Optimize Debugging Automation Tests

What if debugging wasn’t the most frustrating part of your job?

For those who couldn’t attend, the Automation Guild 2025 conference was an incredible event filled with insights from testing experts and thought leaders. As one of the speakers, I was honored to be part of such a prestigious gathering. Below is a summary of my session and if you haven’t already, I highly recommend checking out the Test Guild community for active testing discussions and future conferences.

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How Much Time Do You Spend Debugging Automation Tests?

Minutes? Hours? Maybe even days for that one particularly stubborn test?

While the time spent debugging varies, it’s likely that a significant portion of your work involves fixing failing tests. Let’s face it — automation test failures happen to everyone. They can be frustrating and demoralizing, and I don’t know many people who genuinely enjoy troubleshooting them. However, by the end of this blog, I hope to shift your perspective so that debugging failures becomes a structured, less painful process rather than an overwhelming burden.

Step 1: Test Confidence is Everything

Before optimizing the debugging process, you must first establish test confidence — the ability to trust your test suite’s reliability. This might seem obvious, but ask yourself:

If a test failure occurs, can you confidently say it’s not due to test flakiness? Do you know the current stability of your test suite?

If the answer is no, that’s okay. Recognizing this gap is the first step toward long-term success.

Test confidence begins with mindset. Every test failure should be taken seriously. Don’t bury failures in retries or backlog fixes for another day. Instead, foster a culture of accountability where failures are investigated and resolved promptly. Invest in the test suite’s limitations because ultimately the quality of the results, the output, fully depends on the quality of your efforts, the input. When this mindset is embraced, debugging becomes more efficient because previous test runs are known to be stable.

Once confidence in test stability is established, we can reduce debugging time by following a structured approach when failures occur.

Step 2: A Structured Approach to Debugging

When a test failure happens, ask yourself these three key questions:

1. What are the conditions of the failure?

Identify when and how the test was run. Was it executed pre-merge in a CI/CD pipeline? Did it run headless? Was it tested against a hosted development environment? What about a local test runner?

Understanding the test’s execution conditions provides a high-level overview of the failure context before diving into specifics.

2. What changed?

This is the most crucial question, as it often leads directly to the root cause. Consider:

• Did application code change?
• Did test code change?
• Did the environment change (e.g., new data, infrastructure updates)?
• Was the test previously running in isolation but now running in parallel?
• Did nothing change?

Even if nothing changed, that’s still a valuable answer because it leads to the final question.

3. Is it flake?

Can you reproduce the failure under the same conditions identified in Step 1? If not, the failure may be due to test flakiness, requiring a different debugging approach.

Notice that none of these steps start with, “What is the error message?” While error messages are important, they can be misleading and lead to unnecessary rabbit holes. For example, consider this common, timeout Cypress failure:

Error: Timed out retrying after 4000ms: Expected to find element, but never found it.
This error could indicate multiple potential issues:

• A real performance issue in the application.
• An incorrectly used cy.intercept or cy.wait command somewhere in the test.
• A slow environment due to an increase in test data. *A parallelization issue where one test deletes data another test depends on. *A flaky network causing intermittent failures.

If you don’t know the conditions of the test run and the actual change(s) that occurred between stable runs, you’ll be left guessing at what could have caused the failure, especially if the error is generic.

By following a structured approach, we eliminate all that unnecessary guesswork and significantly reduce debugging time as a result.

Step 3: Improve Test Visibility

Reducing debugging time isn’t just about a structured approach; it’s also about improving visibility into test results.

Timing Matters

Debugging is easiest when fewer changes have occurred between stable test runs. A test failure in a pre-merge suite with minimal changes is far easier to debug than a nightly test run with dozens of updates. The more changes introduced, the longer it takes to isolate the cause.

Act Immediately

Treat all test failures as high-priority.

Delaying debugging allows more changes to accumulate, making it harder to pinpoint the root cause. Of course, immediately addressing failures is highly-dependent on various workload and resource factors, so work with your team’s structure to build a culture of accountability that fits your needs. Simply, investigate failures as soon as they happen to avoid unnecessary complexity later on.

Leverage Artifacts

Ensure easy access to logs, screenshots, and video recordings of test failures. This is especially critical for headless test runs in CI/CD pipelines. Without visibility, debugging becomes a guessing game, leading to wasted hours. Some automation tools provide extended time-travel abilities to further assist with CI failures, such as Cypress’s Test Replay.

Summary (Putting it All Together)

Optimizing debugging isn’t just about fixing issues faster — it’s about changing how we think about failures.

1. Build a culture of accountability. Take test failures seriously and treat debugging as an integral part of automation.
2. Follow a structured debugging approach. Identify conditions, assess changes, and determine whether flakiness is involved first to avoid misleading error interpretations.
3. Enhance visibility into test results. Immediate action, clear artifacts, and minimized test suite changes all contribute to faster debugging.

Finally, embrace failures — even the most frustrating ones. Every failure tells us something valuable:

• A real issue was caught. This means our tests are doing their job, and we should be proud.
• There’s room for improvement. Whether it’s the test, environment, or framework, failures highlight opportunities to refine our approach.

Thank you for reading, go out there and crush all those pesky failures with ease. As always — happy testing!