How Visual Diff Algorithm improves Visual Testing

Visual aesthetics play a pivotal role in customer engagement. A website that is visually appealing and consistent is more likely to delight customers. This is why it is essential to perform Visual Regression Testing during every release to ensure that the newly made functional updates do not disturb the visuals of the website.

It is even more important to businesses that are largely dependent on visual aesthetics to ensure that user experience remains consistent throughout.

Visual Regression Testing, also known as Visual Validation, Visual Comparison, or simply Visual Testing, compares the screenshot of the UI with the base screenshot and highlights the differences.

The expected screenshot is called the baseline image, and the recent screenshot, which is used to compare with the baseline image, is called the actual image. The baseline screenshot will be compared with the actual screenshot to produce the output. Test Results will be marked as Pass or Fail based on the differences between the images.

What is Visual Diff Algorithm?

The logic behind Visual Regression Testing, which enables the system to draw pixel-by-pixel comparisons between the baseline and actual image, is known as the Visual Diff Algorithm. This Visual Diff algorithm can be written in different programming languages such as Java, C#, JavaScript, etc. 

How does Visual Diff Algorithm work?

Just as how Functional Testing compares the actual result of the test case with the expected result and marks the test as Pass or Fail based on the difference, Visual Diff compares the visuals in a similar way using Test Automation.

Steps to perform Visual Comparison

1. First Run captures the baseline screenshot of the webpage and stores it as the reference image.
2. The second run (subsequent) captures the screenshot (actual image) and compares it with the baseline image.
3. The output will be produced based on the visual comparison algorithm in a diff image format.
4. Before producing the output image, the tool considers whether there is any sensitivity factor or any other values that the user has specified.

Why do you need Automated Visual Testing for Software?

Since Functional testing doesn’t guarantee that the UI elements rendered on the browser are correct and as expected. For example, the developer might have written the code where one button might partially overlap with the other, the functional test would still pass, but they are visually incorrect. 

To catch all user interface-related bugs, you need Visual Testing.

Some of the common Visual Defects as below

1. Issues with Font
2. Issues with layout (such as padding, spacing margin, etc.)
3. Issues while rendering (Based on the browser, the rendering may be different)
4. Issues with Elements overlap
5. Issues with Responsive screen

Why is Automation more efficient than Manual Visual Testing?

Manual visual testing typically involves a set of test cases and a design document or pre-captured screen, where the QA compares the webpage with a pre-captured screenshot by running a specific page on the website. The major problem with manual testing is since it is done by a human, giving attention to each and every pixel is impossible. The tester compares the screen based on their expertise and knowledge. 

The output of the manual visual testing depends on the tester’s attention to detail capability. This makes manual Visual Testing complicated and provides less accuracy. Moreover, it will take a lot of time to test manually, causing a delay in the release.

Automated visual testing is always better in comparison with manual, as the screenshot capture and comparison are done by an automated tool. The automated visual testing tool compares the captured screenshot pixel-by-pixel so the output will be highly accurate and reliable. The produced output contains the difference in highlighted color, so it is easy to analyze and understand.

How to perform Visual Testing with Visual Diff Algorithm using Percy?

Percy is an Automated Visual Testing platform that uses the Visual Diff Algorithm to perform Visual Regression Testing. It can easily be integrated with most of the popular frameworks, such as Cypress, Selenium, TestCafe, Storybook, Playwright, Puppeteer, WebDriverIO, and NightwatchJS.

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Based on the automation framework of your choice, you can download the package or module and make the pre-requisite configurations to run the visual test on Percy.

Using Cypress framework to demonstrate how Percy performs Visual Testing using Visual Diff Algorithm.

Step 1: Install Percy using the following command

npm install --save-dev @percy/cli @percy/cypress

Step 2: To import Percy to Cypress, navigate to cypress/support/index.js File and enter the following command:

import '@percy/cypress'

Step 3: Write your first Percy Visual Test Script as shown below. The following code uses Visual Diff Algorithm to compare the baseline image with the actual screenshot and deliver test results upon execution.

//visual-test.js
describe('Cypress Visual Testing', () => {
it('Visual Test', () => {
cy.visit("https://browserstack.com/");
cy.percySnapshot('Home-Page');
})
})

Step 4: Run Percy Test using the below command:

npx percy exec -- cypress run

Step 5: Review the Test Result

The results will be displayed with a detailed dashboard, where Percy provides a detailed Visual Comparison using the Visual Diff Algorithm and clearly highlights the difference if there are any.

Conclusion

Visual Diff Algorithm makes life easier by automating the visual regression tests to ensure that the website UI appears flawless and consistent to the user after every release. Percy is a Visual Testing Platform that uses a Visual Diff Algorithm to make pixel-by-pixel comparisons and highlight any visual changes in the website within a few minutes. Moreover, Percy is now able to carry out visual regression tests on mobile browsers as well, Safari for iOS and Google Chrome for Android.

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