When you look back in test automation, there are three different periods. These are the following:
Test Automation: First Period
In the first period, you will find some vendor tools like WinRunner, Silk Test, and QTP of old-time. These were the solutions that began it all and have set the platform for the future testing automation innovation such as Selenium.
Test Automation: Second Period
Selenium began the second wave of test automation, counselling more on developers and programming best practices when creating automated tests.Selenium provides a playback tool for authoring functional tests without the need to learn a test scripting language.
The present buzz these days is around AI and Machine Learning. Companies are racing to create tools they can pitch as “AI-driven.” In fact, at a latest call Google conference CEO Sundar Pichai opened the event by stating that “We’re moving from a mobile-first to an AI-first world.”
Test Automation: Third Period Tools
Here are just a some of the “third wave” automation tools. One of the basic features of these softwares is that varoius of them are leveraging machine learning and AI-assisted technology.
Applitools is one of the first tools in the third wave, and it made people start believing that a new way of testing is possible.When I first heard about visual validation testing, which uses a sophisticated algorithm to out potential bugs in your application without you explicitly calling out all the elements, I thought it must be B.S.I discovered there actually are no visual processing settings, percentages, or configurations that require to be set up to create visual testing with Applitools. Applitools gives an end-to-end software testing stage generated by Visual AI. It can be the use of people who are in Test Automation, Manual Testing, DevOps, and Digital transformation.
2. Sauce Labs:
Certainly, Sauce Labs were one of the initial contenders in the cloud-based test automation space, but with all the data they presently have access to they’re in a great position to grip machine learning and come up with some cool insights.That was one of the points that came up during the 2017 SauceCon conference. During the keynote, CEO Charles Ramsey presented a slide that showed how we've gone from mainframe all the way to iOT, in addition things such as artificial intelligence, machine learning, and deep learning.
Testim tries to grip machine learning to speed up the authoring, execution and most essentially the maintenance of automated tests. Their motive is to assist you to begin trusting your tests.Testim focuses on reducing your flaky tests and test maintenance, which they see as one of the most significant challenges for most organizations.Testim allows you to create amazingly stable codeless tests that leverage our AI, but also the flexibility to export tests as code.
Sealights is a Cloud-based platform. We all see that developers and QA–both managers and engineers–are very industrious these days using CI and CD practices, where they have recurrent releases and not sufficient time to test the complete application several times.That’s one of the main motive Sealights was created.
With the use of Machine learning like technologies which analyzes both the code and tests that run for it, Basically, it lets you find the coverage of your tests.But when Sealights says “tests,” they don't only aim unit tests; they aim any kind of test, from functional, manual, performance, whatever you name it.
"Quality obligation" is even an all the more exciting observation they permit, as it particular the client's endeavor on the things that is significant, by refreshing the person in question absolutely which records/methods/lines have changed in the last build that wasn't tested by a particular test type (or any test type). Once you will find that, you can easily ensure any code that is untested will not go to the Production before undergoing at least a minimal test.
Test.AI is promoted as a tool that will append an AI brain to Selenium and Appium. Jason Arbor was the creator of it, and also a co-writer of "How Google Tests Software and the founder of appdiff". Tests are explained in a simple format close to the BDD syntax of Cucumber, so it needs no code and no need to mess with element identifiers. The AI recognizes screens and elements aggressively in any app and automatically drives your application to execute test cases. It’s sufficiently smart to know that if an element ever changes it can adjust and identify it with you having to make any manual changes. But that still in its beta stage., but I was given a sneak peek of it by Jason.