What is Data Driven Testing? Learn to create Framework
What is Data Driven Testing?
Data-driven is a test automation framework which stores test data in a table or spread spreadsheet format. This allows automation engineers to have a single test script which can execute tests for all the test data in the table.
In this framework, input values are read from data files and are stored into a variable in test scripts. Ddt (Data Driven testing) enables building both positive and negative test cases into a single test.
In Data-driven test automation framework, input data can be stored in single or multiple data sources like xls, XML, csv, and databases.
In this tutorial, you will learn
- What is Data Driven Testing?
- Why Data Driven Testing?
- How to create a Data Driven Automation Framework
- Best practices of Data Driven testing:
- Advantages of Data-Driven testing
- Disadvantages of Data Driven testing:
Why Data Driven Testing?
Frequently we have multiple data sets which we need to run the same tests on. To create an individual test for each data set is a lengthy and time-consuming process.
Data Driven Testing framework resolves this problem by keeping the data searate from Functional tests. The same test script can execute for different combinations of input test data and generate test results.
Example:
For example, we want to test the login system with multiple input fields with 1000 different data sets.
To test this, you can take following different approaches:
Approach 1) Create 1000 scripts one for each dataset and runs each test separately one by one.
Approach 2) Manually change the value in the test script and run it several times.
Approach 3) Import the data from the excel sheet. Fetch test data from excel rows one by one and execute the script.
In the given three scenarios first two are laborious and time-consuming. Therefore, it is ideal to follow the third approach.
Thus, the third approach is nothing but a Data-Driven framework.
How to create a Data Driven Automation Framework
Consider you want to Test Login functionality of an application.
Step 1) Identify the Test Cases
- Input Correct username and password – Login Success
- Input incorrect username and correct password – Login Failure
- Input correct username and incorrect password - Login Failure
Step 2) Create detailed est Steps for above 3 Test Cases
Test Case# | Description | Test Steps | Test Data | Expected Results |
---|---|---|---|---|
1 | Check Login for valid credentials |
|
Username: valid password: valid | Login Success |
2 | Check Login for invalid credentials |
|
Username: invalid password: valid | Login Fail |
3 | Check Login for invalid credentials |
|
Username: valid password: invalid | Login Fail |
Step 3) Create Test Script
If you observe the Test Steps Remain common through the 3 Test Steps. You need to create a Test Script to execute these steps
// This is Pseudo Code // Test Step 1: Launch Application
driver.get("URL of the Appliation"); // Test Step 2: Enter Password
txtbox_username.sendKeys("valid"); // Test Step 3: Enter Password
txtbox_password.sendKeys("invalid"); // Test Step 4: Check Results
If (Next Screen) print success else Fail
Step 4) Create an excel/csv with the Input Test Data
Step 5) Step Modify the Scrip to Loop over Input Test Data. The input commands should also be parameterized
// This is Pseudo Code
// Loop 3 Times
for (i = 0; i & lt; = 3; i++) {
// Read data from Excel and store into variables
int input_1 = ReadExcel(i, 0);
int input_2 = ReadExcel(i, 1); // Test Step 1: Launch Application
driver.get("URL of the Application"); // Test Step 2: Enter Password
txtbox_username.sendKeys(input_1);
// Test Step 3: Enter Password txtbox_password.sendKeys(input_2);
// Test Step 4: Check Results
If(Next Screen) print success
else Fail
}
Above are just 3 test cases. The test script can be used to loop over following test cases just by appending test data values to Excel
- Input incorrect username and incorrect password – Login Fail
- Input correct username and password blank – Login Fail
- Input blank username and blank password– Login Fail
And so on
Best practices of Data Driven testing:
Below given are Best testing practices for Data-Driven testing:
- It is ideal to use realistic information during the data-driven testing process
- Test flow navigation should be coded inside the test script
- Drive virtual APIs with meaningful data
- Use Data to Drive Dynamic Assertions
- Test positive as well as negative outcomes
- Repurpose Data Driven Functional Tests for Security and Performance
Advantages of Data-Driven testing
Data-Driven offer many advantages some of them are:
- Allows to test application with multiple sets of data values during Regression testing
- Test data and verification data can be organized in just one file, and it is separate from the test case logic.
- Base on the tool, it is possible to have the test scripts in a single repository. This makes the texts easy to understand, maintain and manage.
- Actions and Functions can be reused in different tests.
- Some tools generate test data automatically. This is useful when large volumes of random test data are necessary, which helps to save the time.
- Data-driven testing can perform any phase of the development. A data-driven test cares are generally merged in the single process. However, it can be used in multiple test cases.
- Allows developers and testers to have clear separation for the logic of their test cases/scripts from the test data.
- The same test cases can be executed several times which helps to reduce test case and scripts.
- Any changes in the test script do not effect the test data
Disadvantages of Data Driven testing:
Some Drawbacks of Data Driven Automation Testing method are:
- Quality of the test is depended on the automation skills of the Implementing team
- Data validation is a time-consuming task when testing large amount of data.
- Maintenance is a big issue as large amount of coding needed for Data-Driven testing.
- High-level technical skills are required. A tester may have to learn an entirely new scripting language.
- There will be more documentation. Mostly related to scripts management tests infrastructure and testing results.
- A text editor like Notepad is required to create and maintain data files.
Conclusion:
- Data-driven is a test automation framework which stores test data in a table or spread spreadsheet format.
- In Data-driven test automation framework, input data can be stored in single or multiple data sources like xls, XML, csv, and databases.
- To create an individual test for each data set is a lengthy and time-consuming process. Data Driven Testing framework resolves this issue by keeping the data separate from Functional tests.
- In Data Driven Testing, it is an ideal option to use realistic information
- It allows testing application with multiple sets of data values during Regression testing
- Drawback of this method is that it is depended on the automation skills of the Implementing team
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