Testing at speed requires constant access to complex environments, populated with accurate test data. However, test automation today often hits the barrier of unavailable or misconfigured environments, while inaccurate or misaligned test data causes test failures and low test coverage. This is often because manually creating virtual services and test data from the scant information available about complex system dependencies is slow and unreliable. Put simply, data – both virtual and test data - kills automation ROI. Yet, the complexity of systems is only going to continue growing.
Join this webinar to see how modelling and data generation combine for truly continuous testing, automatically deploying complex environments filled with rich test data. You will see how data modelling removes the time and errors associated with system complexity, building accurate data models from data sets recorded during manual testing. With the data model, generating virtual data becomes trivial, quickly producing request-response pairs for every possible test. Accurate and complete virtual environments can then be spun up, with comprehensive test data populated simultaneously into the test environments. That means the right test data, populated in the right environment on demand, making continuous testing a reality.
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