How to Automate Visual Regression Testing?

Automation is essential to simplifying this process since it provides the testing workflow with efficiency, accuracy, and scalability. Development teams can identify visual differences early in the development cycle by automating visual regression testing. This allows for quick feedback and improves the overall quality of the software. Let’s understand about this term in detail.

What does Visual Regression Testing Mean?

Visual regression testing is a software development technique for identifying unintentional visual modifications made to the user interface (UI) of a web application. To find any differences, screenshots of the user interface (UI) of the application are compared before and after code changes. Developers can guarantee that changes to the coding don’t bring about unexpected visual changes that could degrade the user experience by automating this process. Visual regression testing contributes to the overall quality and usability of the program by ensuring that it looks consistent across a range of browsers, devices, and screen resolutions.

Purpose of Visual Regression Testing:

1. Detecting Visual Defects: VRT aims to identify any visual discrepancies or defects introduced during the development process, such as layout shifts, color changes, font variations, or UI element misalignments.
2. Maintaining Visual Consistency: It helps maintain a consistent and polished user experience by ensuring that UI elements render correctly across various devices, browsers, and screen resolutions.
3. Preventing User Experience Issues: By catching visual bugs early, VRT reduces the risk of user-facing issues that could impact usability, accessibility, and overall customer satisfaction.

Why should you Automate it?

1. Enhanced Cooperation: By offering a common framework for evaluating and verifying UI modifications, automated visual regression testing fosters cooperation across developers, designers, and QA engineers.
2. Consistency: Visual regression tests are performed consistently across various browsers, devices, and environments thanks to automation, which produces more dependable and repeatable results.
3. Early Issue Detection: Teams can identify and resolve visual inconsistencies early in the development process, preventing them from developing into more serious issues, by including visual regression testing into the CI/CD pipeline.
4. Efficiency: Teams may test more frequently and thoroughly due to automation, which drastically cuts down on the time and effort needed to do visual regression testing as compared to human techniques.
5. Accuracy: Automated tools can take and compare screenshots with precision, reducing the possibility of human error in manual testing and guaranteeing accurate results.
6. Better User Experience: Automation contributes to the upkeep of a polished and consistent user interface by proactively detecting and fixing visual flaws, which eventually improves user happiness and experience in general.

What about Manual Visual Checks?

Manual visual checks include human testers visually examining a web application’s user interface to find any errors, inconsistencies, or variations. Although automation has many benefits, manual visual checks have a role in the testing process and offer certain advantages of their own.

Some of the benefits are:

1. Subjective Evaluation: Since automated methods could have trouble capturing important details like aesthetics, user experience, and brand consistency, human testers can offer subjective insights into the application’s visual elements.
2. User Perspective: By emulating user interactions and evaluating the application from the viewpoint of end users, manual testers can evaluate the program by taking into account aspects like readability, accessibility, and intuitiveness that may have an impact on user engagement and satisfaction.
3. Complex Visual Elements: It can be difficult to precisely automate some visual aspects or interactions, such as animations, transitions, or complicated layouts. Manual visual inspections offer a more detailed evaluation of these components.
4. Edge Cases: Although automated tests might not fully cover uncommon scenarios and edge cases, human testers are skilled at spotting them. They can replicate real-world user interactions and assess the application’s reaction by using their imagination and domain knowledge.

What percentage of Visual Bugs are caught by Automated Visual Regression Tests?

Although a large percentage of visual flaws can be detected by automated visual regression tests, the precise percentage depends on test design, UI complexity, and the tools and techniques used. To obtain complete test coverage and guarantee a superior user experience, it is frequently required to combine automated testing with manual verification and exploratory testing.

1. Effectiveness of Test Cases: A large percentage of visual problems can be detected by thorough, well-designed test cases. Between 70% and 90% of visual problems may be found by automated tests, depending on how extensive the test cases are.
2. Accuracy of Comparison Algorithms: One important consideration in visual comparison is the accuracy of the algorithms employed. The accuracy of automated visual regression tests is increased by certain systems that use complex picture diffing techniques to precisely detect even minute visual changes.
3. Human Oversight and Verification: Despite automation, results verification and the detection of false positives or negatives depend on human oversight. Using human testers can help ensure a more thorough testing strategy by identifying visual issues that automated tests might miss.
4. Complexity of UI Elements: Automated tests are good at spotting simple visual alterations like layout modifications or color variations. More complex components, such as animations or dynamic content, may be difficult for them to handle, which could reduce the total percentage of visual problems found.

