What is visual regression testing? It is a type of regression testing that aims to ensure that any changes to the program do not adversely affect the graphical user interface (GUI). It is also referred to as visual validation testing. Instead of focusing on the functionality of the software, its aim is to verify the software aesthetics.

Visual regression testing verifies that all visual elements display correctly across all available browsers, devices and platforms. These elements can include buttons, menus, icons, text and fields.

Visual testing vs functional testing

There are several differences between visual testing and functional testing. Visual testing focuses on the appearance of the application, while functional testing focuses more on whether the application works. With good visual regression testing, QA testers (check also the IT Tester Consultant Medior job position) can be sure that users will have a good visual experience. Testers must test many aesthetic aspects of the visual element including:

• Size,
• Width,
• Length,
• Location,
• Visibility (whether the user can see the element),
• Readability (whether the user can easily read the text and information on the element),
• Alignment (whether the UI element is well positioned in relation to other elements),
• Consistency across screen resolutions (whether the layout remains the same across screens).

As you can see in the screenshot above, the Windows screen behaves a bit chaotically after the version update. It may not affect the end result of the Windows update, but it’s certainly not OK for the GUI.

Visual regression testing is there to avoid such scenarios.

The importance of visual regression testing

User interface (UI) design is critical to the user experience of a product. Good user interface design makes the interaction between users and digital products or services as seamless as possible. This has a positive effect on user engagement, which then improves brand image and ultimately economic results.

Without visual regression testing, we risk existence of visual bugs going unnoticed and slipping into the GUI of the application. The GUI is what the user sees. If the app’s GUI is too buggy, the user will have trouble navigating the product.

Poor aesthetics and usability can make potential customers reluctant to buy or use the product, leading to lost sales opportunities. In addition, a poor graphical user interface is commonly associated with a lack of professionalism. A misplaced button or poor text layout can reduce user confidence in the quality of the product. If you want to position yourself well in the market, try to maintain a sense of professionalism through proper visual regression testing.

Manual visual testing

Manual visual regression testing is the traditional approach to visual testing. Testers do not use any visual testing tools. They use their own visual vigilance to detect a bug, and this approach is actually quite common among many testers.

However, testers are human and humans make mistakes. Due to the variety of screen sizes, browsers and devices to be tested on, manual testing is not the best approach.

Can you spot 11 differences in these two pictures? Try it, record the time it takes you to do it, and imagine you’re doing it repeatedly for hundreds of browsers and devices, and this is still just one image. It is simply impossible to manually test all the visuals.

However, this does not mean that manual testing is not necessary. When performing ad hoc or exploratory testing, manual testing is faster and easier. For large-scale testing, we need to have automated visual regression testing.

Automated visual testing using artificial intelligence

False positive results in visual regression testing

A false positive result in visual regression testing is when testers report that an element is visually defective when in fact it is not. False positives in visual testing can have a negative impact on the development process. This is because teams need to filter out these “false positives” before they can start fixing critical issues.

A common approach to visual regression testing is to compare a reference or baseline image of the desired user interface with the actual user interface in order to find differences between them. These differences represent visual regressions that need to be corrected. This approach is known as the pixel matching or image matching approach. It may sound simple, but there are some fundamental weaknesses that have led to false positives, including:

• Dynamic content: all websites and apps have dynamic elements such as the date, time or basket icon on the e-commerce website. Visual regression test scripts register these changes as errors, but usually they are not.

These are all normal shopping carts, but they can be flagged as bug with the image comparison approach.

• Animations and GIFs: animations and GIFs belong to the category of dynamic content. The “Load” button also counts as an animation and can cause false positives in visual regression testing.
• Rendering differences: different hardware configurations render images differently. This results in differences in colours. These differences are very difficult to account for in visual test scripts.
• Padding/margin: similarly, padding and margin on the screen vary across devices, browsers and systems.
• Font size and colours: font-related differences should not always be classified as visual errors. However, automated visual testing scripts don’t always understand this.

The number of test objects and the sensitivity to minor changes in the user interface make the image matching technique unreliable. This is where visual regression testing tools come into play. These tools are equipped with robust features that make life easier for visual regression testers.

Visual regression testing tools

Visual regression testing tools, which are typically equipped with artificial intelligence features, support the visual testing process by reducing the risk of false positives. This allows teams to conserve resources and focus on what’s really important. Visual regression testing tools are developed based on an image matching approach. Testers do not need to manually compare the actual GUI with the expected GUI to detect visual errors.

To address the sensitivity of the Image Comparison technique, many visual testing tools allow testers to identify and “ignore” dynamic zones. These zones will not be flagged as an error if changes are made to them.

A new feature introduced by many visual regression testing tools is Layout Comparison. This function defines and compares different zones between the basic GUI and the actual GUI to highlight visible layout changes. It adds more depth to the visual testing process.

Another interesting feature is text/content based matching. It uses machine learning to extract and compare on-screen text regardless of font size, font and font colour. Small differences in the handwriting will not be considered as errors.

Visual testing tools are divided into automated visual testing tools and open source visual regression testing tools.

However, it should be noted that the demand for visual testing alone is not that high. Testing teams need a platform that supports visual regression testing and other types of testing, especially UI and API testing. With such a platform, teams can better manage software quality. In short, a good visual regression testing tool/platform should have the following features:

• visual comparison options,
• support for automated visual testing ,
• integration with other testing frameworks,
• cross-browser testing,
• API/UI testing support,
• testing in the cloud,
• reporting and analysis functions,
• opportunities for cooperation.

If equipped with the above features, this visual regression testing tool can really transform and facilitate visual testing. Below, we’ve listed some of the best and most popular visual testing tools in 2024.

