flaky (Test Automation)

Why This Matters

In this full guide, we'll explore how to create robust test automation using JavaScript and popular libraries like Cypress, Selenium, and Playwright. We'll focus on minimizing flaky tests, which can cause significant delays in development cycles and reduce trust in your test suite.

Why This Matters

Flaky tests are a common issue in test automation that can lead to wasted time, missed regressions, and decreased confidence in the testing process. A flaky test is one that passes sometimes but fails at other times without any code changes. Flaky tests can be caused by various factors such as network instability, race conditions, or even browser-specific issues.

Eliminating flaky tests is crucial for ensuring the reliability of your test suite and maintaining a high level of confidence in your software's quality. By addressing flaky tests, you can save time, reduce frustration, and improve the overall efficiency of your development process.

Prerequisites

To follow this guide, you should have a basic understanding of JavaScript, HTML, and CSS. Familiarity with one or more test automation libraries (Cypress, Selenium, Playwright) is also beneficial but not required as we'll provide explanations throughout the lesson.

Core Concept

Test automation involves writing scripts that execute a series of predefined actions on an application under test and verify the expected results. This process helps to ensure that the software behaves as intended, and it can be particularly useful for regression testing, where the goal is to verify that changes in the codebase have not introduced any unintended side effects.

Flaky tests arise when a test script passes sometimes but fails at other times due to unpredictable factors such as network instability or race conditions. These tests can be frustrating and time-consuming, as they require repeated runs to ensure that the failure was not a false positive.

To minimize flaky tests in your test automation suite, it's essential to understand their root causes and implement strategies for mitigating them. Here are some common reasons for flaky tests:

1. Race conditions: These occur when multiple actions are performed concurrently, and the order in which they complete can affect the outcome of the test. For example, if a test script clicks a button and then checks that the expected element is visible, but another action modifies the page before the check is performed, the test may fail even though the application behaves correctly when run manually.
2. Network instability: Flaky tests can also be caused by network issues such as slow connections or temporary outages. In these cases, the test script may time out or encounter errors that would not occur under ideal network conditions.
3. Browser-specific issues: Different browsers may have different rendering engines and quirks that can cause tests to fail inconsistently across platforms. For example, a test script that relies on specific CSS styles may pass in Chrome but fail in Firefox due to differences in the way the two browsers handle those styles.
4. Test design issues: Poorly designed tests can also contribute to flakiness. For instance, tests that rely on hard-coded values or assumptions about the state of the application can break when those values change or when the application behaves differently than expected.

To minimize flaky tests, it's essential to write robust test scripts that are designed to handle a variety of scenarios and edge cases. Here are some strategies for doing so:

1. Wait for elements to load: Instead of assuming that elements are immediately available on the page, use JavaScript to wait for them to load before performing actions or making assertions. This can help prevent race conditions and ensure that tests are only executed when the relevant elements are present.
2. Use explicit waits instead of implicit waits: Implicit waits can cause flaky tests because they rely on the browser's default wait time, which may not be sufficient in some cases. Explicit waits, on the other hand, allow you to specify a specific amount of time to wait for an element to load or a condition to be met.
3. Test under various conditions: To ensure that your tests are robust and reliable, it's essential to test them under a variety of conditions, such as different browsers, network speeds, and device types. This can help you identify potential issues before they become flaky tests in your production environment.
4. Use stable selectors: Instead of relying on complex CSS selectors that may change over time, use simple and stable selectors to target elements in your test scripts. This can help reduce the likelihood of false positives and make your tests more maintainable.
5. Write robust assertions: To minimize flaky tests caused by unreliable assertions, write assertions that are specific and tolerant of minor differences in the application's behavior. For example, instead of checking that a button's text exactly matches a hard-coded value, you could check that it contains the expected text or is close enough to the desired value.
6. Use test data: To minimize the impact of flaky tests on your development cycle, use test data that is representative of real-world scenarios but is not critical for the application's functionality. This can help you identify issues without affecting the production environment.
7. Implement retries and timeouts: To handle unpredictable factors such as network instability or race conditions, implement retries and timeouts in your test scripts. Retries allow the script to attempt an action multiple times before giving up, while timeouts prevent the script from waiting indefinitely for a condition to be met.
8. Monitor test results: To identify flaky tests quickly, monitor the results of your test suite and track the number of failures over time. This can help you prioritize tests that need attention and ensure that your test automation is providing value.

Worked Example

Let's create a simple test script using Cypress to demonstrate some of these strategies for minimizing flaky tests. In this example, we'll test the functionality of a login form on a web application.

describe('Login functionality', () => {
beforeEach(() => {
cy.visit('/login') // Visit the login page
})

it('should allow valid credentials', () => {
cy.get('#username').type('valid_user') // Type the username
cy.get('#password').type('valid_password') // Type the password
cy.get('#submit').click() // Click the submit button
cy.url().should('include', '/dashboard') // Verify that we are on the dashboard page
})

it('should not allow invalid credentials', () => {
cy.get('#username').type('invalid_user') // Type an invalid username
cy.get('#password').type('invalid_password') // Type an invalid password
cy.get('#submit').click() // Click the submit button
cy.get('.error-message').should('contain', 'Invalid credentials') // Verify that an error message is displayed
})
})

In this script, we've used explicit waits by calling cy.get() to wait for the relevant elements to load before performing actions or making assertions. We've also written robust assertions by checking for the presence of an error message instead of relying on a specific text string.

