Data-driven testing approach in test automation
Automate software testing and verify the functionality of an application in a minimum time with a data-driven testing approach. You add input value or data to design and execute a test case. However, manually entering data into a test case can be time-consuming and full of errors.
A simple approach is data-driven testing, where you create a data repository to store test data and map it to your test case as required. With data repositories, you create a test case once and execute it using multiple datasets. You can also make changes in the datasets without affecting the test case.
Let’s take an example of testing the login functionality of a University portal by using password data of different complexities. We can store this data in repositories or excel sheets and fetch the data to test varied complexities for signing in. These complexities may include capital letters, lowercase letters, numbers, etc. The data repositories enable you to run your test cases under numerous scenarios using large datasets, thus making the test cases reliable.
Data-driven testing with Opkey
Opkey is the test automation tool that supports data-driven testing and has built-in data repositories. There are two types of data repositories in Opkey- Global data repository and Local data repository. You can reuse data from the global data repository to iterate different test cases and a local data repository for a specific test case. You can also use data stored in external databases like excel or CSV files.
Opkey also has an ‘Auto data generation’ feature to generate random data while running a test case. This feature is helpful when you do not have existing datasets for your test cases.
Benefits of data-driven testing in test automation:
Lowers test maintenance time - You can use data repositories to iterate your test cases and save time as you create a test case only once and execute it using several datasets at any given time.
Improves test coverage- You can execute a single test case using different data sets. Using data from the repositories, you get better test coverage, as you can test all possible scenarios without making any changes to the test cases.
Reduces errors and duplication- You can store large amounts of data in the repositories and map the data to your test case as required. A Data repository minimizes human error and prevents duplicate data entry in a test case, as you need not enter data manually.
