Automated UI Testing: Tutorial and Guide

Modern applications often have robust user interfaces (UIs) with their own workflows, routing, and internal components. While techniques like functional and performance testing are used to monitor the responsiveness of an application’s underlying systems, alternative methods must be used to monitor the quality of in-app user interactions and visual rendering.

UI testing is the practice of using software tools to programmatically interact with and validate an application’s user interface. Engineering teams use this process to verify the functionality, usability, and consistency of a user interface across different scenarios and environments.

Automating the UI testing process helps teams detect issues early in development and validate code changes. This is often done by integrating UI testing steps into continuous integration and deployment workflows. Emerging tools go a step further, leveraging AI and machine learning to automate UI test maintenance. This article is a guide to the technical concepts and best practices to know when building a UI testing strategy.

Summary of automated UI testing concepts

Overview of automated UI testing

The typical actions involved in a UI test might include simulating user actions and verifying UI elements. Tests might check for the presence, state, and properties of UI components like buttons, forms, and text. As part of this process, the test simulation may mimic clicks, text input, form submissions, and other user interactions.

Specialized types of UI testing include, but are not limited to the following:

• Cross-browser and cross-device testing: Ensuring consistent behavior across different browsers and device types.
• Visual regression testing: Quickly identifying if new code changes have inadvertently broken existing functionality.
• Performance validation: Measuring load times and responsiveness of UI elements, such as the load times for a component with many data elements.

Core components of automated UI testing tools

There are several key components of these tools to look for:

• Cross-platform compatibility: As software applications increasingly span multiple platforms and devices, maintaining consistency across different environments becomes essential. Automated testing tools enable developers to execute tests seamlessly across various operating systems and browsers, ensuring that all users have a consistent experience regardless of their device.
• Integration with CI/CD: Continuous testing aligns with agile development practices and rapid support responses. Adding UI test build checks (to be run when new code is checked in) helps identify issues early in the development cycle, promoting faster iterations and enhancing software reliability.
• Real-time feedback and analysis: Automated testing tools provide immediate feedback and detailed analysis during test execution. This capability allows developers to quickly identify and address issues, streamlining the debugging process and significantly reducing the time to market for new features and fixes.

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Challenges and limitations of automated UI testing

While automated UI testing offers numerous benefits, it’s important to be aware of its challenges and limitations.

Implementing automated UI testing requires an upfront investment in tools, training, and infrastructure. This can be time-consuming and potentially costly, especially for smaller teams or projects.

As applications evolve, test scripts need to be updated to reflect changes in the UI. Maintaining an up-to-date test suite in dynamic software environments can be challenging. Some teams handle this manually, but this approach can be difficult to scale.

Finally, it’s challenging to automate every possible user interaction or scenario, meaning that some edge cases might be missed by automated tests. Some tests may become “brittle” over time, losing stability and giving intermittent false results.

Benefits of AI-powered UI testing

Modern, AI-powered tooling can dynamically generate tests, moving beyond traditional testing methodologies that rely on static test cases. Developers craft these tests based on observed user behaviors and system interactions, allowing for broader coverage and the proactive coverage of potentially unanticipated edge cases. This mitigates the traditional challenges of time overhead and test suite entropy.

The proper balance between automation and manual intervention depends on individual team goals, SLAs, and operational details. Engineering teams should weigh the tradeoffs between automation and manual testing approaches to see what balance of the two is correct for them.

Choosing a testing strategy

Every engineering team has to decide on the proper amount of test coverage for its applications. While full test coverage is always desirable, it comes with the tradeoff of developer time to set up. In practice, 100% test coverage may be infeasible in significantly large or complex codebases.

To strike the right balance, consider any combination of the strategies detailed below.

Qualiti removes the time overhead of building and maintaining a test suite by using NLP techniques to analyze and update tests as needed. As code versions are added, test cases can automatically be updated, prioritized, and organized into Smart Folders. Qualiti’s Test Plans can be scheduled or triggered automatically to run in accordance with any workflow or release schedule.

Prioritization of critical features

Start by automating tests for the most critical and frequently used features of your application. These are typically:

• Core business logic
• User authentication and authorization flows
• Data processing and storage operations
• Key user journeys and workflows

By focusing on these high-value areas first, you ensure that the most impactful aspects of your application are robust and reliable.

Risk-based testing

Conduct a risk assessment of your application to identify areas that are prone to frequent changes, historically buggy, critical to business operations, or difficult to manually test.

