20 Automation Testing Best Practices for 2025

Test execution time is often one of the biggest pain points in any automation strategy. As your test suite grows, running all tests sequentially becomes a bottleneck that slows down your feedback loop and limits your release speed. To prevent this, your test architecture must support parallel execution. This means that every test should be designed to run independently, without depending on data or states created by other tests.

It also requires careful orchestration of test environments. If your tests share a common database or filesystem, you might end up with resource conflicts or race conditions. The best practice is to use isolated, sandboxed environments or mock services where possible.

💡 Insight: A test that works in isolation but fails in parallel is often a sign that the code under test has hidden dependencies or that your test setup needs to be restructured.

2. Avoid using fixed sleeps; Use dynamic waits instead

It might seem easy to sprinkle sleep(5) statements throughout your tests to give your application time to “catch up.” But this habit almost always leads to brittle tests and wasted time. Fixed delays add unnecessary wait time in the best-case scenario and cause unpredictable failures in the worst.

Instead, rely on dynamic waits.

These are waits that respond to specific conditions such as an element becoming visible, a network request completing, or a state change being confirmed. Dynamic waits make your tests faster and more reliable because they move forward as soon as the condition is met.

3. Integrate robust test metrics for your test suite

Without good visibility into how your tests are performing, it becomes difficult to manage them. Test metrics such as test duration, pass/fail trends, failure frequency, and flake rate are essential for understanding both the health of your test suite and the stability of your application.

Establish a clear baseline for performance and use dashboards to track how things evolve over time. This will help you identify tests that are slowing down your pipeline or failing intermittently, and it allows teams to prioritize maintenance where it's most needed.

📚 Read More: How to build a test report?

4. Stress-test new tests to prevent flakiness

Every time you introduce a new automated test, you are adding another node to a web of dependencies. And unless you validate that test thoroughly, it may behave differently under varying conditions, or worse, only fail occasionally.

Before merging a new test into your main branch, run it multiple times in isolation and in combination with other test suites. Test it against different configurations, environments, or states. Stress-testing builds the kind of confidence that your test will perform consistently over time.

5. Tackle flaky tests immediately

A flaky test is a liability. It not only creates noise in your CI pipelines but also diminishes trust in your automation suite. Developers start ignoring failed test results, assuming they’re false alarms, and that’s how real issues slip through unnoticed.

When a test starts failing inconsistently, don’t put it on the backburner. Investigate root causes, log environmental factors, and determine whether the test itself or the application code is at fault. In many cases, flaky tests are symptoms of deeper issues in the app such as race conditions or timing bugs.

6. Add dedicated test data attributes to the codebase

Selectors are the lifeblood of UI test automation. If your selectors rely on visual cues like button text or nested class names, they are likely to break the moment a designer updates the layout. Instead, introduce unique data-* attributes that are used exclusively for automation.

By adding attributes like data-test-id="submit-button", you decouple your tests from cosmetic changes. It makes your tests more stable and easier to debug. This small investment during development pays off every time your team avoids a broken test after a UI change.

7. Ensure the whole team can write E2E tests

End-to-end testing should not be a specialized skill that lives only within the QA team. Everyone involved in product development, including backend developers, frontend engineers, and product owners, should be able to contribute to E2E test creation and maintenance.

This doesn’t mean everyone needs to be an expert in test frameworks. But they should understand the structure, goals, and tools used in automation. When testing is democratized, quality becomes a shared responsibility, not a final checkpoint.

8. Make automation a core part of development culture

Automation works best when it is integrated into the development lifecycle from the very beginning. That means writing tests alongside new features, reviewing test coverage in code reviews, and discussing automation strategies during sprint planning.

When test automation is treated as a critical part of software delivery and not as an afterthought, teams are more likely to catch bugs early, reduce manual testing burdens, and maintain long-term quality.

9. Use modular and independent test design

Complex, monolithic tests may seem efficient in the short term, but they become harder to maintain as your application grows. A better approach is to design your tests as small, focused modules that test individual pieces of functionality.

