What Are Flaky Tests and How to Fix Them?

A flaky test is a test that produces inconsistent results without any changes to the code. These tests can pass one minute and fail the next, creating a perplexing and frustrating situation for developers. Flaky tests go by many names, including intermittent failures, brittle tests, and unstable tests. They are more likely to occur in continuous integration (CI) environments than in local test environments, adding another layer of complexity to their detection and resolution.

Understanding the nature of flaky tests is crucial for effective management. Recognizing their characteristics and identifying common causes allows us to develop strategies to detect and resolve these elusive issues. In this blog post, we explore what flaky tests are, why they occur, their impact, and how to handle them.

What are the characteristics of flaky tests?

Flaky tests are frustrating due to their inconsistent results. They can pass or fail without any discernible pattern, making it challenging to pinpoint the root cause. Often, flaky tests depend on shared resources or network conditions, which can introduce unpredictability into the software testing process. For example, a test that relies on an external API might fail intermittently due to network latency or downtime, even though the code itself is functioning correctly.

Another common characteristic of flaky tests is their reliance on inadequate test data and complex dependencies in the testing environment. When tests are not properly isolated, they can interfere with each other, leading to inconsistent outcomes. This issue is exacerbated in CI environments, where tests are run in parallel and under varying conditions. Recognizing these characteristics is key to effectively detecting and managing flaky tests.

What are the causes of flaky tests?

Flaky tests can arise from various causes, each contributing to their unpredictable behavior. One common cause is race conditions, which occur when multiple processes interfere with each other due to relative timing. These conditions can lead to inconsistent results, as the outcome of the test depends on the precise timing of events. Environmental differences, such as discrepancies in library versions or machine resources, can also introduce inconsistent behaviors in tests.

Non-deterministic code, which relies on unpredictable inputs, is another critical contributor to flaky tests. Improper assumptions during test writing, such as assuming a specific order of execution, can also lead to flakiness.

Understanding these root causes allows us to develop targeted strategies to detect and fix flaky tests, ensuring more reliable testing outcomes.

Why is flaky test detection important?

Detecting flaky tests is not just a technical necessity—it is a critical component of maintaining software quality and developer productivity. Flaky tests can lead to unpredictability in software quality assessment, making it difficult to trust the results of your test suite. This unpredictability can result in poor quality releases or delayed delivery times, as developers spend valuable time debugging and re-running tests.

The impact of flaky tests extends beyond the immediate technical challenges. They can impair developer productivity significantly, consuming days or even weeks in debugging efforts. Identifying and addressing flaky tests helps to manage flaky tests, maintaining trust in your test suite and ensuring efficient development cycles.

What are the consequences of flaky tests?

Flaky tests have far-reaching consequences, impacting both productivity and the reliability of testing efforts. A few nondeterministically failing tests can seriously drain productivity, as developers spend considerable time re-running tests and debugging issues that may not exist. This repeated effort not only wastes computational resources but also disrupts workflows, as developers must constantly shift their focus to address flaky test failures.

Moreover, flaky tests can obscure the reliability of overall testing efforts, leading teams to a state where they might as well have no tests at all. Developers often quarantine flaky tests or try to fix failed tests when they encounter failures, leading to further disruptions. If developers can’t fix a flaky test, it often remains off to the side, complicating the development process and diminishing confidence in testing results.

Additionally, flaky tests affect team morale and productivity. Namely, encountering unreliable tests can make developers skeptical about all test outcomes, leading to a negative work environment. This skepticism can result in alarm fatigue, where developers begin to ignore test results altogether, further undermining the reliability of the test suite.

Addressing flaky tests is a critical component of maintaining a positive and productive work environment. Effectively managing flaky tests can restore trust in testing efforts and improve overall morale.

How to detect flaky tests?

Detecting flaky tests is challenging but essential for maintaining the reliability of your test suite. Their inconsistency makes them tough to pinpoint, as they may not manifest consistently or frequently. However, identifying and fixing flaky tests is crucial for reinforcing trust in the test suite and ensuring reliable development cycles. Keeping a record of flaky tests helps avoid wasted time debugging and understanding how to detect flaky tests and their impact on development velocity.

There are various methods for detecting flaky tests, including dynamic and static methods, leveraging CI/CD pipelines, and capturing test run data. Each method has its strengths and can be used in conjunction with others to provide a comprehensive approach to detecting and managing flaky tests.

Dynamic and static methods for detecting flaky tests

Dynamic detection involves re-running tests under varying conditions to see if results change. This method is effective in identifying flaky tests, as it exposes the tests to different variables and environments, making it easier to spot inconsistencies. 

Static methods, on the other hand, analyze the code without executing tests. These methods often utilize machine learning techniques to identify patterns and potential flakiness in the code. While static methods may not catch all flaky tests, they can provide valuable insights into code quality and potential areas of concern.

Using both dynamic and static methods provides a robust approach to detecting flaky tests.

Using CI/CD pipelines for flaky test detection

CI/CD pipelines play a critical role in detecting flaky tests by streamlining testing processes and enhancing visibility into test behaviors. These pipelines facilitate the automation of test re-runs, helping to spot flaky behaviors more efficiently. Reviewing CI pipeline history provides insights to flag flaky tests and take corrective action.

Integrating flaky test detection into CI/CD pipelines ensures early identification, reducing the time and effort needed to address them. This proactive approach maintains the reliability of the test suite, allowing developers to focus on high-quality code.

