AI has been making a lot of noise off late, especially in the context of software development. Of course, this topic is quite wide, but in this article, we shall focus our attention on AI-driven automation testing. Let us start with understanding what is AI and automation testing. Automation testing refers to the process of executing software test cases with assistance from automation-driven testing tools.
As for AI — well, this globally renowned technology is a computer’s ability to learn and improve on its own. Think of it as the tool that is helping mankind build better and smarter machines that can execute a variety of tasks that, till a few years ago, would have necessitated the involvement of a human resource.
The use of AI in software testing makes the software development lifecycle easier. With the application of reasoning, problem-solving, and machine learning, artificial intelligence helps reduce the tedious and manual aspects of software development and testing while automating the whole process.
Now that we have our basics sorted, here are some of the key benefits of AI automation tools.
Cut costs: Provided you pick the right AI automation tools, one can very quickly save time across a variety of aspects. Not only that, but AI can also help prevent errors across processes. All of these factors, cumulatively, contribute to sizable cost savings for the company.
Simplify test execution: Since AI can build intricate test cases within hours, it takes a huge load off QA testers’ shoulders.
Easy maintenance: Maintenance of tests can become a sizable issue for testers, more so when it involves a large-scale product and an accelerated development ecosystem. Such time-consuming maintenance processes can be delegated to AI tools, which can help save a lot of time.
Now, time to see precisely how one can use AI in automation testing.
Develop automated tests: AI tools can easily understand the intricacies of the company’s systems and tools to better comprehend relationships between the document object model’s various parts. To what end? To help testers create substantially better quality automated tests.
Crawling the app: One of the key benefits of AI in this context is that it can crawl the app for countless key data points, such as load times, etc. This helps the AI platform to analyze the company’s product tenet over different development cycles and, eventually, help determine issues, variations, etc.
Finally, let us wrap this up with a quick list of some of the most popular AI power test automation tools in the market.
Functionize: An AI-driven testing tool based in the cloud it helps leverage NLP to create tests. It can be used across a variety of OS platforms as well as web browsers.
TestCraft: A rather popular tool for continuous and regression testing, TestCraft is used in conjunction with Selenium and allows testing teams to develop automated test cases in Selenium. One of its biggest USPs is that test cases can be created using a drag-and-drop dashboard, which means coding skills are not necessary for using this platform.
Applitools: A tool designed for visual UI testing and monitoring, Applitools is driven by Visual AI. This platform can be used by testers with varying levels of skill to gauge the visual facets of the app’s UI. Since it is a regression tool, Applitools is also used to ensure user-rated pages, screens, etc. have not changed during tests.
Now, if you too want to leverage the countless benefits of AI-driven automation testing, it would be a good idea for you to start looking for a trusted automation testing company to help with your project and endeavors.
