Automated test generation for data-driven frameworks

Create optimised data on-the-fly for continuous data-driven testing. Test Modeller avoids the time spent maintaining complex data in spreadsheets for test automation, optimising testing based on risk to find more bugs while they are quicker and more affordable to fix.

Data-driven testing or data-driven bottlenecks?

Data-driven test automation is only as rigorous as the test data that feeds it, and only as fast as the time spent maintaining that data. Testers today often feed in data via spreadsheets, maintaining a complex set of files for different test scenarios. The data might be pulled from production, creating compliance risks in less-secure non-production environments, or it might be made by hand. Either way, the data combinations available typically fall far short of the logical variations contained in today’s systems, which far exceeds the “happy path” values commonly found in production, as well as the time available to make data in-sprint. Overall, testing with a narrow slice of Excel data risks costly bugs, non-compliance, and testing bottlenecks, calling for a new approach to data-driven test creation.

Continuous, data-driven testing

With Test Modeller, rigorous data-driven testing occurs seamlessly as part of CI/CD, dynamically pulling data and generating optimised scripts for fast-changing systems. Test Modeller imports data stored in spreadsheets and beyond, quickly building a structured and easy-to-use repository of data. Automated model generation converts data sheets in the repository into dynamic data models, creating intuitive flowcharts of the system-under-test. The easy-to-maintain flows provide collaborative documentation for complex systems, while enabling risk-based test generation for data-driven test automation frameworks.

data-driven test automation using Test Modeller

Test Modeller provides a range of test generation algorithms that optimise data-driven testing based on time and risk. The click of a button or automated CI/CD process generates the smallest set of test cases and scripts needed to satisfy a given risk profile, pulling rich rows of data on-the-fly for continuous test execution. As critical systems change, testers are no longer forced to hack complex data or manage cumbersome folders of spreadsheets. They can quickly update central models to maintain the data-driven tests needed to find bugs earlier and at less cost to fix.