In this presentation Luke Freiler will show you how to expand your testing strategy through structured Alpha, Beta, and Delta Tests that leverage real users outside the lab to support your agile and continuous delivery methods.
This presentation reviews some techniques such as machine learning model testing, A/B testing, UI testing and automating the testing on multiple devices using Selenium.
The value of machine learning is rooted in its ability to create models that guide future actions and to discover patterns missed by the naked eye. Machine learning methods are vastly superior in analyzing potential customer churn across data from multiple sources such as transactional, social media, and CRM sources.
Developers continue inventing new technologies to build Web applications. They automatically generate code and markup, and asynchronously load data. And this creates new technical challenges for Web UI test automation.