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Technologies for DevOps, Test Automation and AI: The QA Financial Forum Paris 2019

8 October, 2019
News and research on financial software quality assurance and risk management

Micro Focus readies RPA and AI visual testing tools

20 June 2019
The UK-based testing giant is planning to launch new RPA and AI testing tools that will “revolutionise” functional testing, says Raffi Margaliot, head of application delivery (pictured).

London-listed software firm Micro Focus is planning a series of new product launches, starting with an RPA product roll-out in July, and followed by an AI visual testing tool later this year, to be delivered via Micro Focus’s Unified Functional Testing (UFT) product platform.

The new visual testing tool under development with Micro Focus engineers in Israel, Romania and China: “Looks like it will revolutionise the world of functional testing,” Margaliot told QA Financial. “We now have a solution that leverages AI in beta with a few of our customers where we are able to learn about the application from a computer vision perspective -- inspecting the shopping basket or the menu on an app, for example – analysing the UI visually and build tests that are lot more robust.”

The technical challenge addressed by this computer vision solution, said Margaliot, is: “To achieve accuracy in identifying the object on the screen -- whether that is on iOS devices, on Android devices, on Windows or Macs -- in a consistent fashion and be able to recognise not just trivial objects, like buttons, but also look at advanced and customised UI elements.”

“We also have another AI project for natural language processing,” Margaliot added, “So instead of scripting your tests in a scripting language such as JavaScript, we are able to add human language like ‘fill in credit card details’.”

“We are able to really simplify functional testing this way. And a combination of AI, computer vision and natural language processing should enable a less skilled workforce to leverage automation.”

In a further step toward the application of AI testing tools, Margaliot’s teams is also working on how to validate algorithms produced with AI, to see if they are behaving as expected. “This really is uncharted territory, with no solution in the market,” said Margaliot.

Tel Aviv-based Margaliot is a 21-year test automation veteran who started his career with Mercury Interactive and then moved on to head application delivery at HP. Three years ago, HP sold that business, including its core ALM platform for software development to Micro Focus for $8.8 billion. It’s a deal that has proved to be controversial. In March 2018, Micro Focus said the merger was 12 months behind its schedule for delivering value and the company’s share price plunged from a 2017 high of close to £29 to below £10. This year it has recovered strongly, to over £20.

New competitors in the test automation space have continued to stalk Micro Focus’s many customers, in an attempt to lure them away from long-standing contracts. Micro Focus, they have been saying, has been content to live on legacy long-term licence fees and is no longer an innovator.

But Margaliot insists that the new AI-driven products being launched will reinforce Micro Focus’s true position as a software vendor that bridges legacy mainframe infrastructures with new, club-based architectures. This is particularly relevant to Micro Focus’s financial services clients, he said, many of which need to maintain those mainframe platforms.

"The principles of DevOps, such as continuous experimentation and feedback, are easier for a startup with a single technology  stack,” Margaliot said. “But our customers in financial services are typically managing decades of technology and software.”

“A key challenge those financial firms face is that almost every business service is using many different applications in different technology stacks. Our approach is that that we are bridging the old and the new, and not making our customers tear out what they already have in place.”

"A big part of the Micro Focus DNA is connecting the old and the new, and not having customers replace everything. There is a huge eco-system of tooling around DevOps, commercial and open source tools and our strategy is to help our customers integrate with that eco-system.”

The shift to DevOps at financial firms is not happening in a uniform way, Margaliot added. “We have found that performance testing and security remain with core teams whereas functional testing has moved to Agile teams,” he said.

A key strategy for Micro Focus is integrating its different tools with new vendor partners, such as Tasktop, the performance management platform, reflecting a more general shift from project management to the management of different IT products, and the growing importance of value stream management is more important, Margaliot said.

“When customers choose Micro Focus, they know we will support them for the long term,” said Margaliot. “If they invest for years in mainframe lifecycle or client service applications and package applications we'll make sure they can evolve them and take them in to the future versus ripping them out and introducing new things.”

Margaliot is confident that Micro Focus’s new product launches planned for this year will stamp it as the leading innovator in the software testing marketplace, partly because of the number of technology stacks supported by UFT. He also sees testing continuing to offer a huge growth opportunity to the firm as its customers seek to accelerate delivery and increase their rates of automated testing.

While Micro Focus may consider acquisitions in the AI space, they would be mainly geared to acquiring developer talent rather than proprietary technologies, Margaliot said. “Specifically, for what we've built [for AI testing], when we looked we did not find any existing solution to buy. We came to the conclusion that the IT we have would be enough to transform the market.”

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