Applitools Integrates Testing Platform With GitHub

Applitools announced today that its test automation tools have been integrated with GitHub and GitHub Actions in addition to being available on the Microsoft Visual Studio App Center.

Company COO Moshe Milman said these integrations make it possible to add testing tools that incorporate machine learning algorithms, dubbed Visual AI, to a DevOps workflow using the Applitools Eyes testing platform. Those tests are run on a cloud platform dubbed Ultrafast Grid.

The goal is to make it possible to easily correlate code changes across different versions of updates to web and mobile applications using any testing framework and programming language, said Milman. Visual AI can now be applied to every build and pull request, he noted.

When feature branches are created, Applitools instantly mirrors those feature branches to create a new set of baseline images. That approach simplifies the automated testing of all feature branches without impacting the trunk and its tests, he said, noting as pull requests are merged back in, the integration automatically updates the target branch with the source branch’s baseline images in a way that ensures no conflicts exist between branches.

The Applitools approach to AI testing also provides developers with more control based on the application use cases, he added. For example, different settings can be applied to test 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.

In general, Milman said the number of organizations that are applying DevOps processes now to the development of both web and mobile applications is increasing. Mobile applications are core to digital business transformation initiatives that have accelerated in the wake of the COVID-19 pandemic. Many of those applications are being built using components that typically are shared through repositories such as GitHub, which Milman noted creates the imperative to integrate testing tools with code repositories and other DevOps platforms.

It’s still early days as far as applying AI to application testing is concerned. However, it’s now more a matter of when versus if organizations will be relying more on AI to test applications. As the number of testing platforms that include AI capabilities expands, each IT team will need to evaluate which approaches provide the most accurate testing.

Nor is it clear to what degree AI might reduce the need for dedicated application testing teams. More responsibility for testing applications has been shifting left toward developers for several years now. Nevertheless, an independent test review of an application before it is deployed is always a good idea. AI capabilities in testing tools should reduce the most common mistakes the developers seem to make regularly.

As part of an effort to make it tools more widely accessible, Applitools also makes Applitools Eyes along with its GitHub integrations available for free for open source projects hosted on GitHub that sign up to be part of Applitools’ open source plan.

Regardless of how DevOps teams gain access to those tools, the future of application testing promises to be a lot let less monotonous.