In algorithmic-based applications, feedback loops continuously change inputs and outputs, limiting the use of standard testing techniques. Model-based testing techniques allow us to configure a desired business process through the use of tools, such as Conformiq, Reactis tester, TVG, and TorX. These model-based testing tools generate both test cases and test scripts automatically, autoexecute them, and analyze the test results. Every time feedback loop changes the input, model changes as required, and hence all test cases are changed automatically. Every time the feedback loop alters the input, the models change and the test cases are automatically updated. The most important part of model-based testing is designing a model for automated test case generation. This requires testers who are able to apply model-based thinking to test case generation based on the needs of an algorithmic business. Refer to the following diagram:
The benefits...