7+ Best Visual Regression Testing Tools For Testers

What is Visual Regression Testing?

Visual regression testing is a type of regression testing to ensure that no changes to the program 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, it aims to validate the software’s aesthetic side.

Visual regression testing verifies that all visual elements are displayed properly across all available browsers, devices, and platforms. These elements may include buttons, menus, icons, text, and fields. 

There are major differences between visual testing vs functional testing. Visual testing focuses on the look of the application, while functional testing focuses more on whether the app works.

With good visual regression testing, QA teams can be sure that users will have an amazing visual experience. Testers have to perform tests for many aesthetic aspects of a visual element, including:

• Size
• Width
• Length
• Position
• 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-placed in relation to other elements)
• Consistency across all screen resolutions (whether the layout remains the same on different screens)

As can be seen in the image above, after a version update, the Windows screen goes chaotic. This may not affect the end result of the Windows update, but something wrong is going on for the GUI.

In a worse-case scenario, the visual bugs can heavily impact the User Experience. The image above was a bug from an electric bike/e-scooter sharing app. With this messy interface, users will sure have a difficult time navigating around and performing the task they wanted. 

Visual regression testing is there to prevent all of the scenarios above from happening. 

Why Automate Your Visual Testing?

Manual visual regression testing is the traditional approach to visual testing. Testers don’t employ any visual testing tools. They use their own visual acuity to spot the bug, and this approach is actually quite common among many testers. 

However, testers are humans and humans make errors. Considering the number of screen sizes, browsers, and devices to be tested on, manual testing is not the best approach.

Can you spot 11 different spots in these 2 images? Try it, record your time, and imagine doing that repeatedly for hundreds of browsers and devices.

That does not mean manual testing is unnecessary. 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. 

Risks of false positives

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

A common approach to visual regression testing is comparing a referenced or baseline image of the desired UI with the actual UI to find differences between them. Those differences are visual regressions to be fixed. This approach is known as the Pixel-based Comparison or Image Comparison approach. It may sound straightforward, but they have some underlying weak points that gave rise to false positives, including:

• Dynamic content: all websites and applications have dynamic elements such as date, time, or the Cart icon on eCommerce websites. Visual regression test scripts register these changes as bugs, but they are usually not.

• Animation & GIFs: animation and GIFs fall under the category of dynamic content. The “Loading” button is also counted as animation, and it can cause false positives in visual regression testing. 
• Rendering differences: different hardware configurations render images differently. This results in discrepancies in color and anti-aliasing. These differences are extremely hard to account for in visual test scripts
• Padding/margin: similarly, on-screen padding & margins vary across devices, browsers, and systems
• Font size & colors: font-related differences should not always be classified as visual bugs. However, automated visual testing scripts do not always understand this. 

The number of objects to test and the sensitivity to minor changes in the UI makes the Image Comparison technique unreliable. This is when visual regression testing tools come into play. These tools come with robust features that make life easier for visual regression testers.

What Are Visual Regression Testing Tools?

Usually packed with AI features, visual regression testing tools support the visual testing process by reducing the risk of false positives. This allows teams to save resources and focus on what truly matters. Visual regression testing tools are built on the basis of the Image Comparison approach. Testers don’t have to manually compare the current GUI with the expected GUI to spot visual bugs. 

To address the sensitivity of Image Comparison technique, many visual testing tools allow testers to identify and ‘ignore’ dynamic zones. These zones will not be flagged as a bug if changes occur there. 

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

Another interesting feature is text/content-based comparison. It leverages Machine Learning to extract and compare text on the screen regardless of font size, family, and color. Negligible font discrepancies will not be seen as bugs. 

Visual testing tools are categorized 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 these features:

• Visual comparison capabilities
• Support for automated visual testing 
• Integration with other testing frameworks
• Cross-browser testing
• Support API/UI testing
• On-cloud testing
• Reporting and analytics features 
• Collaboration capabilities

If equipped with the aforementioned features, that visual regression testing tool can truly be a game changer for any QA professionals.

Best Automated Testing Tools and Visual Testing Frameworks

1. Katalon 

Katalon is known as the All-In-One quality management platform. Katalon is built on Appium and Selenium, allowing you to perform functional testing and visual testing in 1 single place. Katalon has many visual testing features to help your team achieve visual quality along with usability. These are all AI-powered features that reduce risk of false positives, increase accuracy, resulting in improved efficiency. 

Katalon can detect and capture the critical UI elements of your application, then create a baseline image to compare against. It can also detect and highlight dynamic regions of the application such as banners or pop-ups. These regions will not be flagged as bugs even if they change during tests. 

What’s better is that Katalon allows teams to test across a wide range of devices and browsers. Instead of investing in tons of physical machines, teams can allocate their resources to more critical areas. After testing, Katalon generates detailed analytics and reports for improved decision making.

Highlighted Features:

• A centralized platform to perform both functional and visual testing
• AI-powered features (Layout Comparison, Text-to-text Comparison)
• On-cloud test environments on many devices
• Self-healing features to automatically maintain automated visual tests
• Seamless integration with your CI/CD pipeline, such as Jenkins, GitLab, and Bamboo

Website: Katalon

Try Out Katalon Visual Testing

2. Kobiton

Kobiton's Visual Testing solution is an all-in-one solution for mobile testing, with a user-friendly interface. Also, there is no need for any setup or integration. All you have to do is run one baseline manual session on a real device. Kobiton's AI engine will take care of the rest.  

Kobiton's automated visual testing solution can capture metadata from each run, analyze and compare each page across devices. After that, it pinpoints any visual discrepancies concerning page layout, structure, and color. Also, Kobiton provides recommendations on how to improve the application's beauty and user experience. 

