At its online Future of Testing: Mobile event, Applitools today previewed the ability to apply visual artificial intelligence (AI) to applications that run natively on a mobile computing platform.
Accessed via a cloud service that is currently available for free on a limited basis, the Ultrafast Test Cloud for Native Mobile offering will extend the company’s visual AI tool for browser-based mobile applications to applications that run natively on Apple iOS or Google Android devices.
Applitools CEO Gil Sever said that while most mobile enterprise applications today rely on browsers to make it simpler to build and deploy applications, in time, many more of these applications will be running natively on iOS or Google Android platforms, mainly because they provide a better user experience.
That approach also eliminates the need to rely on cumbersome platform emulators to test applications because the Applitools AI tool can learn the nuances of each platform in a way that streamlines the application testing process.
In fact, visual AI tools will not only make developers and testing teams more efficient, but they also will make it easier for end users to participate in the application testing process, Sever noted.
The Applitools approach to AI testing also provides developers with more control based on the application’s use cases. Different settings can be applied to test, for example, a medical application that requires perfect alignment of pixels versus an e-commerce application that may not require as much fidelity. Developers can then resolve regression issues by employing root cause analytics.
It’s not clear how broadly visual AI tools that use computer vision algorithms to automate testing will be employed. There is no doubt the current pace of application development is faster than most dedicated teams of testers can handle. As a result, more responsibility for application testing is being shifted left toward developers that, in the interest of time, might be more inclined to rely on AI and other forms of automation that can be accessed via a cloud service.
The rise of AI testing tools might also go a long way toward ensuring more applications are thoroughly tested before being deployed in a production environment. One of the first steps in any application development schedule that gets compressed when a project falls behind schedule is testing. As more rote tests are automated, there should be more opportunities for dedicated testing teams to focus on improving the end user experience.
It may be some time before most organizations are routinely employing AI to test applications. However, none of those organizations should expect AI to replace the need for humans to test applications alongside AI testing platforms that can see the actual application. After all, there’s a world of difference between seeing the changes that were made to an application and understanding why they actually needed to be made.
