In test automation, there are often cases where you might have multiple data sets for which you need to run the same tests on. This approach has been described with several names, including data-driven testing, parameterized testing, or table-driven testing. In mabl, we call it data-driven testing, or DDT. This is the process of loading data that is external to your functional tests to strengthen and extend your automated test cases. It is possible to create mabl tests that you then parameterize to run across several different inputs.


Data Driven Testing Master Class

In today’s connected world, data drives everything. Consider something as simple as your morning alarm clock. At the start of the day, your alarm goes off at the time that you need to get up.

Of course, your alarm clock doesn't know what your routine is. That designated time is really just data your alarm uses. If you need to wake up earlier one day, you change the data and the alarm goes off earlier.

With Data Driven Testing, you can easily control what data gets used in your tests, giving you greater control over what your tests do and the value you get from them.

Data Driven Tests also allows you to scale up your test cases easily by checking tens of scenarios at once.

Watch the webinar to learn:

- How to create mabl tests that can be easily data driven in the future
- How to organize and control your mabl tests' data 
- How to use mabl data tables to drive your tests 
- How to enable mabl tests to pass values to sequential journeys

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Additional Resources:

Demo site used in the webinar 
https://storage.googleapis.com/dpaul.site/DataDrivenDemo.html

Damon Paul has brown hair and is wearing a black shirt. They are a Solutions Architect at mabl.

 

ABOUT YOUR HOST

Damon Paul is a Solutions Architect at mabl who loves nothing more than to empower humans with technology and knowledge. With experience as both a Manual QA Specialist and QA Automation Engineer, Damon is great at quickly understanding a team's quality testing needs and then guiding them towards the testing practices that work best for them.