Automation

Speed is king in agile. In a world where most of the agile process is automated, testing is the slowest and most expensive part of getting your app or website deployed to the world. Very few app teams have a decent amount of test automation, and even they still have days of manual testing during each agile cycle before they release new versions of their app. Testing is difficult, especially at the UI level, which is why it is still relegated to humans. But all that is changing with the application of artificial intelligence and machine learning. Join Jason Arbon as he explains how agile testing is ripe for disruption because AI itself is based on examples of input and output—which sounds a whole lot like the testing activity.

When Isabel Evans learned to drive a car, she also learned how to check, clean, and change spark plugs, mend the fan belt with a stocking, and indicate speed and direction changes with arm and hand signals. Now, we don’t expect to have to do any of those things; we just drive the car...

After its highly hyped introduction decades ago and followed by a long, quiet “winter,” artificial intelligence (AI) has slowly crept back into our consciousness. While our Siri and Alexa assistants entertain us, machine learning (ML) has brought new conveniences into our lives...

What does AI mean for the future of testing? What aspects of testing will the machines replace? What things will AI soon be better than humans at and what things will humans always do better than AI? This panel explores the future of AI for testing including thoughts on how humans can prepare for a future of testing where we work alongside AI. Hear experts discuss their views on the future impact of AI in testing and where the boundary between human and AI-powered testing truly lives.