What is Data Driven Testing - Complete Guide

In software development life cycle, testing has an irreplaceable place. Testing helps to develop a fine-functioning app by finding and fixing bugs. Though testing plays a vital role, it also has limitations like time consumption, hectic processes, limited coverage, and possible human errors. The automation testing concept emerged to overcome these failures with manual testing. Many tools and scripts came into existence to conduct automation testing. Each test has a particular purpose. Data driven testing is based on the input data from the storage to check the different possibilities. 

This testing is a must-have process for checking software functionality to a great extent. It allows running tests for multiple cases and obtaining positive and negative software outputs. When I started using automation testing, it had many positive features but was also complicated. Later, after using it during various software tests, I found automation testing very convenient. I am writing this blog for those who need clarification on what is data driven testing and who need to learn about it.

What is Data Driven Testing?

Imagine software is built with the option to enter a mail ID. Only when valid emails are entered can the user proceed with the software. How can a tester run a test multiple times with different email addresses? Running a vast set of test data manually is merely complicated. To handle such hectic cases, data-driven testing methods can be used. Data-driven testing is a method that reads the data stored and uses scripts to find the output results. The same test can be run with different inputs using this process. 

This process helps to check the software's functionality for the set of inputs. The scripts used during this testing can be stored and reused, so the same test can be run with different inputs.

The software's positive and negative outputs must be found when performing functional test cases for various inputs. Data-driven testing can be favorable if the inputs are in an external file like a spreadsheet. This testing helps to unveil potential issues that may be unnoticed in some sets of inputs. In all the above cases, you can check the software's functionality.

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Working of Data Driven Testing

The data driven testing works in simple steps as follows,

• Import data from data sources like spreadsheets, CSV files, and other databases to run tests with many inputs.

• The test Automation scripts and the expected output conditions are set before starting the test. The expected outputs are used to compare with the results.

• After entering all details, variables enable the testing of software functions.

• After executing the test, the resulting output is compared with the expected output set during test script formation. The test continues for the different inputs in the database.

This type of testing can be used in various cases for example, 

• For testing login functionality in any software

When checking the login, use different valid and invalid credentials.

• For testing order forms of customers in e-commerce sites

Checking the confirmation with an order number, count, and product rate remains the same for different items present in the store.

• For testing the logic involved in shopping cart

Effects like adding an item or counting to a cart can be verified; this is done for products in the list.

• For testing software with multiple users

Different users can use the software, so check with existing and non-existing user credentials. This can help you check the functionality and software compatibility.

• For testing ZIP code testing. 

Some software may use the ZIP code to provide delivery, pickup, or other services. In such cases, tests are done using different Zip codes.

Types of Data Driven Testing

Data driven testing is divided based on various factors involved in the process. Here are the classifications: 

Based on the Data Source

Based on the source of the input data used for testing, the types are:

1. File-Based Data Driven Testing

Storing test data in external files like CSV or Excel and running test scripts on the software runs file-based automation testing.

Example: Importing test data from data.csv for execution.

2. Database based Data Driven Testing

When software testers fetch data from relational databases like MySQL or MongoDB using SQL queries, they use it as test inputs.

Example: Running tests with customer details stored in a database table.

3. API/Service-Driven Data-Driven Testing

Data is retrieved dynamically from APIs or web services during test execution.

Example: Fetching product prices via an API for e-commerce platform testing.

4. Embedded Data Testing

Data is hard-coded or embedded directly within the test script.

Example: Writing test cases in code with predefined input-output pairs.

5. Keyword-Driven Testing

Data-driven testing is done wherever the action keyword is linked to execution in the software. Each UI test is based on the software's operation. Keyword-driven testing is easy to understand since it does not require any critical things.

6. Negative Testing

Testers provide faulty inputs in this testing to check the software's output on incorrect inputs. This testing is conducted to identify any bugs and vulnerabilities present.

Example: The test inputs the wrong email address to verify if it is recognising capacity.

Also Read: When to Use  Automation Testing?

Data Driven Testing Tools

The list of supporting tools

1. Selenium

Selenium is a popular tool for data-driven testing. Parametric testing through TestNG and JUnit makes data-driven testing possible.

2. TestNG

Features in TestNG make data-driven testing possible. You can repeatedly test with the data in the external file without changing the code. 

3. JUnit

With parameterised test runs, install Junit supports data driven testing for software. 

4. QTP/UFT

QTP/UFT supports many tests, including regression testing, UI-based tests, and file operations. It also includes data-driven testing.

5. Ranorex

Ranorex is one of the best tools for automated data driven testing. 

Importance of Data Driven Testing

The process of implementing this testing method is essential because of the following. 

1. Reduce the test time:

Running the test with many inputs may be time-consuming. Instead, data-driven testing performs repeated tests with different inputs in the storage. By performing repeated and automated testing, data driven testing can reduce the time involved. 

2. Code Reusability:

One can store the test codes used in data-driven testing for one software and reuse them several times for various software.

3. Identification of Bugs or Vulnerabilities:

The data-driven testing with different data inputs can help to identify the bugs or vulnerabilities.

4. Minimise Human Error:

The chances of human error are high when the test is hectic or involves massive data. Automatic data-driven testing can reduce the possibility of human error in software testing. 

5. Improved Productivity:

Since data-driven testing can handle massive data testing in less time, productivity can be increased. This allows software to be delivered in less time and more effectively.

Also Read: Types of Automation Testing 

Hurdles in Implementing Data Driven Testing

Organisations may face some challenges when using data-driven testing in practice.

1. Data Quality

The test case depends on the data inputs. Proper inputs can help you run the test, get the correct results, and compare them with the expected results. If the data is inappropriate or in the correct format, it may lead to test failure. 

2. Data management

Data-driven testing is based on data inputs; different software will need different data lists. All the data used must be adequately managed for future use. Even for cross-verifying, the test output data must be managed efficiently. 

3. Test Case Quality

The test case sets the rules for testing and formulates the regularity of the input data. It should be based on the software's boundaries and limits to put the software's positive and negative results. Proper planning can reduce the coding process and the time involved in the testing. 

4. Tool Limitations

Knowledge of the tool used is mandatory before performing data-driven testing. The proper knowledge can help build a test script appropriately and set an input testing limit.

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Conclusion

The functionality of the software cannot be compromised in any situation. Data driven testing plays a vital role in checking functionality of the software. I found many advantages after using automation testing for projects. In recent times, automation testing has become popular because of its efficiency. The people in testing fields can update themselves from manual to automation testing. Guidance of a revised Automation Testing Course and certification can be helpful. Being in trends can help with securing better positions and salaries regardless. I hope this blog gave you a better understanding of data driven testing!