Struggling to provide the same user experience on multiple browsers? This means you are still restricted to traditional development practices where you are targeting only one browser at a time. The alternative? We suggest that you use modern cloud-based platforms like LambdaTest to add automated cross-browser testing using tools like Selenium ChromeDriver, along with advanced practices like artificial intelligence and machine learning.
Unaware of the integration in cross-browser testing? Don’t worry! We are here for you. Our article will help you understand how AI can change cross-browser testing, the major features that LambdaTest will provide for this, and how you can add this entire process to your testing workflow.
The Challenge of Modern Cross-Browser Testing
Do you still not completely agree with the inclusion of artificial intelligence in modern cross-browser testing? Let us divert our attention towards some of the major challenges that you will face with the traditional practices, and which can be solved with AI:
- We all know that your end user can access the application on thousands of browsers currently available. In such a scenario, it becomes almost impossible to generalize the test cases or anticipate your target browsers. Since a huge section of your target audience will not update their browsers, you’ll also have to extend your cross-browser test cases to these outdated browser versions as well.
- Modern web applications come with native integrations for advanced JavaScript frameworks like React, Angular, and Vue.js. These are mainly implemented so that the developers can add a microservices architecture for backend services. However, with the growing size and complexity of modern apps, every minor update in this workflow can completely break your traditional cross-browser test cases.
- It is true that cross-browser testing is mostly dependent on the software of the application, but various underlying options, like the operating system, can have a significant impact on the functioning of your web apps. Moreover, the change in screen sizes, device capabilities, and input methods will also have a significant say in this entire workflow.
- Finally, traditional cross-browser testing often uses manual testing, which can be time-consuming and also very hard to scale with complex web applications. Modern agile and DevOps practices demand that you update your apps frequently, almost every day. So, you also have to integrate continuous testing to ensure that all these updates do not break the basic functioning of the application. This entire workflow will become impossible with traditional cross-browser testing.
How AI Solves The Challenges
Now that we have a clear understanding of all the challenges that you can face with traditional cross-browser testing, let us divert our attention toward some of the major features that AI introduces to overcome these obstacles:
- Intelligent Test Generation
Are you struggling to create the test scripts for every existing scenario? Rest assured as AI will examine your web app structure and user interactions to automatically propose the test cases or even create it, if required. By scanning the Document Object Model, analyzing user pathways, and identifying important user interface elements, AI can speed up the test creation process while ensuring proper coverage.
- Smart Object Recognition
If you are still using element locators like XPath, CSS selectors, or ID attributes to locate the UI elements, you will see that they are very prone to break when there are any changes in the front-end code of your application. Instead, AI tools use this image recognition or advanced pattern-matching algorithms to find and interact with UI components without relying on these locators.
- Predictive Analytics
If you’re working on an application for a long period of time, it will have multiple data on defect frequency, component reliability, and typical user flow. By using AI models, you can analyze all this information to predict which areas of the application are most prone to failure. Depending on all this information, you can retarget all your testing resources efficiently.
- Visual Regression And Anomaly Detection
A major benefit of using artificial intelligence with cross-browser testing is that you can compare user interfaces at the pixel or layout level. Therefore, you are no longer limited to manual checks of screenshots.
Using the capabilities of machine learning-based visual comparison format, you can find very minute differences in layout, styling, or rendering. In most cases, you will realize that all these changes are often overlooked by manual tests.
What Is LambdaTest
LambdaTest is an AI-native test orchestration and execution platform that lets you perform manual and automation testing at scale with over 3000+ browsers, OS combinations, and 5000+ real devices. Let us now divert our attention to some of the major features of LambdaTest to further help you understand its role in modern application testing:
- With LambdaTest, you can integrate various automation frameworks like Selenium and Appium to initiate automation testing processes like automated cross-browser testing and automated mobile application testing.
- With this platform, it becomes very easy to keep track of all the bugs that you will be detecting in the test execution process. Why? LambdaTest comes with a native bug tracker out-of-the-box.
- While using LambdaTest, every member within your testing team will have an idea about the current status of the test execution process. This is because it comes with a real-time test activity logger that keeps track of all the test execution processes.
