There are several methodologies available for implementation in software testing. However, not all require the same effort to create and maintain these tests. If you need to run the same tests, but with different parameter values, then you can easily do this through Data-driven testing (DDT).
What is Data-Driven Testing (DDT)?
Data-driven testing is a software testing methodology that uses a table of conditions directly as test inputs and verifiable outputs, and in which the test environment settings and control are not hard-coded.
This means that the test criteria – the input and result data values – are stored in one or more data sources, such as CSV files, Excel files, datapools, etc. Therefore, data-driven tests read data from these databases instead of hard-coded values. In other words, when using a Data-Driven Testing methodology, we create test scripts to be executed together with their related data sets in a framework. By doing so, we provide a re-usable test logic that improves test coverage and reduces maintenance.
Think of it this way, a framework where you only use one test but with an array of data.
What are the benefits of Data-Driven Testing?
Even though not all tests can be automated, using an automated technique such as Data-driven testing comes in handy when there are a number of data sets that you have to run the same tests on.
Creating a different test for each data set values, especially hard-coded values, is not just time-consuming but also rather difficult to modify and maintain. But through Data-driven testing you keep the data separate from functional tests, which allows you to execute the same test script for different combinations. By doing this you can generate test scripts with less code, since all the information like inputs, outputs and the expected result is already documented. By doing this it is possible to improve test coverage and reduce unnecessary duplication of test scripts. This frees up time so that testers can employ a more exploratory approach and flexibility in application maintenance.
Data-Driven Testing with LEAPWORK
With LEAPWORK you can work with Data-driven testing using various input sources. It is possible to drive automation from Excel data, databases, various web services and DOS command lines. By separating data from functionality when automating software tests, you can reuse the automated flow, and just switch out the input. This can be useful when running the same tests often but using new or updated data.
Read more Data-Driven Testing in LEAPWORK
Thanks to its modular type of design, Data-driven testing in LEAPWORK is easy to navigate in. By making use of Data-driven testing, you can reduce risk and shorten timelines while at the same time making it easy for your team to access and share information with real-time analysis.