The era of intelligent testing

Deepak Parmar
February 9, 2018

How intelligent testing is challenging the norms of QA

Intelligent testing seems to be the new buzzword in 2018. But what comprises intelligent testing?  Essentially it is the combination of machine learning and AI-enabled analytics, and continuous feedback that helps testing teams to predict outcomes and reduces time to market of software projects/products.

Intelligent testing can sharpen up every aspect of your business from achieving sales targets to outdoing the competition. The idea is not only to gain intelligence but actionable intelligence to do more with data and software. This proactive and prescriptive approach to anticipating defects and resolving them before they happen is what makes this approach a game-changer.

A moving goal-post

The reason why AI powered testing is so interesting is that the problems it can solve are not deterministic. Also the solutions that it offers change as the systems incorporate new data. This is a marked shift from the deterministic way of testing. As the methods and technology change, so will the expectations and results.

To understand how testers can make the most of intelligent testing, read this experience report by Angie Jones, Senior Software Engineer in Test at Twitter, called “Test Automation for Machine Learning: An Experience Report”. Jones used machine learning to analyze an advertising application. The product used analytics to decide the best ad that a business could provide to a specific customer in real-time.  “As technology advances, so must our test approaches. In this case, hard rules such as “the exact results must be known in order to test or automate” had to be revisited and challenged.”

In our latest newsletter we explore this trend further with our posts on how artificial intelligence helps deliver quality at speed, and the importance of measuring your effectiveness. As technology and business processes evolve, there is a definite shift from ‘making do’ to doing things smartly and efficiently whether it is automation or testing. Would you agree? What are your views on the subject? We’d love to hear your feedback.

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