- Finally, after running the test cases, LambdaTest will automatically generate a comprehensive test report consisting of multiple useful elements like videos and screenshots. The purpose is to help you find the faulty elements and quickly implement the required debugging and troubleshooting steps.
LambdaTest’s AI-Driven Features and Benefits
Let us now go through all the AI-driven features that you can access while using LambdaTest. While discussing these features, you will also understand how you can benefit from the integration while executing modern cross-browser testing:
Automated Visual Regression Testing
If you’re attempting to implement visual regression testing manually, you’ll find yourself capturing screenshots of various pages or elements across multiple browsers and then comparing them side-by-side. This approach is not only time-consuming and error-prone but also susceptible to overlooking subtle design changes, text overlaps, or spacing inconsistencies.
Instead, consider leveraging LambdaTest’s AI-native visual regression testing. Their platform utilizes machine learning algorithms to automatically analyze screenshots captured from multiple browsers, comparing them against your baseline images.
These intelligent algorithms understand the context of the images, effectively distinguishing between significant visual changes and minor pixel shifts caused by factors like anti-aliasing or font rendering differences. This ensures that your tests focus on meaningful discrepancies, reducing false positives and enhancing the accuracy of your visual validations.
Intelligent Test Scheduling and Prioritization
While working in a continuous integration environment, your regression test will have hundreds or even thousands of test cases. If you try to run them manually, they will consume a lot of time and resources and even slow down the entire infrastructure.
In this scenario, the AI model of LambdaTest will analyze the historical test data, including the pass/fail patterns, component reliability, and frequency of changes. By understanding all this data, it can intelligently schedule and prioritize the tests that are most likely to fail.
It is also worth mentioning that if the system finds a recent code commit that can affect a specific model, it will prioritize the test related to that specific model. This implementation will deliver quicker feedback on the critical functionalities of your application.
Self-Healing Test Scripts
Working with traditional Selenium or WebDriver-based automation testing? Then, you must still be using locators like ID, class, and XPath to find the UI elements. Do you know a simple change in the UI can break all these locators? It can cause your tests to fail even if the application is functioning absolutely fine. Moreover, the test maintenance process will become a very tiring step as you will usually be updating all these broken locators across multiple test scripts.
To solve this issue, LambdaTest uses an AI layer that self-heals the test scripts in real-time. It achieves this process by combining multiple factors, such as element type, relative position, text levels, and prior test run data. Depending on all these implementations, the system can automatically detect and fix the change locators.
Performance and Load Testing Insights
In an old testing environment, you will be running the performance and load testing in separate environments using separate tools. All these tools will create huge volumes of metrics like response times, throughput, and error rates. If you try to monitor and analyze these metrics manually, you will be creating massive bottlenecks for the timely delivery of the application.
So what’s the solution? LambdaTest uses real-time monitoring and AI analytics to identify performance changes across various browsers and operating system populations. By understanding logs, resource usage, and response time, the platform can find underlying issues and provide suggestions for immediate improvements.
Automated Accessibility Testing
Since accessibility is one of the most important parameters for modern web apps, you will require specialized tools like screen readers or static analytics for HTML structures when trying to implement it manually. So, the entire implementation will be time-consuming and can lead to certain errors in terms of minor accessibility implementations.
However, with LambdaTest, you will have AI-assisted analytics checks directly included in the cross-browser testing pipeline. Therefore, you can automatically scan for issues like missing alt texts, improper ARIA attributes, insufficient color contrast, and even more. This implementation will also learn certain accessibility errors that are tied to a specific platform or design patterns and prompt you to fix them at an earlier stage of the development cycle.
The Bottom Line
Based on all the areas that we discovered in this article, we can easily say that cross-browser testing is one of the most important yet the most challenging areas of software testing. However, by using the capabilities of artificial intelligence with cloud-based platforms like LambdaTest, you can easily run the test cases on a huge selection of browsers, devices, and operating systems.
So this entire integration will be your one-stop solution to help your teams deliver high-quality products faster and more reliably. Moreover, test maintenance, which was once the most hated task of the development project, becomes more manageable using the self-healing scripts.
Want some final advice? Look for all the trends and upcoming innovations in this segment of artificial intelligence and cloud testing. Why? You will be able to provide the best end-user experience to your customers to constantly expand your target audience and have a positive brand image.