Prioritize automated testing for these high-risk areas to maximize the return on your testing investment.

Incremental coverage expansion

Begin with a core set of automated tests and gradually expand coverage over time, which takes into account resource allocation considerations and allows for incremental refinement. In other words, start by automating tests for the most critical functionalities, then progressively add tests for less critical areas as resources permit. This strategy offers several benefits:

• It allows teams to see immediate value from automation efforts.
• It provides opportunities to learn and refine the testing process over time.
• It helps manage the initial investment in time and resources.
• It allows for a more manageable learning curve for team members new to automated testing.

As the team becomes more proficient with automated testing tools and processes, they can continually assess and expand test coverage to encompass more of the application’s functionality.

Developing reusable test components

Create modular and reusable test scripts, functions, or classes that can be easily adapted for different scenarios. This approach reduces the effort needed to create new tests, improves consistency across test suites, and simplifies codebase maintenance.

Implementing this approach may be simple or complex, depending on the coding techniques used. If code is modular and testable, automated tools can select and test each of them in isolation. The most common approach to modular testing is to separate larger code elements (such as pages, shopping carts, or widgets) into smaller, testable components. Forms, inputs, page sections, and interactive elements can thus be reused across the application.

Popular modern front-end coding frameworks, such as Angular or React, are likely to follow componentized conventions that ensure component reusability and testability. Engineers should still take care when using elements such as iframes, dynamic content loaders, and third-party widgets, which can have on-screen visual rendering issues.

Regular test suite maintenance

Fast-paced teams with shifting priorities may find it useful to regularly optimize their testing workflows as business needs change. These teams will find it useful to schedule regular reviews and updates of the test suite in order to do the following:

• Remove obsolete or redundant tests
• Update tests to reflect changes in the application
• Update testing strategies to reflect KPI updates or business requirements
• Identify gaps in coverage
• Optimize test performance

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Choosing the right automation tool

Automated UI testing is performed using tooling, and the right tool should be selected with care. Setting up an automated workflow begins with defining clear testing objectives that outline the scope, types of tests needed, and expected coverage. Choosing the right tools and focusing on compatibility with the application’s platforms, features, and integration capabilities is crucial. The tools are then installed and configured according to the project’s specific requirements.

A test environment should mimic the production setting to reflect real-world usage as accurately as possible. Over time, developers typically strive to create test cases to cover all in-app functionality, ensuring comprehensive testing. These cases guide automated tools through the application and may be customized to address specific requirements or edge cases.

Test execution involves monitoring progress and analyzing results to identify any defects or areas for improvement. This process is iterative, with continual refinements based on feedback from test cycles to adapt to application UI changes.

Integrating automated testing into CI/CD pipelines automates testing within the development process, facilitating early defect detection and faster product releases. Adequate documentation and training ensure all team members can utilize the testing tools efficiently and adhere to best practices.

By efficiently setting up and managing automated UI tests, development teams can ensure that their applications meet high quality and performance standards, enhancing user experiences across platforms.

Dynamic element identification

Dynamic element identification is an often-desired feature in a UI testing tool. It enables interaction with UI elements that change based on user actions, data updates, or other factors. This ensures accurate simulation of user behaviors and comprehensive test coverage.

Dynamically alterable elements like position, size, color, or behavior pose unique challenges. To mitigate these challenges, some tools use advanced locator strategies that dynamically identify UI elements based on attributes, enhancing adaptability and maintaining test effectiveness as applications evolve.

These advancements help create resilient, automated testing systems that handle modern, dynamic user interfaces. Such capabilities form the baseline of visual regression testing, a transformative testing technique that enables historical issue tracking in the UI.

Dynamic waiting

Dynamic waiting is a technique used in automated testing to make tests more reliable and efficient by avoiding fixed delays. Instead of using hard-coded timeouts or sleep functions, which can cause issues in test environments due to varying load times or system performance, dynamic waiting allows the test to proceed as soon as a specific condition is met.

As a technique, dynamic waiting makes tests more robust and less prone to false failures (due to race conditions or timeouts), while also optimizing test execution time.

Hard-coded timeouts and sleep functions tend to cause issues in test environments. Timing issues  on queries are more likely, because requests might be executed at Instead of using fixed delays, implement dynamic waits to handle alert dialogs efficiently. Use a wait condition that checks for the presence of the alert, allowing the test to proceed as soon as the dialog appears.

Let's explore an example of dynamic waiting in Cypress, specifically for handling alert dialogs.

