Software testing and QA teams can leverage Machine Learning (ML) and Artificial Intelligence (AI) to improve their automated test strategies and keep pace with recurrent releases—with the aid of analytics and reporting. For instance, software testers can use AI algorithms to discover and prioritize the scope for additional automated testing. Besides sorting out software tests’ workloads, AI-powered test apps can optimize test suites after identifying unneeded test cases and ensuring optimal test coverage by inspecting keywords from an RTM.

The pillar on which smart automation rests is ML. As per the Capgemini World Quality report, 38% of companies have planned to execute Machine Learning projects in 2019.

#software testing #testing #trends