Why use model-based testing?

What might be difficult to see in ambiguous text is readily visible in models. Often the highest integration risks are missed when testers work with ambiguities. Our team understands why this makes data testing difficult to achieve. We use modeling to create a systematic approach for test designs, ensuring more comprehensive coverage at all integration and transformation levels. In this way, our team focuses on the highest risks first, ensuring defect discovery earlier in the lifecycle.

Models Define Systems and Processes under Test

In most projects, several models are created for the design and development of the project. These models represent everything from the data and systems to the transformation maps and process sequences. MG Harney leverages the value of this information to create test models that reduce test design efforts, saving time and money.

Models Define Test Designs

Models are not limited to conveying integration architecture and development details. Models capture and communicate test team activities through work and data flows. With models, our test team defines their design ideas in a clear and unambiguous way that helps the project achieve its quality goals.

Models + Data Cases = Test

Models alone do not create a data test. Models represent the maps and decision processes for testing. It is when data cases are combined with models that complete tests are formed. MG Harney creates a relationship between models and data cases for a comprehensive test design.