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What makes test automation fail? Top 10 Reasons with Solutions

 

Test automation is awesome. No doubt about that. However, sometimes test scripts just…fail, and it’s quite frustrating.
 

What makes test automation fail in the first place? Knowing these root causes, we can easily develop best practices to make them run smoother and faster.

 

1. Timing issues

Timing issues happen when your tests try to interact with a page before it's fully loaded. Ever clicked a button that’s not ready yet? Automation scripts can do the same, leading to flaky tests that pass one day and fail the next—super frustrating! This often happens with slower networks or when the page has dynamic elements.

How to Resolve:

  1. Explicit Waits: Instead of rushing, tell your tests to wait until an element is ready (e.g., visible or clickable).
  2. Ditch Hardcoded Waits: Skip using fixed delays (Thread.sleep()). Instead, let tests dynamically wait based on actual page readiness with tools like WebDriverWait.
  3. Use Fluent Waits: Customize waits to keep checking for elements at regular intervals, so you’re not left hanging.

Solve timing issues with Katalon SmartWait
 

2. Hardcoded data

Hardcoding data, like usernames or URLs, into your test scripts locks them into specific scenarios. When things change—like a new environment or updated credentials—your tests fail, and you end up spending way too much time fixing them. Plus, it limits the flexibility of running tests across different environments, making scaling more difficult.

How to Resolve:

  1. Parameterization: Use variables or external data files to feed test data, so you're not stuck with fixed values.
  2. Data-Driven Testing: Leverage data sources like CSV files or databases to dynamically adjust your test cases.

Learn more: How to do data-driven testing easily with Selenium and Katalon

 

3. Lack of modularity

Modular-based Testing Framework

When tests aren’t modular, they become big, tangled messes that are hard to maintain. If one part of your application changes, you’re left with a bunch of broken tests to fix. Plus, without modularity, you're likely duplicating code, which means more places for errors to hide.

How to Resolve:

  1. Breaking Down Tests: Create smaller, reusable test components or functions. That way, if something changes, you only need to update one part.
  2. Use Test Libraries: Group common actions (like logging in) into libraries, so you can reuse them across multiple test cases without rewriting code.

Read more: Top 6 types of test automation frameworks you should know

 

4. Inadequate test maintenance

Without regular maintenance, your test automation suite can quickly fall apart. As your application evolves, the automated tests need to keep up with changes in functionality, UI updates, or new features. This not only causes frustration but also makes your test suite unreliable for catching real issues.

Keep your tests fresh by:

  1. Regular Reviews: Schedule frequent audits of your test cases to ensure they align with the latest app changes.
  2. Refactor When Necessary: Don’t be afraid to refactor or rewrite tests as your application evolves. It's better to spend a little time maintaining them than dealing with constant failures.

 

5. Unreliable test data

Imagine running a test that worked perfectly yesterday, but today it fails—not because there’s a bug, but because the test data changed or wasn’t managed properly. This kind of inconsistency can lead to a lot of confusion and frustration, making it hard to trust the test results. It’s even worse when multiple tests share the same data, as changes in one test can cause a ripple effect, breaking others and creating a cascade of failures.

Here’s how to keep things on track:

  1. Isolate Test Data: Ensure that each test has its own unique data, preventing conflicts or unintended interactions between tests.
  2. Use Test Data Management Tools: Implement tools or scripts that handle data management for you—cleaning, refreshing, and ensuring that the test environment is always in a consistent state. This keeps your tests running smoothly and accurately.

Learn more: Test data management best practices

 

6. Environment inconsistency

Inconsistent test environments are a common culprit in automation failures. If your test environment differs from the production or staging setups—whether it’s different server configurations, database versions, or even minor changes in third-party APIs—your tests may behave unpredictably.

How to Resolve:

  1. Standardize Your Environment: Use containers like Docker or virtual machines to replicate the production environment for all test runs.
  2. Automate Environment Setup: Create scripts that automate environment configuration to ensure consistency across all tests, minimizing discrepancies between environments.
     

7. Lack of skilled automation engineers

Katalon Academy

Effective test automation requires more than just running scripts. It demands engineers who understand both coding and testing principles. Without the right skills, test scripts can be poorly written, inefficient, and hard to maintain. Inexperienced engineers may also struggle to keep up with evolving software, causing tests to become obsolete or unreliable.

How to Resolve:

  1. Provide Training and Upskilling: Invest in educating your team about test automation best practices and coding fundamentals. See how you can learn test automation easily with Katalon Academy.
  2. Hire Experienced Engineers: Bring in engineers who are skilled in both development and testing to build robust, maintainable test suites.
     

8. Lack of manual testing

While automation is excellent for repetitive tasks, it can’t replace the human intuition required for exploratory testing or catching usability issues. Relying solely on automation means you risk missing bugs that aren’t part of predefined scripts. Automation also can’t evaluate user experience, which is critical for customer-facing applications.

How to Resolve:

  1. Balance Automation with Manual Testing: Use automation for tasks that are repetitive and time-consuming, but rely on manual testers to explore edge cases and test usability.
  2. Perform Exploratory Testing: Encourage manual testing to discover issues that automated scripts may not anticipate, ensuring better coverage and user-focused insights.

Learn more: What is Exploratory Testing? Definition, How-to, and Best Practices

 

9. Unrealistic expectation

Many teams expect automation to handle every aspect of testing, but that’s not realistic. Automation can’t cover everything, especially complex user interactions or unexpected edge cases. Overestimating what automation can do leads to disappointment when tests miss critical bugs or fail to keep up with new features.

How to Resolve:

  1. Set Realistic Expectations: Understand the limitations of automation. It’s a great tool for speeding up repetitive testing tasks but should complement—not replace—manual testing.
  2. Prioritize High-Value Automation: Focus on automating tests that add the most value, such as regression testing or performance monitoring, and leave edge cases for manual testing.
     

10. Failure to adapt to Agile changes

 Agile development moves fast, and if your test automation isn’t flexible enough to keep pace, it will quickly become outdated. Tests written for earlier versions of the software may fail after even small changes, creating bottlenecks in your development cycle and delaying releases.

How to Resolve:

  1. Keep Tests Modular and Flexible: Write smaller, modular test cases that can be easily updated when new features are added or changes occur.
  2. Embed Automation into Agile Workflows: Continuously update and run automated tests in line with Agile sprints, ensuring that tests evolve alongside the software they’re validating.

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