Test Modeller for GitLab

Enterprise-wide test automation adoption

Watch this short example of Test Modeller working with a Selenium-Java framework to see how:

1. Test Modeller automatically parses Java, C# or Python code, importing its core objects and actions in minutes.

2. The automation logic becomes fully re-usable, overlaying it onto flowchart models that are quick-to-build and easy to maintain. Connectors are provided to import test cases and requirements, with full BDD and TDD support.

3. Anyone can build automated tests for complex systems. An intuitive “low code” test builder leverages code from existing frameworks, combining the flexibility of coded techniques with the simplicity of low code approaches.

4. Automated tests detect more defects first time round, using automated algorithms to generate the smallest set of tests needed to “cover” the model.

5. Test data for every test is defined at the model level, using over 500 dynamic functions that resolve during test creation.

6. Automated test scripts and data can be generated for commercial, open source and homegrown frameworks, avoiding vendor lock and testing across the whole testing pyramid from one tool. 

7. The optimised tests and data can be synchronised back to existing GitLab projects, using CI/CD pipelines to execute them.

8. Run results are synchronised with the models in Test Modeller, as well as across Application Lifecycle Management (ALM) and Project Management tools. 

9. Granular analysis of test failures reduces defect remediation time, while test automation frameworks are integrated into DevOps pipelines.

10. The automated tests and data can be updated in minutes as the application changes, simply updating the central models and re-generating tests.