As applications become more complex and UI consistency becomes critical, ensuring that the user interface appears as expected across multiple environments is key. Applitools Eyes, when integrated with the Playwright SDK, provides a powerful, efficient, and streamlined approach to visual testing in your Playwright tests. The combination of Playwright, a popular end-to-end testing framework, and Applitools Eyes, a visual AI-powered testing tool, makes visual validation easier, faster, and more scalable.

Applitools Eyes is a visual AI-powered testing tool that helps address these UI consistency challenges. It uses advanced AI-driven image comparison to detect visual differences. Unlike traditional visual testing tools that perform pixel-by-pixel image comparisons, Applitools Eyes uses AI algorithms to determine if the visual differences are actual bugs.

Applitools Playwright SDK introduces several improvements designed to streamline the process of setting up and running visual tests, making the experience more efficient and user-friendly.

In this blog, we will discuss when it is appropriate to use visual testing with Playwright and which cases will be suitable for using Applitools.

Overview of Visual Testing

Visual testing is a technique performed to ensure the visual appearance of a given website or application matches the provided design and layout . This includes the comparison of the actual UI against a standard image or a reference UI image. This type of testing primarily focuses on detecting any visual anomalies, which include alignment issues , font problems, color discrepancies , images, or structural shifts that can disrupt the user experience.

How Visual Testing Differs from Functional Testing

Visual testing and functional testing are both crucial if the goal is to deliver a high-quality application; visual testing checks the visual appeal of the application, while functional testing verifies how the application functions.

Let’s see some major differences between visual and functional testing.

Before delving into how we can perform visual testing using Playwright and Applitools, let’s review some of the new improvements that Applitools has introduced .

What’s New In Applitools Playwright SDK?

The Applitools Playwright SDK is a library that integrates Applitools’ visual testing capabilities with the Playwright automation framework.

Let’s explore the improvements done by Applitools to streamline the process of setting up and running visual tests, making the experience more efficient and user-friendly. 

Here’s a detailed breakdown of what’s new in the updated SDK:

Test Fixtures:

• Test fixtures Centralize and reuse setup code across multiple tests, making the setup for visual tests more consistent and reducing redundant configuration.
• This feature is particularly valuable when running tests on multiple pages or scenarios, as it simplifies the initialization of Applitools Eyes in each test.

CLI Onboarding:

• The Command-Line Interface (CLI) simplifies the initial setup process by automating configuration steps, helping users quickly integrate Applitools Eyes with Playwright. 
• This is especially helpful for new users, reducing the complexity of the setup and enabling faster onboarding into visual test creation.

Config Object Setup:

• The configuration object setup automates the insertion of Applitools Eyes settings into the Playwright configuration file (e.g., playwright.config.js or playwright.config.ts). 
• This feature eliminates manual setup, reducing the risk of errors, ensuring accurate configuration from the outset, and saving developers valuable time.

Custom HTML Reporter:

• The custom HTML reporter enhances Playwright’s default test report by integrating visual test results from Applitools Eyes. 
• This allows developers to view a direct comparison between the baseline image and the current test screenshot, helping identify visual regressions more effectively. 
• By adding visual results to the standard Playwright report, it simplifies the review process, offering a comprehensive overview of the test outcomes.

Before we deep dive into how Applitools helps in visual testing, let’s first see how we can perform visual testing using Playwright.

Visual Testing Using Playwright

Playwright comes equipped with tools to make visual testing effortless, allowing developers to take and compare screenshots of web pages or specific web page elements. 

Here’s how visual testing works in Playwright:

1. First Run: Playwright captures and saves a screenshot of the page or specific UI elements. This is known as the base image.
2. Subsequent Runs: In the next run, Playwright takes a new screenshot and compares it against the base image.
   • If there are no differences, the test passes.
   • If differences exist, the test fails, flagging the areas where changes occurred.

Prerequisites

Ensure the following tools are installed:

Node.js: Download and install from Node.js.

Visual Studio Code (Optional): Recommended IDE for coding.

Install Playwright:

npm i @playwright/test

Write the Simple Visual Regression Test Using Playwright
Create a new JavaScript file in your test folder, e.g., demo.spec.js.

Use the page.screenshot() method to capture the screenshot and the expect.toMatchSnapshot() assertion from the @playwright/test module to compare images.

const { test, expect } = require('@playwright/test'); 
test('Visual Regression Test Example', async ({ page }) => { 
   // Navigate to the website 
   await page.goto('https://playwright.dev'); 
   // Capture a screenshot of the page 
   const screenshot = await page.screenshot(); 
   expect(screenshot).toMatchSnapshot(); 
}); 

When we execute the above code for the first time, the test case fails with the below error, and Playwright captures and saves a screenshot of the page or specific UI elements. This is known as the base image.

When we execute the same test case again, it will pass.

Visual Regression Test with maxDiffPixels option 

There might be the case when there are some minor differences in the images and the test case starts failing; to handle this situation we have an option, the ‘maxDiffPixels option,’ that we can pass. It allows you to specify the maximum number of pixels that can differ between two images for the comparison to still be considered successful.

const { test, expect } = require('@playwright/test');
test('Visual Regression Test Example', async ({ page }) => {
  // Navigate to the website
  await page.goto('https://playwright.dev');
  // Capture a screenshot of the page
  const screenshot = await page.screenshot();
  expect(screenshot).toMatchSnapshot({ maxDiffPixels: 100 });
}); 

const { test, expect } = require('@playwright/test');
test('Visual Regression Test Example', async ({ page }) => {
  // Navigate to the website
  await page.goto('https://playwright.dev');
  // Capture a screenshot of the page
  const screenshot = await page.screenshot();
  expect(screenshot).toMatchSnapshot({ threshold:0.5} );
}); 

Visual Regression Test with Threshold option

Passing ‘threshold’ as an option is another option to avoid failing the test case. This is particularly useful for handling slight differences that occur due to rendering variations.

const { test, expect } = require('@playwright/test');
test('Visual Regression Test Example', async ({ page }) => {
  // Navigate to the website
  await page.goto('https://playwright.dev');
  // Capture a screenshot of the page
  const screenshot = await page.screenshot();
  expect(screenshot).toMatchSnapshot({ threshold:0.5} );
}); 

So far we have seen how we can automate the visual UI using Playwright. In the next section you will see how we can use Applitools Eyes and Playwright SDK together to automate visual testing.

Visual Testing using Applitools Eyes and Playwright SDK

Visual testing is a crucial aspect of modern software quality assurance. It ensures that a web application’s UI renders correctly across different devices, screen sizes, and browsers. Tools like Applitools Eyes and frameworks like Playwright SDK simplify this process by providing robust solutions for automated visual regression testing.

Below are the steps to set up Applitools Eyes and Playwright SDK.

Install Playwright

npm init playwright@latest

Install Applitools Eyes SDK 

npm install -D @applitools/eyes-playwright

Add the below line in .spec.js file 

To configure your project for Applitools Eyes, we have to add the below line.

import { test } from '@applitools/eyes-playwright/fixture';

In the next section you will see examples to explain how we can use SDK with Playwright tests. 