In the following code, a  listener is created for the 'window:alert' event. This allows for the capture and verification of  the contents of any alert that appears. We click a button (with the id 'trigger-button') that is expected to trigger an alert. Cypress's waitUntil  function  implements dynamic waiting. This function repeatedly checks a condition until either it returns true or a timeout is reached. In the waitUntil function, we check whether win.alert.called  is true, indicating that an alert has been triggered.

A maximum timeout of 5000 milliseconds (5 seconds) is set, along with an interval of 100 milliseconds between checks.

Once the button is clicked, check if an alert has appeared within 5 seconds:

cy.on('window:alert', (text) => {
  expect(text).to.contain('Expected alert message');
});

cy.get('#trigger-button').click();

cy.waitUntil(() => {
  return cy.window().then((win) => {
    return win.alert.called;
  });
}, { timeout: 5000, interval: 100 });

This approach ensures that  test waits only as long as necessary for the alert to appear, up to a maximum of 5 seconds. If the alert appears immediately, the test continues without unnecessary delay. If the alert doesn't appear within 5 seconds, the test will fail, helping us identify potential issues.

Visual regression testing

Visual regression testing focuses on identifying unintended changes to an application’s UI betweens app versions. In this form of testing, before-and-after screen captures are taken of components of the app at various points in the version history. Screen captures may be taken for all components in each run or only for changed components. Visual regression testing adds a historical reference point for engineers, where they can check how code changes affect the UI for end users. It is commonly used as a part of the issue tracking process for engineers or QA personnel. Visual regression testing enables testers to detect discrepancies early in development.

For example, imagine that a development team has UI testing coverage for its application. As team members update pages or components, initial screenshots can serve as a baseline for comparison. As new UI elements are added, automated UI testing captures new screenshots to compare against the baseline, highlighting layout shifts, changes to element styling, and potentially erroneous element modifications.

Visual regression testing is perhaps most commonly used in CI/CD pipelines, automatically validating every code commit or deployment. This integration promotes continuous delivery and maintains high software quality. Reporting and visual differences highlighted in the tests provide clear insights, facilitating quick debugging and issue resolution.

Overall, visual regression testing ensures that all visual aspects of an application meet the design specifications and user expectations, maintaining high visual quality even in dynamic software environments.

Best practices for writing effective UI tests

To maximize the benefits of automated UI testing, consider the following best practices:

• Keep tests focused and atomic: Write tests that focus on a single functionality or user flow. Where possible, keep code similarly organized, which makes tests easier to maintain and debug.
• Use descriptive naming: Name tests clearly to describe what they’re checking. This helps in understanding test results and maintenance. Page and component names should be similarly reflective of their intended location or purpose.
• Handle waits properly: Implement dynamic wait functions instead of hard-coded timeouts to make tests more reliable and faster.
• Make tests independent: Ensure that manually written tests can run independently and in any order. Avoid dependencies between tests.
• Use stable locators: Where relevant, prefer stable element locators (like IDs or data attributes) instead of relying on text contents or CSS classes that might change frequently.
• Implement proper error handling: Include informative error messages and logging to make debugging easier when tests fail.
• Regularly review and refactor: Periodically review and refactor test code to keep it clean, efficient, and up-to-date with the latest best practices.
• Version control your tests: Keep test scripts in version control with application code to track changes and collaborate effectively.
• Prioritize test coverage: Focus on critical user paths and high-risk areas of the application first, then expand coverage over time.

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Conclusion

Automated UI testing encompasses a range of strategies and tools that work together to create a robust testing framework. By implementing automated UI testing, development teams can significantly reduce the time and effort required for manual testing while increasing test coverage and accuracy. The ability to run tests consistently and frequently allows for early detection of issues, leading to faster development cycles and improved software quality.

As technology continues to evolve, the future of automated UI testing looks promising. The integration of AI and machine learning is revolutionizing the field, enabling more intelligent test generation, maintenance, and execution. Tools like Qualiti are at the forefront of this evolution, offering dynamic test suite management and reducing the overhead associated with traditional testing approaches.

However, it’s important to remember that successful implementation of automated UI testing requires planning. Teams must consider factors such as test prioritization, risk levels, and monitoring strategies.

As applications become more complex and user expectations continue to rise, automated UI testing will play an increasingly important role in ensuring software quality and user satisfaction. By staying informed about best practices and emerging technologies in this field, development teams can position themselves to deliver high-quality, user-friendly applications in an efficient and cost-effective manner.