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Why your automated tests are failing and what to do about it
Chief Executive Officer
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Unstable (flaky) tests are one of the most common and significant challenges in software development. As practicing QA engineers, we've seen this issue repeatedly affect our clients, leading to frustration and wasted resources.
Many companies offer fixed-price solutions, promising to cover an application with regression tests in just a few months. While this might sound appealing, the reality often falls short. Shortly after delivery, the once-impressive test automation solution starts to randomly falter, either partially or entirely. This failure isn’t always due to product changes, as one might assume. Let’s explore the root causes of test instability and how to address them.
Common causes of unstable tests
Test instability generally stems from two main areas:
Test configuration errors: These involve mistakes or oversights in how the tests are set up, such as improper handling of asynchronous operations, incorrect timeouts, or flawed test logic. Even small misconfigurations can cause tests to fail unexpectedly or behave inconsistently.
Environment issues: The environment where tests run is crucial for their stability. Problems can occur due to server performance, network conditions, or reliance on external services. Instabilities often happen when the test environment isn't properly set up or when different components clash.
| Test configuration errors | Environment issues |
|---|---|
| Asynchrony | Dependence on external services |
| Incorrect timeouts | Dynamically changing data |
| Errors in test writing | Unstable performance of the test environment |
| Improper test environment configuration | |
| Interdependencies between tests | |
| Parallelism | |
| Limitations of test frameworks | |
| Tool updates | |
| Data conflicts |
Asynchrony: Improper handling of asynchronous operations, such as waits or timeouts, can lead to tests running inconsistently.
Incorrect timeouts: Insufficient or excessive timeouts can cause events to be missed or tests to hang.
Errors in test writing: Tests can be unstable due to logical errors, incorrect expectations, or incomplete coverage of scenarios.
Improper test environment configuration: Misconfigurations, such as incorrect file paths or wrong dependency versions, can cause test failures.
Dependence on external services: Tests relying on third-party services or APIs may be unstable due to unpredictable behavior, such as delays, temporary outages, or changes in their configuration.
Dynamically changing data: Test data that changes or updates during test execution can lead to unpredictable results.
Data conflicts: When multiple tests use the same data, this can lead to conflicts and errors.
Interdependencies between tests: If tests depend on each other or share common resources, this can lead to instability, especially when running in parallel.
Parallelism: Improper management of parallel tests can cause data races or resource-intensive conflicts, leading to instability.
Limitations of test frameworks: Issues or bugs within the testing tool or framework itself can cause instability.
Tool updates: Updates to testing tools, such as changes in libraries or frameworks, can lead to test instability.
Unstable performance of the test environment: Limited resources or high load on the servers where tests are executed can cause slowdowns or test failures.
The importance of a solid foundation
Automation testing is an investment meant to save time and money in the long run. However, if the foundation is weak, it might be faster and more cost-effective to start over rather than trying to fix it later.
For instance, one of our clients approached us with a test automation solution consisting of 400 scripts written in Cypress before they started working with us. The solution took an engineer 5 months to develop, averaging 80 tests per month—a seemingly good pace. However, these tests only remained functional while the engineer was actively involved. Shortly after, nearly every test began to fail.
We assessed the situation and found that it was faster to rewrite the test automation solution entirely using Playwright. This took 3 months with one engineer, resulting in 270 stable scripts without duplicated scenarios. The lesson? Quality trumps quantity every time.
Practical steps to ensure test stability
You've likely realized that unstable tests can lead to wasted time, missed defects, and a lack of confidence in your testing process. To help you avoid these pitfalls, here are some practical strategies you can implement to ensure your tests remain stable and dependable:
To keep your tests stable and reliable, consider these effective strategies:
Identify and remove redundant checks
Less code equals fewer problems. Avoid checking the same thing in multiple places. Structure your tests to cover comprehensive scenarios with minimal duplication.
Identify flaky tests and analyze causes
Run tests multiple times to identify flaky ones. Inconsistent results indicate instability that needs addressing, whether due to asynchrony, environmental issues, or unpredictable data.
Ensure proper asynchronous handling
Use explicit waits (e.g., await or sleep) to handle asynchronous operations correctly. Adjust timeouts to balance delays without slowing down tests excessively.
Make your tests independent
Ensure each test can run independently. Avoid dependencies on the state set by previous tests or on data that may change during execution. Use mocks or stubs for external services.
Stabilize your test environment
Maintain a stable test environment with minimal changes and conflicts. Consider using containers (e.g., Docker) or virtual machines to create a reproducible and isolated environment.
Ensure proper test data and state restoration
Use fixed, predictable data for tests. If dynamic data is necessary, ensure it remains in the expected state. Restore the system to its original state after tests to avoid side effects.
Parallelize your tests
Group tests run in parallel without affecting each other. This approach speeds up testing and helps identify potential data races.
Balance checks in your tests
If some checks can be covered via API testing, do so. Minimizing UI checks speeds up test execution. Focus on what's essential as per the original test case.
Automate test runs
Implement CI/CD systems for automatic test runs and analysis. This helps identify unstable tests quickly and ensures consistency in test execution.
Continuously improve and train your team
Regularly review tests to fix weaknesses. Ensure team members understand the importance of stable tests and are familiar with best practices. Stay updated on trends in your tech stack and automation.
Ensuring stable automation tests requires addressing root causes like configuration errors and environmental issues. Simplify test setups, maintain a consistent environment, and use best practices for handling asynchrony and dependencies.
Regularly identify and fix flaky tests, and leverage CI/CD for automation. Investing in a solid foundation and continuous improvement leads to more reliable tests and better software quality.
Final thoughts
The advice shared here is based on our extensive experience, aimed at helping you write high-quality code if you're an engineer, and identify potential red flags if you're a manager.
We confidently say that the complexity and specificity of a project rarely affect test stability. With the right foundation and approach, any project can have a stable automation test suite. And remember, we're always here to help if you need real professionals on your team.
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