Before moving in the detail of various types of matchLeavel, let see one basic example to understand how we do the visual testing in Applitool,  and the method used in Applitools, to capture and validate a checkpoint in your application’s UI.

Below is code that integrates Applitools Eyes with Playwright to perform a visual test.

import { test } from '@applitools/eyes-playwright/fixture';
test('My first visual test Using Applitools with matchLevel: Dynamic', async ({ page, eyes }) => {
await page.goto('https://app14743.cloudwayssites.com/helloworld/');
  // Visual check
  await eyes.check('Landing Page', {
    fully: true,
    matchLevel: 'Dynamic',
  });
});

In the above code we mainly use two things: one is the method eyes. check() and two options: {fully: true}, and {matchLevel: ‘Dynamic’}

eyes.check(): Performs a visual snapshot of the page or a specific element and compares it with the baseline image stored in Applitools.

Options:

• fully: true:
  • Captures the entire page, including scrollable sections.
  • Ensures that all content on the page is included in the visual test.
• matchLevel: ‘Dynamic’:
  • A matching algorithm that focuses on the content while ignoring dynamic changes, such as text or layout differences.
  • Useful for pages with frequently changing content, like user-generated text or dynamic data.

Below are the options that we can pass in our test case. These options provide flexibility and precision, enabling robust visual testing tailored to different scenarios and challenges.

This table summarizes each configuration, making it easier to understand their purposes.

Examples with different matchLevel

MatchLevel determines how the captured visual output is compared with the baseline image.Let’s see the examples with different options.

1. Visual Testing with matchLevel: Strict

This ensures pixel-perfect comparison between the baseline and current screenshot, highlighting any visual difference, no matter how small.

test('My first visual test Using Applitools with matchLevel: Strict', async ({ page, eyes }) => {
  await page.goto('https://app14743.cloudwayssites.com/helloworld/');
  await eyes.check('Landing Page', {
    fully: true,
    matchLevel: 'Strict',
  });
});

• Purpose: Validates the entire page with Strict match level.
• Strict Match Level: Identifies even small differences, such as minor pixel or layout changes, ensuring high precision in visual validation.

2. Visual Testing with matchLevel: Dynamic

Focuses on content consistency by ignoring minor layout differences, such as text movement, while ensuring key visual elements remain unchanged.

In the below example you can see even if the text color is changed after clicking on link ‘?diff2’ test case still works perfectly fine because we have set matchLevel: Dynamic. This ensures the visual test focuses on the content and structure of the text rather than superficial changes like color.

test('My first visual test Using Applitools with matchLevel: Dynamic', async ({ page, eyes }) => {
 await page.goto('https://app14743.cloudwayssites.com/helloworld/');
 await page.getByRole('link', { name: '?diff2' }).click();
 await eyes.check('Homepage', {
   fully: true,
   matchLevel: 'Dynamic',
 });
});

• Purpose: Validates the entire page with Dynamic match level.
• Dynamic Match Level: Ignores minor content/layout differences (e.g., text changes, animations) and focuses on high-level structural comparisons.
• fully: true: Captures a screenshot of the full page, not just the visible viewport.

3. Visual Testing for a Specific Region/Component

Limits visual comparisons to a particular area or component of the application.

test('My first visual test Using Applitools with particular region/Component', async ({ page, eyes }) => {
  await page.goto('https://app14743.cloudwayssites.com/helloworld/');
  const component = page.locator('.fancy.title.primary');
  await eyes.check('My Component', {
    region: component,
  });
});

• Purpose: Tests only a specific component or region on the page.
• region: Focuses the validation on the area defined by the component locator (.fancy.title.primary), instead of the entire page.

4. Visual Testing with Ignored Regions

Excludes specific areas from comparison, preventing false positives caused by expected dynamic changes in those regions.

test('Visual test Using Applitools with ignoring the region', async ({ page, eyes }) => {
  await page.goto('https://app14743.cloudwayssites.com/helloworld/');
  const dynamicContent = page.locator('.fancy.title.primary');
  await eyes.check('Homepage', {
    fully: true,
    matchLevel: 'Strict',
    ignoreRegions: [dynamicContent],
  });
});

• Purpose: Tests the page while ignoring specific dynamic regions.
• ignoreRegions: Excludes certain areas from the visual validation (e.g., areas with dynamic content like dates, ads, or animations).
• fully: true: Captures the entire page for validation.

About dynamic match level

Dynamic match level is a feature in Applitools Eyes that verifies text by matching it against predefined or custom patterns, ensuring the content adheres to a specific format. It focuses on format validation rather than content changes, making it ideal for dynamic text like dates, emails, or numbers.

Type of dynamic match level

Dynamic match levels allow for flexible verification of text by matching it against predefined or custom patterns. The default types include:

• TextField: Text inside input fields.
• Number: Numeric values like ZIP codes or phone numbers.
• Date: Validates text as a date in proper format.
• Link: Hyperlinks or URLs.
• Email: Checks for a valid email address format.
• Currency: Recognizes monetary values.

These types ensure accurate validation by focusing on the format rather than the content changes, such as dynamic updates to dates or numbers.

Custom dynamic pattern

To create a custom dynamic pattern we have to follow below steps in Applitools dashboard 

Here are the steps to create a custom dynamic pattern:

1. Open the Settings Window: In the Page Navigator, select Apps & Tests.

In the list of applications on the left, hover over an application and click > Settings.

2. Add a Custom Type: Click Add custom type.

3. Define the Custom Pattern:

Enter a name and a Regex pattern.

4. Save the Custom Pattern:

In the below screenshot you can see we have set a custom pattern for Zip Code. Once the custom pattern is created, its name can be used in the code to reference the pattern.

Click Add will save the entered pattern. 

5. Apply the Settings:

Once all required patterns have been selected, click Apply settings.

Applitools Dashboard: Execute visual testing using the Applitools Playwright SDK

Applitools’ Dashboard is a powerful interface designed to manage and analyze test results efficiently, especially for visual testing and monitoring user interfaces.

Below are the steps that we normally have in the Applitools Dashboard when we execute any visual test case.

Precondition : Run the below command to export the key 

export APPLITOOLS_API_KEY='your_api_key_here'

Once the key is exported, the next step is to execute the test cases using the below command.

npx playwright test --ui tests/visual.spec.js

First Run: Playwright captures and saves a screenshot of the page or specific UI elements. This is known as the base image.

Subsequent Runs: In the next run, Playwright takes a new screenshot and compares it against the base image.

• If there are no differences, the test passes.
• If differences exist, the test fails, flagging the areas where changes occurred.

In the below screenshot in the Applitools Dashboard, you can see all the above four test cases are executed successfully.