To handle potential race conditions, we could add retries and timeouts to our test script:

describe('Login functionality', () => {
beforeEach(() => {
cy.visit('/login') // Visit the login page
})

it('should allow valid credentials', () => {
cy.get('#username').type('valid_user') // Type the username
cy.get('#password').type('valid_password') // Type the password
cy.get('#submit').click() // Click the submit button
cy.url().should('include', '/dashboard', { timeout: 10000 }) // Verify that we are on the dashboard page within 10 seconds
.then(() => {
// If we're still on the login page after 10 seconds, retry the test
if (cy.location('pathname').includes('/login')) {
cy.retry()
}
})
})

it('should not allow invalid credentials', () => {
cy.get('#username').type('invalid_user') // Type an invalid username
cy.get('#password').type('invalid_password') // Type an invalid password
cy.get('#submit').click() // Click the submit button
cy.get('.error-message').should('contain', 'Invalid credentials', { timeout: 10000 }) // Verify that an error message is displayed within 10 seconds
.then(() => {
// If we're still waiting for the error message after 10 seconds, retry the test
if (!cy.get('.error-message').isVisible()) {
cy.retry()
}
})
})
})

In this updated script, we've added retries and timeouts to handle potential race conditions or network instability. If the test fails to meet the specified conditions within the timeout period, it will retry the action until successful or reach a maximum number of retries.

Common Mistakes

1. Relying on implicit waits: Implicit waits can cause flaky tests because they rely on the browser's default wait time, which may not be sufficient in some cases. Instead, use explicit waits to specify a specific amount of time to wait for an element to load or a condition to be met.
2. Using complex CSS selectors: Complex CSS selectors can make your tests brittle and prone to flakiness because they may change over time. Instead, use simple and stable selectors to target elements in your test scripts.
3. Not handling race conditions: Race conditions can cause tests to fail even when the application behaves correctly. To minimize this issue, wait for elements to load before performing actions or making assertions, and consider implementing retries and timeouts in your test scripts.
4. Writing brittle assertions: Brittle assertions can cause flaky tests because they rely on specific values that may change over time. Instead, write robust assertions that are tolerant of minor differences in the application's behavior.
5. Not testing under various conditions: Testing your application under a variety of conditions can help you identify potential issues before they become flaky tests in your production environment. Consider testing on different browsers, network speeds, and device types.
6. Ignoring test results: Monitoring the results of your test suite and tracking the number of failures over time can help you prioritize tests that need attention and ensure that your test automation is providing value.
7. Not using test data: Using test data that is representative of real-world scenarios but is not critical for the application's functionality can help minimize the impact of flaky tests on your development cycle.

Practice Questions

1. How can you minimize race conditions in your test scripts?
2. What are some strategies for writing robust assertions to minimize flaky tests?
3. Why is it important to test under various conditions, and what factors should you consider when doing so?
4. How can you handle unpredictable factors such as network instability or race conditions using retries and timeouts in your test scripts?
5. What are some common mistakes that can lead to flaky tests, and how can you avoid them?

FAQ

Q: Why do flaky tests occur, and why are they a problem?

A: Flaky tests occur due to unpredictable factors such as network instability, race conditions, or browser-specific issues. They are a problem because they can cause wasted time, missed regressions, and decreased confidence in the testing process.

Q: How can I minimize flaky tests in my test automation suite?

A: To minimize flaky tests, you should write robust test scripts that are designed to handle a variety of scenarios and edge cases. This includes waiting for elements to load, using explicit waits instead of implicit waits, testing under various conditions, using stable selectors, writing robust assertions, using test data, and implementing retries and timeouts.

Q: What strategies can I use to write robust assertions?

A: To write robust assertions, you should make them specific and tolerant of minor differences in the application's behavior. Instead of checking that a button's text exactly matches a hard-coded value, you could check that it contains the expected text or is close enough to the desired value.

Q: How can I handle unpredictable factors such as network instability using retries and timeouts in my test scripts?

A: To handle unpredictable factors such as network instability, you can implement retries and timeouts in your test scripts. Retries allow the script to attempt an action multiple times before giving up, while timeouts prevent the script from waiting indefinitely for a condition to be met.

Q: What are some common mistakes that can lead to flaky tests, and how can I avoid them?

A: Some common mistakes that can lead to flaky tests include relying on implicit waits, using complex CSS selectors, not handling race conditions, writing brittle assertions, not testing under various conditions, ignoring test results, and not using test data. To avoid these mistakes, follow best practices for writing robust test scripts and monitor your test suite's performance to identify potential issues.