This modular approach makes it easier to reuse test logic, isolate bugs, and understand failures when they occur. It also allows your team to scale test coverage gradually and more confidently.

📚 Read More: 6 Types of Test Automation Frameworks

10. Perform data cleanup in startup, not teardown

Relying on teardown scripts to clean up test data is risky. If your test fails mid-execution or crashes due to an unexpected error, the teardown process might not run. This leaves behind orphaned data that can interfere with future test runs.

Instead, initialize your test environment by clearing out old data at the beginning of each test. This guarantees that every test starts in a clean state, reducing the chance of cross-test contamination and ensuring reproducible results.

11. Use good naming conventions for variables

Clarity in naming is one of the most underrated practices in automation. If a variable is named x or temp, no one, not even the person who wrote it, will understand what it refers to a week later.

Use names that are specific, descriptive, and meaningful in the context of your test. For example, loggedInAdminUser is much better than user1. Good names reduce the need for comments and make the purpose of each step obvious at a glance.

12. Follow the DRY Principle

If you find yourself copying and pasting the same lines of code into multiple tests, that’s a sign that it’s time to refactor. Duplicated logic is harder to update and more prone to errors.

Instead, create helper functions or reusable components for common actions like logging in, submitting forms, or generating test data. This not only saves time but also ensures consistency across your entire test suite.

13. Store credentials in environment files

Sensitive data like usernames, passwords, or API keys should never be hardcoded in your test scripts. Not only does this pose a security risk, but it also ties your tests to a specific environment.

By storing credentials in environment files (or a secure secret manager), you keep your tests portable and configurable. This makes it easier to run the same tests across staging, production, and local development with minimal changes.

14. Keep pull requests small and focused

Automation code is code. It needs to be reviewed with the same care and attention as application logic. Large pull requests that modify dozens of files are difficult to review and often introduce unintended bugs.

Break down your changes into small, logical chunks. Each PR should ideally focus on a single feature or area of the test suite. This improves readability, speeds up reviews, and reduces the risk of regression.

15. Use comments sparingly

While comments can be helpful, overusing them often indicates unclear or messy code. The best tests are those that communicate intent through structure, naming, and clarity.

Aim to write tests that are self-explanatory. Use comments only when you need to provide context or explain a non-obvious decision. Otherwise, let the code do the talking.

16. Follow a maintainable structure (page model or screenplay)

Organizing your test logic is essential for long-term maintainability. The Page Object Model (POM) is a popular pattern that encapsulates UI interactions into separate objects. Alternatively, the Screenplay pattern focuses more on modeling user behavior.

Regardless of which you choose, the goal is the same: separate concerns, reduce duplication, and make tests easier to navigate. A well-structured framework allows your team to onboard faster and reduces the cost of change.

17. Model domain logic, not just UI pages

Tests should reflect business behavior, not just visual structure. Instead of mimicking the click path through a page, think about what the user is trying to accomplish, such as logging in, placing an order, updating a profile.

When you abstract your test logic around business actions rather than technical elements, your tests become more robust, meaningful, and reusable — even as the UI evolves.

18. Track and reference automation-created data

Many test failures occur not because of broken functionality, but because leftover data from previous runs interferes with the current one. To avoid this, tag all data created by your tests with unique markers — such as timestamps, test IDs, or prefixes.

This makes it easier to clean up afterwards and helps you trace issues back to specific test runs when things go wrong.

19. Enable tests to adapt to UI changes gracefully

UI tests are notoriously fragile when tied too closely to layout or styling. To make them more resilient, abstract your selectors, minimize assertions on visual properties, and build logic around expected behaviors.

Automated tests should verify that a feature works, not that a button is precisely 40 pixels wide. Focus on what matters: the underlying logic and the user outcome.

20. Incorporate continuous integration and testing pipelines

Automation is about running tests continuously. Integrate your tests into your CI/CD pipeline so they run automatically on every code push, pull request, or deployment.

This ensures that feedback is immediate and issues are caught before they reach production. A strong pipeline turns your test suite into a living, breathing quality gate for every change.