Making Test Automation efficient with Data-driven Testing

Data-driven testing is a technique in which the test data set or input and expected output values are read from data files instead of using the same hard-coded values each time the test runs. It is a common automation testing practice to parameterize tests with different input values. 

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Imagine this scenario: You are a software tester who has just been assigned to test an online banking system for the first time. The application is so large that it takes hours to write test scripts and run them. Yet, no matter how many times you run your test scripts, you can’t seem to find any bugs.

You’re not alone. Software testers often struggle with creating test data that can reveal bugs during the testing stage. Unfortunately, this leads to releasing buggy applications, resulting in loss of reputation, revenue, and customer trust.

Test automation helps alleviate these problems by reducing execution time, ensuring consistency, and improving the detection accuracy of bugs within the software application. However, most test automation tools only offer a record and playback interface that enables testers to create automated test scripts in a short amount of time. While this does save time in the short term, it results in applications being tested with limited data sets repeatedly. This is where data-driven testing comes into play. Using data-driven testing methodologies from the start lets you ensure that your software applications are tested with multiple input values for each test case to reveal more defects than with any other software testing methodology.

Data-driven testing is usually implemented when a large set of test data needs to be executed with only slight variations in the input values for each set of tests. This approach makes it easier for developers or testers to create and maintain automated tests by adding more test cases on top of existing ones without writing additional codes.

Data-driven testing is also a great way to do automation regression testing. We can create test cases that cover all scenarios in a large set of tests and automate them once. From then on, we can use this same set of data-driven tests every time we need to run an automated regression test. Then, the only thing we need to do is update the data.

Data-driven testing can be implemented in two ways:

Test case level data-driven testing

In this approach, a single automated test method is responsible for running all iterations of the same test case with different input parameters. This means one automation test script carries out all iterations of one test case.

Test suite level data-driven testing 

In this approach, each automated test method validates one specific functionality in the application under test and calls other methods to retrieve input parameters and validation points needed to execute the expected results.

Data-driven testing is a popular and powerful way of performing automation testing. It gives you more flexibility, control, and reusability than keyword-driven testing. It allows you to manage test data outside the test script. By storing your test data in a database or spreadsheet, you can easily update it without changing your tests or scripts. Because each test step is independent of the others, you can run them in any order, and as many times as you need to; this allows you to produce more comprehensive tests with less effort. This method also allows you to use the same script to run multiple sets of data through the same process without duplication of effort.

The advantages of the data-driven approach are:

Data-driven testing may sound very challenging and confusing for test automation. However, it is not a tedious task if approached with a good no-code automation testing platform. In addition, there are numerous benefits of using no-code automation testing tools like ACCELQ for data-driven testing, which will allow software testers to focus on other test automation initiatives.

Some of the significant benefits of using ACCELQ for data-driven testing are:

Data-Driven Testing offers a systematic way of managing test cases and test data. It also provides certain other advantages such as easy generation of test reports and management of test data. In addition, Data-Driven Testing helps automated tests run rapidly over an application with different input data and provides extensive coverage to ensure the performance of an application.