Term: #Data-DrivenTesting
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Codeless Data driven automation testing refers to creating automated test cases without writing code manually. Rather than writing code, testers rely on visual tools that allow them to design test cases through drag-and-drop actions or by recording user interactions.
In the era of rapid software delivery and continuous deployment, traditional testing methods are increasingly being outpaced. Data-driven testing (DDT), once considered a cutting-edge approach in QA, is now evolving into something more dynamic—powered by Artificial Intelligence (AI) and Machine Learning (ML). The future of data-driven testing lies not only in using test data efficiently but also in making that data intelligent, predictive, and automated.
Data-driven testing (DDT) is a powerful approach that allows testers to run the same test logic against multiple sets of data inputs. It improves test coverage, makes tests more maintainable, and helps identify edge cases. However, like any strategy, it comes with its own set of challenges.