Top visual regresion tool in 2024

Visual testing Katalon

The Katalon platform is known as an all-in-one QA platform. Katalon is built on Appium and Selenium, allowing you to perform functional testing and visual testing in one place. The Katalon platform has many visual testing features to help your team achieve visual quality along with usability. All of these features are powered by artificial intelligence, which reduces the risk of false positives and increases accuracy, leading to improved efficiency.

Katalon can detect and capture critical elements of an application’s user interface and then create a baseline image for comparison. It can also detect and highlight dynamic areas of the application, such as banners or pop ups. These areas will not be marked as bugs even if they change during the tests.

Even better, Katalon allows teams to test across a wide range of devices and browsers. Instead of investing in lots of physical machines, teams can allocate their resources to more critical areas. Once tested, the Katalon platform generates detailed analytics and reports to improve decision-making.

Most important features:

• a centralized platform for performing both functional and visual testing,
• AI-driven features (layout matching, text-to-text matching),
• on-cloud testing environments on many devices,
• self-regulating functions for automatic maintenance of automated visual tests,
• seamless integration with CI/CD pipelines such as Jenkins, GitLab and Bamboo.

Price: the Katalon Platform is free to use forever. For more advanced features and quotas, Katalon offers an attractive annual pricing plan.

Visual testing Kobiton

Kobiton’s Visual Testing solution is a comprehensive mobile testing solution with a user-friendly interface. There is also no setup or integration required. Just run one basic manual session on a real device. The AI engine takes care of the rest.

The automated visual testing solution can capture metadata from each test execution, analyze and compare individual pages across devices. It will then pinpoint any visual inconsistencies regarding the layout, structure and colours of the page. Kobiton also provides recommendations on how to improve the app’s appearance and user experience.

Main features:

• Kobiton can capture screenshots of every screen and action performed during functional testing. These screenshots serve as baseline images for automated comparison. It is admirable that Kobiton does not request additional fees for the number of visual comparisons performed,
• AI-driven repair and recommendations for immediate problem solving,
• easily add parameters and datasets to the test without scripts that can be automatically executed by AI,
• compare your UI and UX design with leading apps in the same market,
• performance testing without scripts.

Visual UI testing Applitools

Applitools is one of the most popular visual testing tools on the market. It entered the market relatively early compared to other suppliers. Applitools has changed the visual testing landscape by introducing scanning technology to humanize test scripts and shorten the product release cycle. Read our article Applitools and UX testing.

Most important features:

• Applitools Eyes: AI-powered computer vision algorithms that mimic the human eye to efficiently find both visual and functional regressions,
• can detect dynamic content such as ads or personalized dashboards and ignore them,
• integrates with Cypress, Selenium or other testing frameworks, then run directly in your favourite CI/CD tool: Jenkins, GitLab, GitHub, CircleCI and more,
• integrates with Jira and other bug reporting tools for better results and reporting.

Visual testing Percy (from BrowserStack)

Percy is a visual regression testing solution from BrowserStack. Percy allows you to perform intelligent visual testing across browsers and devices. It can make intelligent comparisons, group these visual changes together, and then select only the most significant visual regressions. It also has a comments and notifications feature that helps your team stay informed about the progress of the project.

Most important features:

• automatic status updates in download requests whenever visual changes are detected,
• image stabilization technology automatically freezes the animation to minimize false positives,
• ignoring specific areas on the page,
• seamless integration into existing CI/CD workflow,
• support for popular test automation frameworks and languages.

AyeSpy

AyeSpy is a lesser known but actually quite useful tool for automating visual testing. It is one of the best free open source tools for visual testing.

Most important features:

• runs on Selenium Grid,
• inspired by Wraith and Backstop – both popular visual regression testing tools,
• according to its creators, the USP of this tool is to improve its performance compared to other visual testing tools (it runs 40 screen comparisons per minute),
• straightforward setup with simple documentation for the team to start testing faster and easier,
• Screenshots can be taken for multiple branches, reducing testing time.

LambdaTest

LambdaTest offers an intelligent visual testing feature that allows teams to compare two image layouts and detect discrepancies. LambdaTest’s image-to-image comparison technology helps testers easily find even the smallest visual defects by uploading screenshots of the baseline and comparison images. Its AI engine takes care of the rest.

Most important features:

• intelligent visual regression testing in the cloud that can identify visual errors related to icon size, padding, colour, layout, text, as well as element positions,
• you can choose from more than 3,000 real browsers and operating systems, including Chrome, Firefox, Safari, Internet Explorer, Edge and more,
• parallel testing supported to reduce test execution time 10x,
• diverse integration ecosystems supporting more than 120 integrations.

SikuliX

SikuliX is one of the best open source visual regression testing tools using image recognition technology and a control GUI. Testers can identify a particular button on the screen and then interact with the identified button by controlling the mouse and keyboard. This makes SikuliX handy when you don’t have access to the source code of an application or web page.

Most important features:

• can be used to automate Flash objects / Flash web pages,
• can perform visual testing of websites, desktop applications on Windows, Linux, Mac, iPhone and Android,
• can automate certain tasks in the graphical user interface, even if you don’t know the element IDs,
• can be easily integrated into other third-party applications.

Conclusion

Visual regression testing is an important approach to ensure a quality GUI for your application’s users. Manual testing and automated UI testing using open source tools can be tedious and inefficient. That’s why you need to invest in a low-code solution for the long term satisfaction.

There are several leading visual regression testing tools available on the market that leverage AI/ML (artificial intelligence/machine learning) to maximize their effectiveness. These solutions can quickly and accurately detect changes in the graphical user interface and pinpoint errors. With these quality solutions, organizations can be confident that their product is being deployed as effectively as possible. We hope that we have helped you to choose the right tool for visual testing, or at least given you the necessary information about the different tools and their functions.

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