Applitools Playwright SDK with Example in Detail

Let’s take an example of a particular component in the page. In the below screenshot, the component focuses on a specific component or region of the page. You can see only the ’Hello World’ part is tested. In case there is any change in this component, the test case will fail.

In the below example we have updated the component with the text ‘Happy World’ 

test('Visual test Using Applitools with Updating Component UI', async ({ page, eyes }) => {
await page.goto('https://app14743.cloudwayssites.com/helloworld/');
await page.getByRole('link', { name: '?diff2' }).click();
await eyes.check('Homepage', {
  fully: true,
  matchLevel: 'Strict',
 });
});

When we execute the above code, it will not execute successfully because the UI of the component is changed after clicking on the link ‘diff2.’

To fix the above problem, we have marked it resolved from the Applitools Dashboard. Once we accept the change, it becomes the base image.

Now when we execute the test case again, it gets executed successfully with the updated UI.

When Playwright’s Visual Testing Features Are Useful 

Playwright’s built-in visual testing features are well-suited for scenarios where:

Simple Visual Comparisons:

• Comparing entire pages or specific UI components with baseline images for detecting pixel-level differences.
• Example: Ensuring the homepage layout hasn’t shifted after a CSS update.

Static UIs:

• Testing applications with minimal dynamic or animated content, as these are less prone to false positives caused by animations or transient elements.

Fast Feedback:

• When quick pixel-by-pixel comparisons in CI pipelines are sufficient without advanced AI-powered analysis.
• Example: Smoke testing in a fast-moving development cycle.

Budget-Friendly:

• Playwright’s native screenshot and comparison capabilities don’t require additional tools or subscriptions.

When Playwright’s Visual Testing May Fall Short

Dynamic Content:

• UIs with dynamic or frequently changing elements (e.g., time, randomized content, or animations) can cause false positives due to exact pixel mismatches.
• Example: A dashboard with live-updating graphs.

Complex Visual Changes:

• Playwright’s threshold-based comparison may miss subtle or semantic changes that don’t exceed the defined pixel difference threshold.
• Example: Slightly altered typography or colour changes.

Ignored Regions:

• While Playwright allows element-specific testing, ignoring specific dynamic regions within a larger page requires custom logic.
• Example: Excluding advertisements or live widgets from visual comparison.

How Applitools Handles Situations Better

Applitools offers superior visual testing capabilities compared to Playwright, especially when handling dynamic content, ensuring pixel-perfect validation, focusing on specific components, and reducing false positives. 

Dynamic Content Handling:

• Match Levels: Applitools’ AI-powered matchLevel options (e.g., Strict, Layout, Content) allow intelligent comparison by focusing on structure and ignoring irrelevant pixel differences.
• Example: Testing a real-time dashboard with dynamic data but a consistent layout.

Ignored Regions:

• Applitools allows you to define ignored regions to exclude specific parts of a page from comparison (e.g., ads or timestamps).
• Example: Excluding a “current time” widget from visual testing.

Advanced Visual Validation:

• Features like dynamic regions and AI-based semantic analysis help detect visual regressions that go beyond pixel-by-pixel differences.
• Example: Identifying a button misalignment that might not be detected by Playwright’s threshold settings.

Visual Testing Across Components:

• Allows you to target specific regions or components for testing without manually cropping or capturing screenshots.
• Example: Testing the styling of a navigation bar or modal dialog.

Conclusion

Playwright’s built-in visual testing features are suitable for simple cases where you need pixel precision in image comparisons of static UIs. However, it may struggle with complicated designs, whether they involve minor changes within the site or more intricate design requirements .

Applitools Eyes, which employs artificial intelligence, is more suitable for overcoming these difficulties. It performs extraordinarily in cases with dynamic content; it easily identifies subtle visual regressions and is equipped with extra functionalities such as ignored areas and cross-browser testing. For teams with significant testing and enhancement requirements, where the built-in visual testing capabilities of Playwright may fall short for complex and large-scale application testing, Applitools serves as an invaluable complement. It ensures and elevates the visual quality of dynamic applications, making it an ideal choice for robust testing and quality assurance.

About the Author

Kailash Pathak (Applitools Ambassador | Cypress Ambassador)

Senior QA Lead Manager with over 15 years of experience in QA engineering and automation. Kailash holds certifications including PMI-ACP®, ITIL®, PRINCE2 Practitioner®, ISTQB, and AWS (CFL).

As an active speaker and workshop conductor, Kailash shares his expertise through blogs on platforms like Medium, Dzone, Talent500, The Test Tribe, and his personal site https://qaautomationlabs.com/

The post Leveraging Applitools for Seamless Visual Testing in Playwright appeared first on AI-Powered End-to-End Testing | Applitools.

Artificial Intelligence (AI) is transforming industries everywhere, and software testing is no different. AI’s ability to analyze vast datasets, recognize patterns, and learn from historical data is reshaping the way testing is conducted. It’s making testing faster, more accurate, and highly automated. For testing leaders, the key is understanding how AI can add value and using it strategically to optimize your processes. In this post, we’ll explore how AI is changing software testing with real-world examples and practical steps for how testing leaders can integrate AI into their teams.

The Traditional Challenges of Software Testing

As testing leaders, we’re responsible for overseeing multiple facets of the testing process—managing resources, ensuring deadlines are met, maintaining quality, and more. Some common challenges include:

• Time-Consuming Manual Testing: Large-scale projects demand a lot of time for manual testing. While automation helps, it’s often deprioritized when fast manual testing is needed for urgent releases, which can lead to technical debt.
  
  Example: Perhaps you’ve faced situations where manual testing was prioritized over automation to meet a deadline. Later, you’re left with outdated test scripts and the challenge of playing catch-up.
• Human Error: Even experienced testers make mistakes, and missed defects in manual testing can lead to costly post-release issues.
• Growing Test Case Volume: As applications become more complex, the volume of test cases increases. This makes it difficult to cover all potential scenarios, which sometimes leaves less obvious but critical areas untested.

AI is emerging as a solution to these challenges by optimizing repetitive tasks, minimizing human error, and improving testing speed and accuracy.

How Testing Leaders Can Introduce AI

As a testing leader, it’s your job to ensure AI is adopted in a way that enhances your team’s efficiency without feeling like an additional burden. Here’s a practical approach to implementing AI in your testing strategy:

1. Identify Key Bottlenecks
   Start by assessing your current testing process. What tasks are taking up too much time? Where is your team encountering the most roadblocks? AI is especially useful in areas like regression testing, test case maintenance, and data analysis.
   
   Example: Teams often struggle with maintaining test scripts as applications evolve. An AI tool like Applitools can handle these updates automatically, reducing the burden on testers.
2. Pilot AI Tools for Specific Tasks
   Introduce AI incrementally, starting with small, focused tasks like automating regression tests or generating test scripts for repetitive scenarios.
   
   Example: One testing leader integrated AI to handle visual regression testing, reducing the time spent on this task by 40% in just a few months. This allowed their team to focus more on exploratory testing.
3. Leverage Data-Driven Insights
   AI thrives on data, so take advantage of your team’s real-world data to improve testing. AI tools can simulate user interactions, predict where bugs are likely to occur, and even analyze past defects to help you focus on high-risk areas.
   
