Disruption is rife – Embrace Machine Learning to amplify your test efforts

We have now spent over a year living with the smart speakers Amazon Echo and Google Home, listening to music, asking crazy questions, getting news reports, and so on. While our smart assistants are entertaining us, Machine Learning (ML) has also brought convenience into our lives with solutions such as Netflix, Spotify and Uber. Today, online payment platforms are using machine learning to combat fraud. These emerging trends demand our attention as Artificial Intelligence (AI) starts to be applied in ways that directly affect our day-to-day life, one in which the Test community won’t be immune.

During this session, we will explore applications of Analytics and Machine Learning across the industry to provide a view into how this is being used to optimize software testing activities. We will identify opportunities across the Software Engineering and Testing landscape for the application of AI, ranging from determining the high-value test cases, performing risk based testing, optimizing test automation and configuring regression testing to dynamically generate change based regression test suites. This talk intends to provide tips & tricks about how to prepare yourself in skillset and mindset to willingly embrace the application of Analytics in software testing.

Key takeaways:

Improve the quality of software by identifying high value test cases & performing risk based testing.
Using analytics to optimise test automation and configure regression testing suites dynamically.