Capturing test run data

Capturing detailed logs and metrics is crucial for analyzing test reliability and performance. This information aids in diagnosing flaky tests and ensuring trustworthy test outcomes. Saving memory maps and profiler outputs can help identify environmental impacts on test outcomes, providing valuable insights into the root causes of flakiness.

How to fix flaky tests?

Fixing flaky tests involves a systematic approach: diagnosing the issue, applying common solutions, and leveraging tools. Addressing flaky tests is crucial for maintaining software quality and developer productivity. Reproducing the issue involves running the test multiple times to confirm its flaky nature.

Once confirmed, diagnosing the issue requires identifying potential causes such as environmental differences or race conditions. Applying a fix may involve adjusting the test code, employing mocks to eliminate dependencies, or refactoring tests for better clarity. Implementing best practices like ensuring consistent test environments and writing focused tests can greatly reduce the occurrence of flaky tests.

Best practices to reduce flaky tests

To handle flaky tests effectively, focus on prevention strategies. Following best practices can lead to reliable and trustworthy testing outcomes. The process of addressing flaky tests generally involves three phases: diagnosis, mitigation, and fixing.

Implementing best practices, such as writing reliable tests, isolating test environments, and monitoring and quantifying flakiness, can significantly reduce the occurrence of flaky tests. Let’s explore these best practices in detail.

Writing reliable tests

Defining strict guidelines for writing tests can help in crafting more dependable tests. Testing experts advise creating small and focused tests. This approach is especially important for unit tests. Narrowly focused tests reduce complexity and lead to easier troubleshooting when issues arise. Additionally, non-determinism in tests can be prevented by injecting known data using fakes, stubs, and mocks, ensuring that tests produce consistent results.

Adopting these practices helps teams write tests that are less prone to flakiness and more reliable in their outcomes. Narrowly focused tests using controlled data inputs make it easier to identify and resolve issues, leading to a more robust and trustworthy test suite.

Isolating test environments

Tests can become flaky when environments lack isolation and consistency. When test environments are not isolated, state leakage can occur, leading to inconsistent test outcomes. Separating unit tests from integration tests minimizes interference and improves clarity, allowing each type of test to run in a controlled environment without impacting others.

Isolating the test environment prevents the interference that often leads to flaky tests. This approach ensures each test runs in a consistent and predictable environment, reducing state leakage and other issues that cause random failures.

Monitoring and quantifying flakiness

Monitoring and tracking test suite reliability over time is crucial for identifying flaky tests. This ongoing assessment helps teams address issues related to flaky tests promptly, ensuring that they are resolved before they can impact the development process. Companies can utilize dashboards to visualize flaky test occurrences and patterns, making it easier to monitor and manage test suite reliability.

Implementing monitoring and quantifying strategies allows teams to maintain high visibility into their test suite’s performance. This proactive approach ensures flaky tests are identified and addressed quickly, minimizing their impact on the development process and maintaining test suite reliability.

The bottom line

Flaky tests pose a significant challenge in software testing, creating uncertainty and undermining confidence in test results. Understanding the characteristics and causes of flaky tests is the first step in managing them effectively. Detecting flaky tests using dynamic and static methods, leveraging CI/CD pipelines, and capturing detailed test run data are essential strategies for identifying these elusive issues.

In addition, implementing best practices, such as writing reliable tests, isolating test environments, and monitoring test suite reliability, can significantly reduce the occurrence of flaky tests. By addressing flaky tests proactively, teams can maintain a high level of trust in their testing efforts, ensuring efficient development cycles and high-quality software releases.

Key takeaways

• Flaky tests produce inconsistent results and are often caused by race conditions, environmental differences, and non-deterministic code, complicating the testing process.
• Detecting and addressing flaky tests is crucial for maintaining software quality, developer productivity, and team morale, as they can lead to wasted time and a lack of trust in the test suite.
• Implementing best practices such as isolating test environments, writing reliable tests, and monitoring flakiness can significantly reduce the occurrence of flaky tests and improve overall testing reliability.

Dealing with flaky tests? Let us help you turn those frustrating failures into consistent success. Reach out and let's discuss how we can help you streamline your software testing efforts and improve quality assurance processes. 

Frequently Asked Questions

What are flaky tests?

Flaky tests are unreliable tests that yield inconsistent results, passing or failing randomly without any changes to the underlying code. Addressing flaky tests is crucial for maintaining a robust testing environment.

Why is detecting flaky tests important?

Detecting flaky tests is essential for ensuring software quality and enhancing developer productivity, as they introduce unpredictability and waste valuable time in debugging. Addressing flakiness improves the reliability of test outcomes and supports a more efficient development process.

What are some common causes of flaky tests?

Flaky tests are often caused by race conditions, environmental differences, non-deterministic code, and incorrect assumptions made while writing the tests. Addressing these issues can lead to more reliable and consistent testing results.

How can CI/CD pipelines help in detecting flaky tests?

CI/CD pipelines enhance the detection of flaky tests by automating test re-runs, which offers valuable insights into test performance and variability. This process allows teams to identify inconsistent tests more effectively.

What are some best practices to reduce flaky tests?

To effectively reduce flaky tests, focus on writing reliable tests, isolating test environments, and consistently monitoring the reliability of your test suite. Implementing these practices will enhance the stability and trustworthiness of your testing process.