   Example: A team used AI to analyze historical defect data and prioritize testing in the most vulnerable areas. As a result, they reduced post-release bugs by 30%.
4. Show ROI and Impact
   For management buy-in, you’ll need to demonstrate the tangible benefits of AI. Track metrics such as time saved, increased test coverage, or reduced post-release bugs to prove the value AI brings to your testing process.
   
   Example: A team leader reported a 25% reduction in maintenance costs after introducing AI for test case maintenance, demonstrating significant ROI to the executive team.
5. Foster a Learning Culture
   AI adoption requires your team to learn new tools and adapt their workflows. Create a culture that encourages experimentation with AI, and offers opportunities for continuous learning, such as webinars or online courses on AI in testing.
   
   Example: A testing leader implemented “AI Fridays” where team members spent an hour each week exploring how AI tools could streamline their work. This fostered curiosity and built excitement around AI adoption.

Companies Leading the Way with AI Testing Practices

Here are some companies that have successfully integrated AI into their testing processes:

Key Areas Where AI is Transforming Software Testing

1. Automated Test Generation and Maintenance: AI-driven tools can automatically generate test cases based on the application’s behavior, reducing the time required to create and maintain test scripts.
   
   Example: Teams using Applitools Autonomous report a 50% reduction in the time spent maintaining test cases, thanks to the tool’s self-healing AI.
2. Predictive Defect Detection: AI can analyze past defect data and code changes to predict which areas of the application are most likely to fail, helping teams focus their testing efforts more effectively.
   
   Example: Microsoft uses AI to predict high-risk areas in code which lets testers focus on preventing defects before they happen.
3. AI-Powered Test Execution: AI can prioritize and run only the most relevant tests based on recent code changes, speeding up regression testing by avoiding unnecessary test execution.
4. Intelligent Bug Detection and Classification: AI tools can detect and classify bugs, automatically flagging high-priority issues while filtering out less critical ones. This saves time and allows testers to focus on more significant defects.
   
   Example: Facebook’s AI tool, SapFix, automatically detects bugs and generates code patches, reducing time spent on bug fixing.
5. Visual and UX Testing with AI: AI-powered visual testing tools can automatically detect inconsistencies across platforms and devices. Tools like Applitools can compare UI elements at a pixel level, reducing false positives and saving time.

Conclusion: The Future of Software Testing is AI-Driven

AI is not just improving software testing—it’s transforming it. For testing leaders, the opportunity to guide your team through this transition is immense. By starting with small, targeted AI applications, showing the tangible benefits to management, and fostering a learning culture, you can integrate AI in a way that enhances efficiency and quality.

Companies like Google, Netflix, and Salesforce have proven that AI-driven testing is the future. By adopting AI, you’ll reduce manual effort, increase test coverage, and deliver higher-quality software, faster. The future of software testing is knocking, and AI is the key to unlocking new levels of productivity and success.

About the Author:

Laveena Ramchandani

Laveena Ramchandani is an experienced Testing Manager with a comprehensive understanding of tools available for software testing and analysis. She aims to provide valuable insights that have high technical aptitude and hopes to inspire others in the world through her work. Laveena holds a degree in Business Computing from Queen Mary University of London and regularly speaks at events on data science models and other topics.

The post How AI is Changing Software Testing appeared first on AI-Powered End-to-End Testing | Applitools.

Nowadays companies are investing a lot of money into QA efforts to increase the quality of the software products being released. However, the traditional QA method is not only time-consuming and ineffective but also often disappointing in its results. This triggers inefficiency, additional expenses, and ultimately, higher risk for delivering the end product with visual or functional issues. The pressure to release frequently and stay ahead of the competition can lead to insufficient testing resulting in bugs and other issues that negatively affect the user experience.

Today’s users require software that has functional capabilities, better graphics and is easier to use. To meet these expectations, a lot of testing needs to be done for the application’s visuals and user interface. This is because as the software development life cycle progresses the testing teams are put under pressure as development teams release products faster.

In this blog, we will explore the challenges of testing modern applications and how these challenges can be addressed by utilizing the AI-powered testing tool, Applitools Autonomous.

You will see detailed examples of how Applitools Autnonmous addresses different types of testing like functional, visual, and API testing.

Challenges In Testing Modern Applications

Below are some of the challenges we often face while testing modern applications.

Too Many Scenarios

Modern applications are highly complex, with hundreds of end-to-end scenarios that need to be tested across a vast array of screens, devices, and browsers. 

Too Many Screens & Devices

In modern applications, users access digital content on a wide variety of devices, browsers, and screen sizes, each with its own unique characteristics. Manually verifying that an application looks and functions correctly across all these environments is nearly impossible without automated assistance. Traditional testing methods cannot scale to meet this demand, often resulting in inconsistent user experiences and missed visual bugs.

Constant UI Changes

In dynamic development environments, user interfaces (UIs) are constantly evolving. Even minor changes to the UI can require updates to test scripts. This constant maintenance burden can slow down the development process and lead to outdated or ineffective tests.

Different Skill Sets

Teams often consist of members with varying technical skills, leading to the use of different tools and approaches to testing. This creates silos within the organization, where engineers and non-technical testers might not collaborate effectively. So far we have seen the challenges in testing modern applications.

Types of Testing Using Applitools Autonomous

Applitools Autonomous, powered by Applitools’ proven Visual AI, offers a game-changing solution that allows teams to automate and streamline testing across various dimensions. In this blog, we’ll explore the types of testing you can perform using Applitools Autonomous and how it simplifies the testing process.

Full Website Testing

One of the key features of Applitools Autonomous is its ability to conduct a Full Website Test with minimal effort. Simply by entering your website’s URL, Autonomous crawls the sitemap and automatically creates a test suite covering every web application page.

Benefits of Full Website Testing:

• Comprehensive Test Coverage: Automatically creates tests that span the entire site.
• Visual AI Validation: Screenshots are taken and compared in real time to identify visual discrepancies.
• Technical Issues Detection: Automatically detects issues like HTTP errors, timeouts, and structural changes (added/removed pages).
• Cross-Environment Consistency: Ensures your website renders consistently across all environments.

With just a URL input, Applitools Autonomous handles the heavy lifting of testing, giving teams complete coverage across all environments.

URL List Testing

If you don’t need to test your entire website, or if you want to focus on specific pages, Applitools offers URL List Testing. This allows you to upload a list of important URLs that you want to validate across different browsers and devices.

Benefits of URL List Testing:

• Custom Test Plans: Create targeted test plans for critical or specific parts of your website.
• Visual and Functional Validation: Detect visual differences, server errors, and loading failures.
• Quick Setup: Simply upload a CSV, XLS, or sitemap file to initiate the testing process.

This method gives you granular control over which parts of your web application are tested, ensuring the most important areas receive detailed attention.

