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Data Driven Testing in Software Testing

  • Last Updated : 29 Dec, 2021

Prerequisite: Software Testing

A Data Driven Testing is a type of software testing methodology or more exactly approach to architecture of automated tests by creating test scripts and reading data from data files. 

In this type the data files are involved basically that are Data pools, CSV files, Excel files, ADO objects, ODBC sources etc. The testing functions creates the test scripts in which the test data and the output values are read from the data storages.

Working of Data Driven Testing:  

Let’s understand working with real application scenario:

  • Suppose taking an application for login credential both user name and password are required.
  • If both the user name and password are correct then login successful and it will enter into the home page.
  • Another case is that when username is correct but password is wrong then the login action will fail i.e. showing Invalid credential and will not allow to enter into the home page.
  • Next when the username is incorrect and the password is correct then login fails.
  • Next thing the logic says that it is a control flow process for checking the conditions and functions.
  • And the test scripts are taken in the final position and an automation code is implemented for the conditions. The test scripts are working like functions and actions.

Figure 1: Working model of data driven testing

Advantages:

  • Data driven testing allows reusability of code.
  • It improves test coverage.
  • In case of regression testing the test application allows the set of data values.
  • In data driven testing mainly both the test and verification data ordered in a single file and separated from some test logic. This type of testing generates a clear cut idea and logic of the test cases from the test data for the developers and testers.
  • Changes in test script do not effect the test data as well as test process.
  • There are different tools which generate the test data automatically and a large volume of test data are taken for saving the time when necessary.
  • Less maintenance is required as well as it provides flexibility in application maintenance.
  • A number of functions and actions can be reused in many test cases present in the data driven testing.
  • It helps in reducing redundancy and unnecessary duplication of test scripts.

Disadvantages:

  • One of the biggest drawbacks is that the quality of the test depended upon the automation team skills i.e. being implemented.
  • Data driven testing requires great knowledge and expertise in scripting language.
  • When the amounts of data’s are more for validation it is taken so much of time to execute.
  • In this type maintenance plays a big issue for the code complexity and difficult of understanding the logic.
  • More documentation and high level technical skills are required .Another thing is that the tester should be learnt the entire new scripting language.
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