with discipline along with observation, increasing output as well as accelerating the delivery of high-quality software.