Custom Flow Testing

For complex workflows, Applitools Autonomous offers Custom Flow Testing, which allows you to simulate end-user actions across your site. For example, you can test user journeys like logging in, adding items to a cart, and checking out — with every action captured step by step.

Benefits of Custom Flow Testing:

• Workflow Validation: Ensure that user flows, from login to checkout, function correctly.
• Real-Time Interaction: Record steps in an interactive browser, which are automatically converted into plain English for easy review.
• Dynamic Content Testing: Easily handle personalized content and dynamic data using Visual AI, ensuring accuracy even with fluctuating data.

Custom Flow Testing is ideal for complex, multi-step processes, such as eCommerce workflows or user registration flows.

Cross-Browser and Device Testing

Cross-browser testing can be a significant bottleneck in the development process, but Applitools Autonomous eliminates this pain point. It replicates browsers in seconds, cutting down the time required for Cross-Browser and Device Testing by up to 90%.

Benefits of Cross-Browser Testing:

• Fast Replication: Save time by reducing cross-browser testing time by up to 90%.
• Consistent Testing: Validate how your site performs across multiple browsers and devices with minimal effort.

By reducing the time spent on browser replication, teams can focus on identifying and resolving any browser-specific issues faster.

API Testing

Applitools Autonomous doesn’t just stop at visual testing—it also enables API Testing. You can initiate HTTP requests directly in your tests, manage application states, and store responses for use in later test steps.

Benefits of API Testing:

• Seamless Integration: Initiate API calls and validate responses as part of your testing workflow.
• State Management: Manage application states before or after the UI flow without complex logic.

API Testing combined with visual validation ensures that your web app’s functionality works correctly and efficiently across the board.

Example of Testing Using Applitools Autonomous

In the below section, you will see the different types of testing you can perform using Applitools Autonomous.

Full Website Testing

In full website testing, users provide the URL they want to scan and specify the test environments where they want to execute the scan. Additionally, users can set optional settings such as a maximum number of URLs and select a custom flow to run before the test. Once these steps are completed, the website is ready to be scanned.

For example, let’s look at the site https://dan.sandbox.applitools.com/e-commerce.

Steps to Create a Full Website Test

1. Navigate to Test Management
   • In the navigation bar, go to Test management > Tests.
   • Click Create a new test and then select Create a full website test.

2. Enter the URL: In the URL field, input the website homepage in the format https://www.example.com/.
   
   Alternatively, you can enter the full path to the sitemap or a sub-directory, such as https://dan.sandbox.applitools.com/e-commerce/type/books.
   
   If a sub-directory is specified, Autonomous will use the sitemap in the root directory to identify URLs within the sub-directory. If the sub-directory has its own sitemap, provide the full path to that sitemap.

3. Default Test Environments: The test will use the below environments by default, each defining a browser, operating system, and screen size. You can click on an environment to remove it from the test. After creating the test, you can add or modify environments in the test plan.
   • Chromium, Linux, 1440 x 900
   • Chromium, Linux, 360 x 780
   • Microsoft Edge, Windows, 1080 x 1920
4. Optional Settings:
   • Set the Limit: To limit the number of URLs in the initial test run, click on Optional settings and select Set a max number of URLs to include in the test, then enter the desired number of URLs.
     
     This helps the first test run quickly and get preliminary results. This setting only applies to the first run; future runs will include all URLs in the sitemap, with new URLs marked as “New” in the results.
     
     Note: If you have a trial account, note that there is a limit to the number of tests you can include in a full website test.
   • Custom Flow and Authentication: To enter basic authentication or run a custom flow before each URL opens, click on Optional settings and choose Select a custom flow to run before this test.
     
     You can select Basic authentication and enter a username and password. This adds an authentication-encoded string in each URL, ensuring the username and password are included.
5. Click the Next Button: Once the above steps are completed, your website is ready to be scanned.
   
   Once you click the Next button, Autonomous can then develop baseline data at every screen on the website. These are the initial test images which are in most cases used to identify changes in subsequent test iterations. The maximum count of baselines to be generated is obtained by multiplying the count of URLs in the test by the count of environments.
   
   You can see baseline data is created for every screen in the screenshot below.

6. Execute the Test: Once the baselines have been created, click Run Test. Autonomous will run the test to create a checkpoint for each screen and then compare the checkpoint to the baseline determining any issues and if the screen has changed.
7. Execution report: Once the execution is complete, click Review Results to view all test results on the Results page.
   
   Clicking on the Results tab on the left side lets you see the details of the Pass and Fail test cases. In the screenshot, we can see one test case failed. When we tried to find out the reason it was discovered that this test case was failing because of the 404 error screenshot attached below.
   
   This lets us automatically find technical issues, pages that were added or removed from the website, visual disparities, and unexpected alterations on any of the pages.

URL List Test

A URL list test allows users to create a list of URLs with combinations that will be used for testing. This is especially useful when you have no sitemap, want to crawl specific URLs in your domain, or need to crawl URLs of other domains too.

While setting up your URL list test you should create a file with the URL to be tested and check if all of them are properly loaded. The list should be in CSV, XLS, TXT, or a sitemap .xml file format. The sitemap .xml should only contain the URLs you are going to test—not all URLs on your site.

Steps to Create a URL List Test in Applitools Autonomous

1. Navigate to Test Management: In the navigation bar go to Test Management > Tests.
2. Create a New Test: Click on Create a new test and select the URL list from the dropdown.

3. Enter Test Details:
   • Test Name: Enter a name for the test. This will appear in the list of tests.
   • Description: (Optional) Add a description of the test.
   • Application: Select the application the test should be associated with. Every test must be linked to an application. If you have an existing full website test or another test linked to the same application, associate this test accordingly. For more details, refer to the “Applications” section in the platform documentation.
   • Plan: Choose the associated plans. Plans define the schedule, environment, and test parameters. A test can belong to multiple plans, and the list of available plans will depend on the application associated with the test. For more details, refer to the “Plans” section.

4. Run a Flow Before Each Step (Optional): If you need to perform an action (such as entering authentication credentials or closing a popup) before each step, click Select a flow to run before the screen URLs. For more details, see the “Flow to Run Before Steps” section of the documentation.
5. Import URLs: Click Import URL list to upload a comma-separated text file, CSV, or XML file with the list of URLs you want to test.
   
   Alternatively, enter a single URL and click Add URL to manually add URLs one by one.
6. Set Match Level: The default match level for all URLs is set to Strict. If you want to change the match level for a particular URL, click the area to the right of the URL and select the desired match level from the dropdown.
7. Advanced Settings: To configure additional advanced settings for the test or individual URLs, refer to the Advanced Test Settings section for further customization options.
8. Finalize and Run: Once the configuration is complete, choose one of the following actions:
   • Create (or Update): Saves the test to the associated plans without running it.
   • Create & run > Create & run test: Saves and runs the test as a single instance without executing any other tests in the plan. You will be asked to choose a plan to determine the test environments. You can view the results on the Results page, and the test will be listed as “Run without a plan.”
   • Create & run > Create test & run plan: Saves the test and executes all associated plans, including all tests within those plans. Results can be viewed on the Results or Plans pages.

