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Unwanted random test failures can occur when the user interface (UI) of an application is changed, and these failures are undesirable because they lack stability. Making sure that each test step and modification is accurate which requires continuous maintenance and feedback loops. However, these tasks often noticeably slow down the development process. That’s why it is important to analyze how often tests produce inconsistent results in order to develop more effectively. Certainly! In this blog, we will delve into the topic of flaky tests and explore strategies to minimize their occurrence.
The Science Of Flaky Tests:
A flaky test is inconsistent, producing different results when run multiple times with the same inputs or conditions. It fails on some occasions and passes on others, even when the system being tested remains unchanged. This variability in outcomes frustrates developers and testers, making it difficult to determine the true state and reliability of the software.
Reasons for Flakiness:
Timing and Concurrency:
Flakiness is commonly observed in tests that rely on precise timing or the simultaneous operation of multiple components. The outcome of each test run can vary due to race conditions, synchronization issues, or varying system loads.
External Dependencies:
External systems used in tests, such as databases, APIs, or network services, may impact test results due to their availability, performance, or changes in behavior. Flakiness can occur when testers fail to handle or regulate these dependencies appropriately during testing.
Environment Variability :
Modifications to the test environment, such as different hardware, software settings, or network setups, can cause test results to vary. The results of the test may be adversely affected by minute environmental changes.
Test Data Issues:
Flaky tests might result from dependencies or discrepancies in the test data. Unpredictable results may result from data changes, data corruption, or test data that is not typical of real-world situations.
Test Order Dependency:
Order dependency in flaky tests refers to the situation where the outcome of a test can vary depending on the order in which the tests are executed. Flaky tests are problematic because they can lead to inconsistent and unreliable test results.
Test Design and Implementation:
Flaky tests can also be caused by issues in test design or implementation. Inconsistent results may occur due to poorly written or unstable test scripts, inadequate synchronization techniques, or improper handling of test fixtures and resources.
Best Practices for Reducing Flaky Tests:
Test Environment:
Maintaining a dependable and reliable test environment is crucial. This encompasses hardware, software, network conditions, and settings. By maintaining a standardized and regulated workplace, you can mitigate factors that may contribute to flakiness.
Test Data:
Examine the validity and dependability of the test data. Inconsistencies or dependencies in the data used for testing might occasionally be the source of erratic tests. The consistency of test findings can be increased by using dependable and representative test data sets.
Test Independence:
Tests should be created independently of the status or results of other tests. Test isolation lowers the likelihood of flakiness brought on by test interdependencies and assists in preventing cascade failures.
Test Synchronisation:
To ensure consistent behaviour when tests interact with external systems or resources, it is important to implement synchronization techniques. This involves synchronizing the test execution with external components using appropriate delays, timeouts, or wait conditions. By incorporating these techniques, you can mitigate timing issues and improve the reliability of your tests.
Test Retries:
Implementing retry techniques for flaky tests can be beneficial. When a test fails due to flakiness, automatically rerunning it a certain number of times can yield a more accurate result. However, caution must be exercised to avoid excessive attempts, as this may mask genuine issues.
Logging and Reporting:
Robust recording and reporting procedures can help with the diagnosis of problematic testing. You can find trends and possible causes of flakiness by carefully documenting test executions, including any mistakes, failures, or discrepancies.
Continuous Monitoring:
Observing test results often and examining patterns might reveal information about the frequency and make-up of erratic testing. This knowledge may direct efforts to find the sources behind problems and put forth focused solutions.
For Reference :
https://hackernoon.com/flaky-tests-a-war-that-never-ends-9aa32fdef359
https://dev-tester.com/dont-let-flaky-tests-ruin-your-automation/
https://www.ranorex.com/blog/fix-flaky-automated-tests/
Happy Testing!
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