Test Automation Generation using Test Modeller and TMX

Rapidly generate rigorous automated tests in Test Modeller and execute them across a wide range of test automation frameworks using Critical Logic’s TMX.

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Model-Based Test Automation

Test Modeller makes automated testing of complex applications simple, generating rigorous tests and data from easy-to-use flowcharts. The models are built rapidly from existing requirements and tests, before specifying automation objects and actions that have been imported from TMX’s central repository.

The fill-in-the-blank approach makes it possible for anyone to define accurate automated tests, while removing the delays associated with manual test scripting. It further drives up the quality of tests, using powerful mathematical coverage algorithms to generate the smallest set of automated tests needed for testing rigour. The automated tests and data are further tied directly to the requirements model, and update with them, removing the bottlenecks associated with manual test maintenance.

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Single Pane of Glass Automation

TMX executes tests generated in Test Modeller across a comprehensive range of tools, including commercial and open source test automation frameworks, as well as Continuous Delivery tools. You can avoid vendor lock, executing tests in the frameworks best suited to your technologies and teams. Meanwhile, the “single pane of glass” approach of using central models to produce tests for a range of frameworks reduces the need for costly and copious licences.

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TMX and Test Modeller make it possible to test complex applications rigorously, within the same iteration as any changes have been made to the system under test. Watch this short demo to learn how you can catch potentially costly bugs earlier, using Test Modeller and TMX to:

  1. Build accurate flowchart models of fast-changing systems, using a range of connectors and importers.

  2. Synchronise objects and actions from the TMX repository to Test Modeller, rapidly building automated tests using a visual, drag-and-drop approach.

  3. Assign dynamic test data functions to the model, for always up-to-date data that resolves during test execution,

  4. Generate a rigorous set of automated tests, using automated coverage algorithms to create the smallest set of tests needed for optimal test coverage.

  5. Execute the rigorous tests across a wide-range of frameworks, with run results updated automatically across DevOps pipelines.


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Discover how Curiosity can help you automate your testing today!

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