Custom Flow Testing

The Autonomous Applitools Custom Flow Test is an intelligent and streamlined way to automate end-to-end testing of specific workflows on a website. This feature enables testers to design a sequence of actions or user scenarios, for instance, login, adding items to a shopping cart, and navigating to a checkout page while at the same time, every action is recorded for evaluation purposes.

Key Components of Autonomous Custom Flow Test

• Interactive Browser: Autonomous provides an interactive Chrome-based browser that allows users to manually interact with the application. Testers can perform actions like clicking buttons, filling in forms, scrolling, or navigating between pages.
  
  The interactive browser records every action in real time and automatically translates them into test steps, simplifying the test creation process.

• User Action Steps: Go to Test Management > Tests in the navigation bar. Click on Create a new test and select Custom Flow from the dropdown.
  
  
  The below screen will then open when you click on Custom flow:
  
  
  In the screenshot below, you can see the recorded steps resulting from using the interactive browser:
  
  
  Actions performed in the browser, such as clicking or typing, are captured as plain English commands. These steps can be easily added, modified, or deleted.
  
  For instance, a step might read: “Enter “standard_user” as username”, Enter “secret_sauce” as password, and  “Click on the Login button.” Autonomous also offers auto-suggestions to ensure that the commands are valid, reducing the risk of errors and speeding up the creation of test scripts.
• UI Validation Steps: Visual validation is a core feature of the Autonomous test. At key points in the workflow, Autonomous takes screenshots to validate the user interface. These visual checkpoints help ensure that there are no unexpected visual changes (known as visual diffs) between test runs.
  
  Screenshots act as baselines and provide insights into the accuracy of the UI across different devices and resolutions.
  
  In the below screenshot, you can see that after logging into the application we are visually verifying the page.
  

Use Cases of Custom Flow Testing

Let’s take the example of https://www.saucedemo.com/ where a user may perform the actions below. 

• Login into the application with Username and Password
• Click on Add to cart against the product “Sauce Labs Backpack”
• After adding the item to the cart place the order 
• Finally, verify the confirmation message

For the given use case, we have two options to write the test script:

• Manually add user actions: This involves explicitly defining each user action in the script or code.
• Record the steps: This option allows the user’s interactions to be captured automatically by recording the steps as they are performed.

Both approaches can be utilized based on the specific requirement or convenience. In the screenshot below you can see the above use case is recorded.

Debug or Modify a Test

In the screenshot below you can see we can perform various actions by clicking on any existing action. The user has clicked on an action (likely Step 7, clicking a button with a CSS selector) that reveals a dropdown menu providing options such as:

• Run next steps: Executes the remaining steps in the test from the selected point onward.
• Set as current step: Marks the selected step as the starting point for future test execution.
• Run until here: Runs the test from the beginning up to the selected step, stopping just before it.
• View execution result: Displays the outcome of the selected step, including logs or screenshots, if applicable.
• Edit step: Allows modification of the selected step, such as changing input values or actions.
• Duplicate: Creates a copy of the selected step, useful for repeating actions with minor adjustments.

Previewing Test Steps in the Interactive Browser

This approach saves time during the test construction process because it enables previewing of the test steps as one proceeds with the development of the test script in an interactive browser.

When in an interactive browser running a test there is an option where you get to see the screen as it was before each step was performed and after.

How to Preview a Test Step

Place the mouse pointer over an icon before one or several particular test steps, and you will be provided with a thumbnail of the screen. For a more detailed view of the screen, navigate to the icon on the toolbar to open the full-size picture preview.

On the top of the preview window, you can find information such as the step number, command run, and its status—pass or fail.

Use the icons behind the worksample Click on Action to see the screen before the step and Outcome to see the screen after the step. When viewing the action window the element clicked on during the step is highlighted in pink.

Running the Test from the Start

To start the test from the first step you can just press the “Run” button or “Rerun test from start” which is above the list of the steps.

Once started, Autonomous will go through each step one by one while taking a screenshot of the application at every step. If the browser is not already connected, then the Run will also create the connection before the test is carried out. This way it can be ensured all the steps are performed correctly and also shows the status of a particular step.

• icon indicates that the step was successful
• icon shows that Autonomous couldn’t process the step, and the test will stop at that point without continuing further

During the test, you can pause or stop it at any time by clicking the Pause or Stop buttons.

API Test

Applitools Autonomous is not limited to functional and visual testing. It can also be used for API automation. Supporting all CRUD operations, it allows you to execute standard HTTP actions like GET, POST, PUT, and DELETE in your tests. This adds versatility to its API testing capabilities.

Autonomous also enables you to validate test operations that cannot be confirmed via the UI, such as verifying form submissions through backend records. Additionally, it ensures backend APIs expose the correct endpoints, function as expected, and return proper responses, headers, and cookies.

GET Requests

For GET requests let’s take an example of https://gorest.co.in/

Navigate to Test Management: In the navigation bar, go to Test Management > Tests. Click on Create a new test and select the Custom Flow from the dropdown.

Use Case 1: API Response With Positive Validation

Objective: Hit the API endpoint and verify the following:

• response.status (HTTP status code)
• response.body[0].title (Title of the first object in the response body)
• response.body[0].id (ID of the first object in the response body)

In the screenshot below you can see all the above validations have passed.

You can then hover over a response value to view options to copy the following information to the clipboard:

• Copy Property Value: Copies the actual value from the response, e.g.,{“id“:157394,”user_id“:7436337,”title“:”Vulgus enim alius comis et officia.”,”body“:”Tametsi suscipit reiciendis. “}
• Copy Property Accessor: Copies the accessor to retrieve the value programmatically, e.g., {response.body.0}
• Copy Property Checkpoints: Copies a formatted checkpoint to use in a test, e.g., verify that {response.body.0.id} is 157394 and verify that {response.body.0.user_id} is 7436337

Use Case 2: API Response With Negative Validation

Objective: Hit the API endpoint and verify the following:

• response.status (HTTP status code)
• response.body[0].title (Title of the first object in the response body)
• response.body[0].id (ID of the first object in the response body)

In the screenshot below you can see title validation is failing when we are verifying the title of the first object.

POST Requests

For POST requests let’s take an example of the site https://reqres.in/api/users

Use Case 1: API Response With Creating User

Objective: Hit the API endpoint https://reqres.in/api/users

• Pass the body in the request 

{

    “name”: “morpheus”,

    “job”: “leader”

}

POST https://reqres.in/api/users with header “Content-Type: applitcation/json” and header “Accept: application/json” and body ‘{     “name”: “morpheus”,     “job”: “leader” }’

• Verify the status 201

In the screenshot below you can see test case is passed and a new record is created with the status “201”.

