Artificial intelligence in software testing has arrived


What if software testing could undergo a metamorphosis, becoming better, faster and less expensive all the while letting testers focus on what they excel at? That rosy future could happen, thanks to a sudden interest in artificial intelligence in software testing.

Enterprise solutions provider Infostretch just announced it will offer artificial intelligence in software testing through a brand new service called Predictive and Prescriptive QA. Infostretch isn’t the only option — San Francisco-based startup Appdiff is also bringing machine learning “bots” online as testers. And dinCloud recently announced “James,” a virtual robot QA.

With continuous delivery, continuous integration and DevOps as the hot topics in every software development conversation today, the pressure on testers has never been more intense. “The thing is your crew cannot keep up with the amount of testing that should happen,” Appdiff CEO Jason Arbon said. “That’s one reason for Appdiff. … People can’t keep up any more.”

he solution is artificial intelligence in software testing, or more specifically, an AI subset: machine learning. “Today there are tons and tons of test dataand it’s very hard for a single person to get through it all,” said Avery Lyford, chief customer officer at Infostretch. “It’s tons of report management now. Where are the real issues and what are the real problems?” That is where artificial intelligence in software testing can come in and help sort through the noise, Lyford said.

Infostretch is offering the Predictive and Prescriptive QA product as a service. With a heavy focus on data analysis, Lyford said the artificial intelligence in software testing tool can help streamline the testing process by ensuring the right information is in the hands of the testers who can then make better decisions. The new service can also be used in conjunction with the company’s QMetry offering.

AppDiff is taking a slightly different approach, Arbon said. “We’re going from the end user experience backwards,” he said. “AI bots can do tens of thousands of test cases versus 20 to 100 regression test cases. This plays into today’s DevOps plan to iterate quickly.” Using artificial intelligence in software testing, companies will always know if the UI isn’t working or the UX is struggling, he said.

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