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In today’s world where ‘data is the new oil’ (as said by Clive Humby), not giving proper attention to data-driven testing is not justified. If you have an application that needs data input in some form then it will require data-driven testing.
Additionally, when during testing your application – there are testing scenarios that require multiple permutations/combinations of input data in your application, then you might have to think of using a test automation tool for automating them.
The most effective method of testing an API program involves creating multi-step integration tests that validate common API consumer flows. API endpoints are meant to work together, so it follows that test data coming from one API that feeds another API should not be fixed or pre-built. This is very important because the less you rely on fixed data, the more unpredictable and therefore thorough the testing path will be.
Moreover, API mutation operations may have side effects that cannot be evaluated by simply validating the same endpoint. Side effects propagate throughout the system, and their efficacy can only be validated by querying other endpoints and comparing the results.
According to Guru 99, "Data-driven testing is a test automation framework which stores test data for applications in a table or spreadsheet format. This helps automation testers to have a single test script which can execute tests for all the test data in the Excel file."
The input data for testing can be stored in single or multiple data sources like XLS, XLSX, XML or in JSON files. Here we will see how to manipulate data stored using JSON.