Use Case 2: API Response With Registering User – successful

Objective: Hit the API endpoint https://reqres.inhttps//reqres.in/api/register

• Pass the body in the request 

{

 “email”: “eve.holt@reqres.in”, 

“password”: “pistol” 

}

POST to https://reqres.in/api/register with header “Content-Type: application/json” and body ‘{     “email”: “eve.holt@reqres.in”,     “password”: “pistol” }’

• Verify the status 200
• Verify ‘token’ is generated

Summary

In the rapidly evolving software industry, companies are pouring resources into quality assurance to ensure smooth product launches. However, traditional QA methods are often too slow, costly, and ineffective, which can lead to bugs, poor user experiences, and product defects.

However, AI-powered tools like Applitools Autonomous offer a powerful solution to these challenges. By automating functional, visual, and API testing, Applitools enhances testing efficiency and effectiveness, ensuring higher-quality releases while reducing the risks of user dissatisfaction.

About the Author

Kailash Pathak (Applitools Ambassador | Cypress Ambassador)

Senior QA Lead Manager with over 15 years of experience in QA engineering and automation. Kailash holds certifications including PMI-ACP®, ITIL®, PRINCE2 Practitioner®, ISTQB, and AWS (CFL).

As an active speaker and workshop conductor, Kailash shares his expertise through blogs on platforms like Medium, Dzone, LambdaTest, Talent500, The Test Tribe, and his personal site https://qaautomationlabs.com/

The post Comprehensive Testing with Applitools Autonomous: A Deep Dive appeared first on AI-Powered End-to-End Testing | Applitools.

The demand for high-quality software in the fast-paced tech environment has never been greater. Since companies spend more on QA to make sure their products are not buggy and look good, traditional testing is not enough. Test cases are manual and take time, automation also has its limits, especially when it comes to user interfaces with complex and fast-changing elements. AI-driven software testing comes into play, in this case revolutionizing the way quality is ensured.

Applitools Autonomous is a leading AI-based testing platform that reduces the time and effort required to create, maintain, and run tests. The most effective way of using it is as a tool in visual and functional testing and a valid scalable solution for contemporary applications.

In this blog, we will explore AI-driven testing, what are the challenges of testing modern applications, and how an AI-powered testing tool, like Applitools Autonomous, is helpful in testing applications.

About AI-Driven Testing

The phrase “AI-driven testing” describes the usage of artificial intelligence techniques to help the software testing process. Organizations can leverage machine learning, natural language processing, and other types of artificial intelligence technologies to streamline their testing processes, saving time and resources and optimizing the delivery of high-quality software.

AI-Driven Testing Key Concepts

Automation of Test Creation

The manual script writing of traditional testing can be slow, and prone to errors. This is automated with AI-driven testing in which test cases are automatically generated from the application’s structure, user flows, and user behaviors. For example, Applitools Autonomous can scan an application’s sitemap and spin up comprehensive test suites without you having to do any manual input.

Visual Validation

Visual validation is the strong point of AI-driven testing, making sure the UI functions and looks good on every device and browser. AI can also detect visual discrepancies and changes to the UI that certainly wouldn’t be picked up by standard testing methods.

Dynamic Test Maintenance

Test cases inevitably grow outdated, and applications are always in flux—that can mean a lot of work to keep them up to date. Testing platforms driven by artificial intelligence automatically adapt the tests to complement changes within the application’s UI or functionality. It reduces the burden of maintenance for QA teams and keeps testing relevant and efficient.

Predictive Analytics

Because AI can analyze historical test data to predict potential problem areas in an application, teams can concentrate their testing resources on applications’ high-risk areas. This predictive ability helps an organization’s resources get allocated better and cuts down on the likelihood of critical bugs slipping through the cracks.

Natural Language Processing (NLP)

NLP is often part of AI-driven testing tools that enable users to create test cases based on plain language text. This feature makes it easier to test so that non-technical team members can collaborate on testing with technical team members.

Challenges In Testing Modern Applications

Below are some of the challenges that we often face while testing modern applications.

Too Many Scenarios

Modern applications are highly complex, with hundreds of end-to-end scenarios that need to be tested across a vast array of screens, devices, and browsers. 

Too Many Screens & Devices

In Modern applications, users access digital content on a wide variety of devices, browsers, and screen sizes, each with its own unique characteristics. Manually verifying that an application looks and functions correctly across all these environments is nearly impossible without automated assistance. Traditional testing methods cannot scale to meet this demand, often resulting in inconsistent user experiences and missed visual bugs.

Constant UI Changes

In dynamic development environments, user interfaces (UIs) are constantly evolving. Even minor changes to the UI can require updates to test scripts. This constant maintenance burden can slow down the development process and lead to outdated or ineffective tests.

Different Skill Sets

Teams often consist of members with varying technical skills, leading to the use of different tools and approaches to testing. This creates silos within the organization, where engineers and non-technical testers might not collaborate effectively.

So far we have seen the challenges in testing modern applications. Now let’s see how we can leverage AI to take over the heavy lifting in testing using Applitools Autonomous.

About Applitools Autonomous

Before we dive into Applitools Autonomous, it’s important to understand what autonomous testing is. Let’s use a car analogy to differentiate between manual, automated, and autonomous testing.

Manual testing is like driving a car with a manual transmission, where the driver is fully engaged in controlling the accelerator, brake, and clutch. Every action requires constant attention and input from the driver.

Automated testing, on the other hand, is like driving a car with an automatic transmission. While the clutch is handled automatically, the driver still needs to manage the accelerator, brake, steering wheel, etc. It reduces the manual effort but still requires active engagement.

Autonomous testing is like a self-driving car. Here, you just input your destination, and the car takes over, driving you to your destination while you focus on other things. Similarly, autonomous testing aims to eliminate human intervention, but we’re not fully there just yet. Just like self-driving cars are still evolving, fully autonomous testing is a future goal we are working towards.

Applitools Autonomous With AI

Applitools Autonomous revolutionizes the testing process by bringing the intelligence and precision of top QA professionals to an unprecedented scale through AI. 

As the first autonomous testing platform, Applitools Autonomous lightens the load on your development team by automating the entire testing lifecycle—from test creation and execution to maintenance and reporting.

Applitools Autonomous is an autonomous testing platform designed to automate and enhance the entire software testing process.

Here’s a breakdown of how it works:

• Automated Test Creation: Applitools Autonomous intelligently scans your application’s sitemap to automatically generate comprehensive test cases for every URL. This ensures that your application is thoroughly tested across all pages, eliminating the need for manual test script writing.

• AI-Driven Visual Assertions: The platform applies advanced visual AI to monitor and track changes at both functional and visual levels. Whether it’s a minor UI adjustment or a significant functional update, Applitools Autonomous ensures that any deviation is detected and addressed to maintain the highest standards of user experience.