Highlighted Features:

• Kobiton can capture screenshots of each screen and action performed during Functional Testing. These screenshots serve as baseline images for automated comparison. Notably, Kobiton does not impose extra charges on the number of visual comparisons conducted
• AI-driven remediation & recommendations for immediate troubleshooting
• Easily add parameters and datasets to your scriptless test, which can be automatically executed with AI
• Compare your UI and UX design to the leading apps in the same market
• Scriptless performance testing

Website: Kobiton 

3. Applitools

Applitools is among the most popular Visual Testing tools on the market. It entered the market relatively early compared to other visual testing vendors. Applitools changed the visual testing landscape by introducing scanning technology to humanize testing scripts and shorten the product release cycle.

Highlighted features:

• Applitools Eyes: AI-powered computer vision algorithms that emulate the human eye to effectively find both visual and functional regressions
• Can recognize dynamic content like Ads or personalized dashboard and ignore them
• Integrate with Cypress, Selenium or other test frameworks then run right in your favorite CI/CD tool: Jenkins, GitLab, GitHub, CircleCI, and more
• Integrations with Jira and other bug reporting tools for better results and reporting

Website: Applitools

4. 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 smart comparisons, group those visual changes together, then select only the most noticeable visual regressions. They also have a comment and notification feature to help your team stay updated on the project progress.

Highlighted Features:

• Automatic status updates in pull requests whenever visual changes are detected
• Snapshot stabilization technology automatically freezes animation to minimize false positives
• Ignore specific areas on the page
• Seamlessly integrate into existing CI/CD workflow
• Support popular test automation frameworks and languages

Website: BrowserStack

5. AyeSpy

AyeSpy is a lesser-known but actually quite useful to automate your visual testing efforts. It is among the best free visual testing open source tools.

Highlighted Features:

• Run on Selenium Grid 
• Inspired by Wraith and Backstop -- both popular visual regression testing tools
• According to its creators, the USP of this tool is its performance improvement over other visual testing tools (runs 40 screenshot comparisons in a minute)
• Straight-forward setup with simple documentation for your team to get started more quickly and easily
• Screenshots can be taken for multiple branches, which reduces testing time

Website: AyeSpy

6. LambdaTest

LambdaTest offers a Smart Visual Testing feature allowing teams to compare two image layouts and detect discrepancies. LambdaTest's image-to-image comparison technology help testers easily find even the smallest visual bugs by uploading screenshots of the baseline and comparison image. Its AI engine will take care of the rest.

Highlighted features:

• Smart on-cloud visual regression testing that can identify visual bugs related to Icon Size, Padding, Color, Layout, Text as well as Element’s positions
• You can choose from across 3000+ real browsers and operating systems, including Chrome, Firefox, Safari, Internet Explorer, Edge, and more. 
• Parallel testing supported to cut down test execution time by 10x
• Diverse integration ecosystems supporting 120+ integrations 

Website: LambdaTest

7. SikuliX

SikuliX is one of the top open source visual regression testing tools utilizing Image Recognition and Control GUI technology. Testers can identify a certain button on the screen, then controlling the mouse and keyboard to interact with the identified button. This makes SikuliX handy when you don’t have access to the source code of the application or web page.

Highlighted Features:

• Can be used to automate Flash Objects/Flash Websites
• Can perform visual testing for web pages, desktop applications on Windows, Linux, Mac, iPhone, and Android
• Can automate certain tasks on the GUI even when you don’t know the ID of the elements
• Can easily be integrated into other third-party applications

Website: Sikulix

Price: Open-source

Conclusion

Visual regression testing is a valuable practice for ensuring a high-quality GUI for your users. Manual testing and automated UI testing with open source tools can be long and inefficient. Therefore, investing in a low-code solution for the long term is necessary. 

There are a number of market-leading tools available for visual regression testing that employ AI/ML to maximize their effectiveness. These solutions are able to detect changes in the GUI and pinpoint errors quickly and accurately. With these quality solutions, organizations can be confident that their product is being deployed in the most efficient manner.

Frequently Asked Questions

How does Katalon use AI to reduce false positives in visual regression testing?

Katalon reduces false positives by leveraging computer vision and deep learning algorithms to detect pixel-level changes in the UI. This allows the tool to identify visual changes that may otherwise be missed by traditional test automation processes. 

To better reduce false positives, Katalon leverages AI to match various zones between the checkpoint and baseline image. It then highlight visible changes in the layout. Katalon also uses ML to extract and compare texts from the two images regardless of font family, font size or color. This helps the user to quickly identify texts modified from the original version.

Can UI testing be automated?

Definitely, UI testing can be automated using a variety of tools, such as Katalon, Selenium, Appium, and many others.

What is the difference between UI and GUI testing?

UI (user interface) testing is the process of testing both the functionality and the look of an application. On the other hand, GUI testing only focuses on the visual elements, such as buttons, text boxes, or images. In other words, UI testing is a broader term than GUI testing.

Why UI testing is important?

UI testing is important because it ensures that the user experience of an application is consistent, reliable, and intuitive. It also helps to identify potential usability issues, and can be used to ensure that the application meets the user's expectations.

Read More: What is UI Testing?

Is UI testing functional or non-functional testing?

UI Testing is a type of functional testing. It tests the user interface of a software application and ensures that it works as designed and meets the user's expectations.

Is there any free open-source visual validation tools?

Yes, there are several free open-source visual validation tools available, with the most notable examples including Selenium, Appium, and WebDriverIO. They are all free visual regression testing tools with huge room for customization. However, testers must have a high level of coding experience to create effective test scripts from scratch.

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