Perforce Software, a DevOps solutions provider, has introduced Test Data Pro by BlazeMeter, an advanced component of its continuous testing platform.
Test Data Pro utilizes AI technology to streamline and make test data generation more accessible. The primary goal is to address the significant challenge of obtaining accurate and synchronized test data, which is particularly crucial as organizations embrace a “shift left” approach in testing, Perforce explained
“Obtaining test data from production is a time-consuming process involving multiple teams. PII data has to be properly scrubbed, and the data has to be synchronized across the testing landscape,” explains Stephen Feloney, VP of continuous testing at Perforce. “Because of this lengthy process, testers refresh data less often than they should. Now consider today’s world of rapid releases. There is no time to get data and prep it. Developers and agile testers needed to test yesterday.”
One of its standout features is the utilization of generative AI technology to swiftly profile and create data-generating functions and test data from scratch. This level of precision ensures that users have access to highly accurate and tailored data necessary for executing tests, ultimately leading to increased testing speed and accuracy. Moreover, Test Data Pro excels in synchronizing data across various aspects, including the data driving the test, data in mock or virtual services, and data in systems under test.
This solution also addresses the need for expanded testing coverage. By creating diverse sets of data, Test Data Pro enables comprehensive testing across a wide range of scenarios, even encompassing negative testing.
In addition to enhancing testing efficiency, Test Data Pro also places a strong emphasis on data privacy. It achieves this by automatically generating synthetic, realistic test data. This approach ensures that testing environments do not utilize real production data, eliminating concerns related to data privacy and compliance risks.
Lastly, Test Data Pro introduces the concept of chaos testing for system resilience. By integrating both positive and negative test data during test executions, it empowers users to assess the resilience of systems and validate the performance of applications under circumstances that they might not have tested under conventional methods. This innovative approach helps organizations identify and address vulnerabilities, ultimately enhancing the robustness of their software systems.
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