• Continuous and Scalable Testing: With Applitools Autonomous, your tests can be seamlessly integrated into your CI/CD pipeline or scheduled to run periodically. This means your application is continuously tested, providing real-time feedback and enabling faster, more reliable releases. The AI-driven approach ensures scalability, making it possible to manage even the most complex applications with ease.

• Dynamic Test Updates: As your application evolves, the platform automatically updates tests to reflect changes in the UI or functionality. This reduces the need for manual maintenance and keeps your tests relevant and effective.
• Test Results Analysis: After running tests, the platform provides detailed reports, highlighting any issues found. These reports include screenshots, logs, and other relevant data to make it easier to diagnose and fix problems.

Types of Testing with Applitools Autonomous

Applitools Autonomous allows for different types of testing, all powered by its Visual AI:

• Full Website Testing: Enter your website URL, and Applitools autonomously crawls and tests every page for both functional and visual consistency.
• Functional Testing: Ensure that user flows work as expected with AI validating both the logic and appearance of your UI elements.
• Visual Testing: Identify visual differences and UI discrepancies across devices to provide a consistent user experience.
• Regression Testing: Compare current test runs with historical data to catch any regressions introduced by new changes.
• API Testing: Automate API validation to ensure backend services work seamlessly with the UI.

Key Benefits of Applitools Autonomous and My Thoughts

Applitools Autonomous has some strong features that make it worth looking into if you’re trying to streamline your testing process. Here’s my take on the key benefits:

Automatic Test Case Generation

One thing I found impressive is how Applitools generates test cases automatically by crawling your site’s sitemap. It saves a lot of manual work, which can really make a difference when you’re managing multiple test scenarios. The fact that you can describe workflows in plain English is a nice touch, making it easier for non-technical folks to get involved.

Faster Test Creation

The speed of test creation is something that stood out to me. Applitools Autonomous claims to generate tests up to 10 times faster, and in practice, it does seem significantly quicker than traditional methods. The ability to instantly validate thousands of elements and group similar errors together really helps to keep things moving efficiently.

AI-Driven UI Validation

Visual AI is one of the more compelling features. It does a great job of catching both visual and functional issues across different devices and browsers. This kind of coverage is essential if you’re dealing with a variety of platforms and need consistent performance and appearance across all of them.

Proactive Bug Detection

I also like how you can schedule tests or integrate them into a CI/CD pipeline. This means you can catch bugs early on, which is always a plus. Dealing with issues earlier in the process tends to save time and money down the line, and the proactive nature of this feature is a big win.

Generative AI for Expanded Coverage

By scanning the root domain, Applitools builds out Visual AI scans for each page. This feature is really useful for getting broader test coverage without much manual effort, something I think teams dealing with large-scale applications will appreciate.

NLP Test Builder

The Natural Language Processing (NLP) test builder is another feature that caught my eye. It allows anyone on the team to create tests by describing steps in plain English, which makes the tool accessible to non-technical members. It definitely lowers the barrier to collaboration, which is always a plus.

Faster Test Execution

Running tests at scale can be a pain, but Applitools Autonomous handles this well with its DOM replication technology. It cuts down on test execution time, which makes it easier to test across multiple browsers and devices efficiently.

Automated Test Maintenance

One of the more practical benefits is automated test maintenance. As your UI changes, the tests update themselves, which minimizes the need for manual updates. This reduces the ongoing workload and keeps your tests relevant without constant tweaking.

Dashboards and Insights

Lastly, the dashboard is quite intuitive. It consolidates all your test results and provides a clear breakdown, making it easier to analyze outcomes and resolve issues quickly. The actionable insights offered by Applitools help speed up decision-making and improve overall application quality.

Applications Suited for Testing Using Applitools Autonomous

Applitools Autonomous is designed to enhance the testing process across a wide variety of applications, making it an ideal choice for different sectors and use cases. Here are some of the types of applications that are particularly well-suited for testing with Applitools Autonomous:

• Web Applications
  Applitools Autonomous can help web applications in particular, and those with dynamic user interfaces in general, in a big way. What’s more, this platform is capable of carrying out full website tests, to ensure that not only every page on the website is working as anticipated, but the brand appears as intended across all browsers and devices.
  
  Example: A social media platform like Facebook requires constant updates to its features and UI in some way. By automating testing, we can be sure that the user interface stays consistent across browsers and devices—e.g. post creation, messaging, and notifications—with Applitools.
• Mobile Applications
  Because users have access to the same application on different mobile devices, testing responsive design, testing functionality or both are absolutely necessary. The main thing that Applitools Autonomous shines at is validating mobile apps so that they always have a clear, smooth experience across various screen sizes and orientations.
  
  Example: Instagram is dependent on visual appearance and relies on mobile applications. Applitools Autonomous is able to validate that images load correctly (or the user interface adapts to different devices) and that the app’s functionality is still in check after an update.
• Ecommerce Platforms
  Ecommerce applications need to be very well tested to make sure a user can smoothly navigate around, make purchases, and get correct information. The Applitools Autonomous engine can be expanded to verify the visual aspects of the platform and the functional flows (e.g. shopping cart, payment process…) as well.
  
  Example: There are several features that Amazon has to validate: product search, shopping cart functionality, and payment process. Using Applitools we can address these problems by automating the visual and functional testing of all elements to make sure that everything does work seamlessly and the users all get a consistent user experience across different devices.
• SaaS Products
  Examples of software as a service (SaaS) applications are constantly delivering new features and enhancements. Autonomous from Applitools helps you make sure existing functionality does not break while validating the user interface against any visual differences in a regression backlog.
  
  Example: CRM tools such as Salesforce are always busy introducing new features. Applitools Autonomous can run regression tests that run automatically to verify that new updates do not break existing functionalities and that the user interface is still friendly for the user.
• Healthcare Applications
  In the healthcare sector, applications must be user-friendly and reliable. Applitools Autonomous can validate that interfaces are intuitive and that crucial functionalities, such as patient records or appointment scheduling, work without issues.
  
  Example: Applitools Autonomous ensures that crucial functionalities, such as appointment scheduling and medical record access, are tested for both usability and visual consistency.

Conclusion

In a rapidly evolving tech landscape, the need for high-quality software has become paramount. As traditional testing methods struggle to keep pace with the increasing complexity of applications, AI-driven testing solutions like Applitools Autonomous emerge as game-changers. This platform not only streamlines the testing process through automation but also enhances the quality of software by leveraging advanced AI techniques.

About the Author

Kailash Pathak (Applitools Ambassador | Cypress Ambassador)

Senior QA Lead Manager with over 15 years of experience in QA engineering and automation. Kailash holds certifications including PMI-ACP®, ITIL®, PRINCE2 Practitioner®, ISTQB, and AWS (CFL).

As an active speaker and workshop conductor, he shares his expertise through blogs on platforms like Medium, Dzone, LambdaTest, Talent500, The Test Tribe, and his personal site https://qaautomationlabs.com/

The post AI-Driven Testing with Applitools Autonomous: What You Need to Know appeared first on AI-Powered End-to-End Testing | Applitools.