The LEAP

Automation insights and productivity tips from LEAPWORK.

All Posts

A Short Introduction to Data-Driven Testing

There are several methodologies available for implementation in software testing. However, not all require the same effort for test creation and maintenance. If you need to run the same tests, but with different parameter values, then you can 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.

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.

Put differently, data-driven testing is 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 difficult to modify and maintain.

Through data-driven testing, on the other hand, 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 is already documented. By doing this, it is possible to improve test coverage and reduce unnecessary duplication of test scripts.

As a result, testers' can spend their time where it is more valuable and employ a more exploratory approach while increasing flexibility in application maintenance.

Data-driven testing with LEAPWORK

With LEAPWORK you can work with data-driven testing using various input sources from, for example, Excel, 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 with new or updated data. 

Watch the video below to see an example of data-driven automation with LEAPWORK.

 

 

 

To learn more about easy data-driven automation using a no-code automation tool, download our whitepaper: Test Automation: The Codeless Answer.

New call-to-action

Lucia Cavero-Baptista
Lucia Cavero-Baptista
Content Marketing Manager

Related Posts

How to Automate Mobile Web Testing with Codeless Selenium

With brick and mortar stores closed during an on-going pandemic, websites, especially e-commerce websites, have to focus more than ever on creating quality customer experiences online. This has created a need for faster testing and new website functionality.

What is Mobile Web Testing and Why Should It Be Automated?

Websites and web applications are a huge part of how businesses acquire customers. Just one poor customer experience can sway their purchasing decision, especially in e-commerce.  Users who have a negative experience on a mobile website are 62 percent less likely to purchase from that business in the future. - Think with Google. 

Streamlining System Upgrades in ServiceNow with Automated Testing

For many enterprise businesses, ServiceNow is an operational backbone. But twice a year, panic unfolds. ServiceNow release two major mandatory upgrades requiring extensive testing. And more often than not, functional and regression testing gets postponed or left behind.  When these tests are postponed or skipped, it leaves businesses open to risk. In these key moments, system administrators and developers face pressure to complete functional and regression testing at speed.