Popular Libraries for Automating Visual Regression Testing

1. Percy.io

A visual testing tool called Percy works well with current front-end development processes. It takes screenshots of websites and recognizes visual differences between versions automatically. Percy provides features including responsive design testing support, interfaces with common CI/CD technologies, and visual review and approval workflows.

Who Uses: Development teams who work on websites and online applications and wish to automate visual regression testing as part of their CI/CD processes use Percy.io.

Pros:

1. Smooth interaction with widely used CI/CD tools, such as GitHub Actions, Jenkins, and CircleCI.
2. Offers graphic dashboards that make it simple to compare screenshots and identify changes in appearance.
3. The capacity to take screenshots with different viewport widths and browsers.

Cons:

1. Restricted free tier, premium programs offer more extensive functionality.
2. Needs internet access to take and process screenshots.
3. May not be able to handle dynamic content or complex visual elements without some constraints.

2. BackstopJS

This open-source tool for visual regression testing can be used headless with Puppeteer or within a browser. It uses an easy configuration file to build test scenarios for developers, and it takes screenshots of websites automatically. Features like custom thresholds for change detection, visual diffing, and connection with CI/CD pipelines are all offered by BackstopJS.

Who Uses: Developers and QA engineers who want a command-line interface for setting up and executing visual regression tests are the ones who use BackstopJS.

Pros:

1. A JSON-based configuration file is used for easy setup and configuration.
2. Integrating into CI/CD pipelines is made simple by the command-line interface.
3. Allows for testing on various devices and viewports.

Cons:

1. Restricted analytical and reporting capabilities in contrast to certain other tools.
2. Additional manual labor is needed to set up and manage test scenarios.
3. Perhaps not as appropriate for groups who need sophisticated visual diffing algorithms or a lot of collaboration tools.

3. Applitools Eyes

AI-powered visual validation and regression testing capabilities are offered by Applitools Eyes, a potent visual testing tool. Numerous programming languages and frameworks are supported, such as Cypress, Selenium WebDriver, and others. Advanced functionality like cross-browser testing, layout testing, and connection with CI/CD processes are available with Applitools Eyes.

Who Uses: QA engineers and developers who work on online and mobile applications who need automated visual testing capabilities are avid supporters of Applitools Eyes.

Pros:

1. Powerful AI-powered visual testing techniques for precise image comparison.
2. Supports a large number of programming languages and platforms, including desktop, mobile, and web apps.
3. Intelligent maintenance tools to lower false positives and automatically manage baseline photos.

Cons:

1. For solo developers or small teams, prices could be somewhat high.
2. The complex feature setup and configuration learning curve.
3. restricted offline testing capacity in contrast to several other tools.

Conclusion

In conclusion, an essential technique in modern software development is automating visual regression testing, which enables teams to effectively maintain the visual coherence and caliber of their online applications. Developers can quickly detect visual regressions, accelerate testing procedures, and produce a refined user experience by utilizing automated tools and frameworks. Accepting it enables development teams to produce high-caliber software that fulfills user expectations while also accelerating release cycles and improving teamwork.

Frequently Asked Questions on How to Automate Visual Regression Testing?

Which procedures work best for automating Visual Regression Testing?

Ans: The best methods for accomplishing Visual Regression Clear test scenarios and baseline images should be defined, version control should be applied to baseline images, versioning and branching techniques should be used, tests should be run across a range of browsers and viewport sizes, and test cases should be reviewed and updated on a regular basis.

What distinguishes traditional functional testing from visual regression testing?

Ans: Traditional functional testing concentrates on confirming that an application functions as intended, whereas visual regression testing looks specifically for differences in appearance between several UI versions. By guaranteeing that the user interface (UI) is consistent between releases, it enhances functional testing.

What typical challenges do you have while putting Visual Regression Testing into practice?

Ans: Managing dynamic material, responding to responsive design, resolving browser discrepancies, establishing and maintaining baseline pictures, and incorporating VRT into the CI/CD pipeline are some typical implementation problems for visual regression testing.