Many testing teams today use Selenium for their automation needs and rightfully so, Selenium allows for cross browser and mobile support, it’s free and has a large open source community behind it. Regardless of its feature set, Selenium and test automation in general has its own list of pain points like test maintenance and test coverage. These pain points can have a large impact on testing metrics depending on the test architecture used and the design patterns being followed. To address these pain points a team can utilize areas of Artificial Intelligence (AI) and Machine Learning (ML) via open source libraries. This enables the tests to find their own elements and attempt every possible combination of test cases, which a tester could then store, rerun, and iterate on. This approach effectively gives Selenium a brain in the form of models and actions. Join Mike Wagner, Test Architect and Principal Consultant for tap|QA as he leads this informative session for teams interested in integrating Artificial Intelligence into their existing Selenium framework. Takeaways: Understanding of the different areas of Machine Learning/AI with an emphasis on: * Convolutional Neural Networks (How they apply to element selection) * Reinforcement Learning (How it applies to test coverage) Approach for implementing Convolutional Neural Networks and Reinforcement Learning into an existing Selenium framework. * Introduction to top open source libraries related to Machine Learning


19:00 - 20:00 hs GMT+1


Application Development and Management
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