According to Micro Focus, as businesses place increased emphasis on developing innovative applications that better support users, “scaling testing efforts becomes an elusive goal”.

“These new AI-based capabilities ensure application teams can meet growing demands in an effective, efficient and agile way by increasing test coverage and test asset resiliency, and reducing test creation time and maintenance efforts,” Micro Focus said in a statement on Tuesday.

“The increase in pace and frequency of software releases, the proliferation of operating environments, and the exponential growth in the number of test cases has demanded the use of AI to revolutionise software test automation and positively impact both the efficiency and effectiveness of functional testing,” the company claimed.

“Over the past two years, we’ve steadily infused our existing products with AI features. Last June, we debuted new AI-based capabilities to help organisations overcome the challenges of mobile testing, and this announcement extends the same support to web-based testing,” said Raffi Margaliot, senior vice president, application delivery management, Micro Focus.

“More importantly, this customer-centric innovation is available to our extensive customer base, with intelligent tools to accelerate adoption of AI within their existing testing assets.”

Micro Focus says its AI-powered test automation in the UFT Family lets users:

- Streamline automation: Instead of creating multiple scripts for every possible combination and transaction, users only need to compose a single script that will automatically run on multiple platforms and browsers. This reduces the overall time spent on creating and maintaining test assets while increasing test coverage, and lets teams keep up with the evolving technology landscape and user demands.

- Consistently improve with little effort: The UFT Family’s AI framework evolves and adapts based on a crowdsourced feedback mechanism. Customers are invited to expand and refine the AI model’s training data by securely and privately contributing information about their unique user interface paradigms, to constantly improve accuracy of object recognition.

- Shift testing everywhere: A combination of an AI software development kit (SDK) and natural language processing (NLP) lets technical and non-technical testers easily write tests and reduces the time and effort of technical testers in the creation/maintenance of automation code.

“To adequately test a new mobile application, we knew that generating and maintaining all the test scripts required for our quality standards was going to be difficult within the required timeframes,” said Chris Trimper, enterprise QA automation architect, quality assurance engineering, Independent Health Insurers.

“With the new UFT One AI-based testing capabilities, we were able to leverage a single set of multi-platform scripts across iOS and Android and reduced mobile test maintenance by an estimated 35%.

“It also enabled us to provide rapid feedback to project teams from CI builds and to focus more on overall quality of the new mobile application.”