Model based testing is a software testing approach where test cases are derived from abstract models that describe the expected behavior of a system. These models can represent workflows, state transitions, decision rules, or user interactions, and they serve as a blueprint for generating test scenarios systematically.
One of the main advantages of model based testing is improved coverage. By using models, teams can identify edge cases, rare paths, and interactions that might be missed with manual test design. This is particularly valuable for complex systems with multiple workflows, integrations, or business rules.
Model based testing also supports maintainability. When system requirements change, updating the model allows corresponding test cases to be regenerated automatically, reducing manual effort and keeping tests aligned with the latest specifications. This approach integrates well with automation and CI/CD pipelines, enabling continuous validation of application behavior.
By providing a structured, systematic way to generate tests, model based testing helps teams increase efficiency, improve reliability, and ensure that software behaves as intended under a wide range of scenarios.
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