Independent Health Leveraging AI

About Independent Health

Independent Health is a not-for-profit health plan that continually aims to provide the community with innovative health-related products and services, which enable affordable access to quality health care. It is consistently recognized as one of the highest-ranked USA health insurance plans.

When Independent Health announced a new mobile app as an easy way for members to track their deductibles, review benefits, and view claims, most people were excited, including Chris Trimper, Enterprise QA Architect for Independent Health. However, along with the launch of this new mobile app came an exponential increase in new test maintenance responsibilities. “Don’t get me wrong, I thought it was a great idea and could absolutely see how it would benefit our members. But, from my application testing perspective, it posed a big challenge. Testing for two operating systems, Android and iOS, with different implementations, locators, and object identifiers had the potential to significantly increase our test maintenance cost and effort. I was also worried that we would not be able to keep up with the fast pace of change in a mobile app. Our UX and UI colleagues were planning a regular release schedule of small changes, often stylistic, amounting to an overwhelming amount of test automation work.

“People don’t realize that something simple such as changing the color of a button, moving it to a different location on the page, or giving it rounded edges, requires lots of ‘underground’ code changes and therefore test changes. I’m all for innovation and helping our members, but I just wasn’t sure how best to ensure it meets our quality standards within the required timeframe.”

A long-time Micro Focus user, Independent Health already leverages Micro Focus ALM/ Quality Center for all manual and automated test management. This is used in conjunction with ALM Lab Manager and seamlessly integrates with Azure DevOps. All application tests are triggered from ALM/Quality Center and processed through Micro Focus UFT One. The team uses Micro Focus LoadRunner Professional for all web, REST, and SOA protocol performance testing.

Once Trimper found out that Micro Focus has also been implementing Artificial Intelligence (AI) test capabilities within UFT One, he had to learn more about it. UFT One’s new AI-based capabilities increase automation efficiency by simplifying and improving test creation, execution, and maintenance. By infusing AI in the process, objects are identified in the same way a human does. Because AI understands each object and the contextual interaction, a single test script can execute tests on multiple platforms.

“We were skeptical at first, but after a demonstration, it was like Micro Focus had handed us an ‘easy’ button,” says Trimper. “We could see straight away how this would save us an immense amount of time. Automated back-end code-based testing and AI user level testing can complement each other perfectly. With a growing AI icon library, UFT One experiences the application just like a user would. We save time by testing only the actual components that a user interacts with on the screen, and our tests look more like a user story, focusing on workflow and business requirements.”

Following the successful launch of the first mobile app, Independent Health continues to leverage UFT One for its automated testing effort in all business-critical mobile and web applications, web services, and databases such as Oracle, PostGres, and Microsoft SQL Server. Most web applications are responsive and integrate with other solutions, so business workflows start in one system and move to a different one, while ensuring a backend database record is updated. End-to-end testing is of vital importance. A test scenario could simulate the life of an Independent Health member through enrollment, accessing the customer portal, making changes to their benefit plan, submitting a claim, following the claim processing, and receiving claim payment.

“Our application landscape has developed over a number of years,” explains Trimper. “Under the cover of each of the applications we use different programming languages. For instance, we have a major .NET application that we UI test with UFT One. We use lengthy or short tests depending on the scenario we’re working in, but we drive the interface in exactly the same way an end user would. We only need to modify the UI test scripts when the developers change the flow of the application to alter the user experience, or when they add new features. This is a huge time saver for us. We also work a lot with hybrid applications, for instance a Java application that uses a browser for display. When you look at it, it’s a website, but it has different underlying technology and some controls that aren’t common in a web browser. No problem at all for UFT One, the Web add-in ensures that objects from different technology worlds can live side by side. We test our database connections using UFT One API tests which give us user-friendly drag-and-drop capabilities and a defined test workflow.”

The team uses Micro Focus UFT Mobile for Android and iOS application testing, as Trimper explains: “We realized AI adoption could really revolutionize our mobile testing effort. Instead of having to write and maintain two sets of test scripts and two sets of object repositories, we can develop these against just one device.”

The team has enjoyed AI in the context of UFT One add-on capabilities too. The PDF addon with UFT One wasn’t working great with Independent Health’s systems as they used letters generated by 3rd party template engines, which weren’t recognized by the addon. However, AI came to the rescue and now UFT One can read a PDF file exactly like a user would. This supports the compliance effort as PDF files can now be tested to ensure they contain the correct fonts and icons.

“You need to make the mental shift from assuming that test automation needs to be complicated, when with AI it is just simple and easy, completely focused on the user experience,” says Trimper. “AI can teach us about the application too. Sometimes we run the AI component to determine how a user interacts with the app and give us ideas for further enhancements.”

Trimper can see how AI can support a DevOps testing environment more effectively: “This is still such a growth area. We’re getting closer to natural language testing which will offer up testing to a wider audience and reduce the stress on specialized testing teams. Every new UFT One release gives me something exciting to help reduce our time-to-market and fully support the evolution of our new mobile app.”

He concludes: “We collaborated in a spectacular partnership with Micro Focus on the development of the UFT One’s AI-based capabilities. UFT One and UFT Mobile combined now support our automated testing efforts across mobile, and web applications, covering the core of our application infrastructure. Having multi-platform and multi-device test ability, without needing platform development expertise, has revolutionized the way in which we support our members.”