An Ultimate Guide To Perform Data-driven Testing

Data-driven testing is the systematic method of using multiple data sets to perform effective test cases. In simple terms, it is the approach that lets one execute repetitive test cases on multiple data sets to save a lot of time and resources.

We have previously published a detailed article on what data-driven testing is along with mentioning a lot of information about this crucial form of testing. So, we highly recommend you to check out that article to acknowledge yourself about that unavoidable part of your test suite. Here we are going to discuss how you can perform it and what special points you need to take care of.

How To Implement Data-driven Testing

You may have gathered immense knowledge about different types of software tests as well as about general test automation. So, it’s time for you to know that data-driven tests are a bit different from standard test automation.

Standard tests need you to include required test data in the test itself, and on the other hand, data-driven tests allow you to connect your test to a data source. Also, the best part about data-driven testing is that it enables you to use different data sources ranging from simple CSV files to XML and even full-featured databases like MySQL.

Now, let’s check out the necessary steps to implement data-driven testing.

Choose Your Data Source

First of all, you have to choose your data source. Now, for simple scenarios, a simple structured text file or CSV file can be used. This is a great choice for the tests like checking your login system with a set of username + password tuples.

As you move toward more complex tests, you will need to add more information to the test data, and for that, you will need high-level data formats like XML files. While you are executing large automated test suites, proper relational databases like MySQL should be used. This is a highly useful practice while orchestrating your tests.

Connect The Data Source

Now, as you have selected the data source, it’s time for linking it with your test. This task can be performed with different levels of ease based on the testing framework you are using. For example, linking the data source with the test is easier in Selenium. If you are writing a Selenium test in Python, a simple step can be included to import your test data from a CSV file. Then you should create a loop that will run through each entry in the data source.

As you previously saw, XML files are used in more complex scenarios. In that case, you have to import the data file into your script and parse it to extract the data and the expected result. However, remember that using a database source will make all this much harder.

Analyze The Result

You must already know how important it is to analyze the results to verify their correctness. But, sometimes, this analysis can be difficult as instead of only a binary choice, many possible outcomes can occur.

A smart way for the analysis is to use a case statement to compare the actual outcome with the expected outcome. And, for higher variability in the result, using XML will be a good choice as it can provide a better description of the expected outcome.

Whatever choice you make for the result analysis process, it should be based on the objective of achieving better efficiency and the automation engineers should use immense skill and experience for it.

Why Should You Perform Data-driven Testing?

Questioning being the foundation of science, you must have already doubted why you should perform data-driven tests that initially seem to be effort-taking. Well, there are strong reasons to support performing this crucial form of software testing.

It is a pretty common scenario where testers have multiple data sets for a single test and it is never an efficient approach to create individual tests for each data set. Data-driven testing exempts you from that insanely time-consuming practice of creating individual test scripts for multiple data sets.

With data-driven testing, you can easily keep data separate from test scripts and can execute the same test scripts for different combinations of input test data, and efficiently generate useful test results.


Let’s understand the need for data-driven testing with an example of testing the login system with multiple input fields with 1000 different data sets.

This test can be performed using the following three approaches. Check them out carefully to figure out the most efficient one.

1st Approach: You have to create 1000 scripts for each data set and separately run each test one by one.

2nd Approach: You can manually change the value in the test script and run it multiple times.

3rd Approach: You can import the data from the excel sheet, fetch test data from excel rows one by one, and execute the script.

Now, you can clearly see that out of these three scenarios, the first two need immense effort and time while the third one can complete the task more efficiently in much less time.

The third approach is using a data-driven framework that makes the best use of the data sets.

How To Create A Data-driven Automation Framework

Again taking the example of testing the login functionality on an application to understand it from the perspective of data-driven testing.

Step 1: Identify The Test Cases

Primarily, you have to identify the test cases. Here the test cases will look like the following.

  • Input correct username and password - Login Success
  • Input incorrect username and correct password - Login Failure
  • Input correct username and incorrect password - Login Failure

Also, the correctness and incorrectness of the username and password depend on various factors.

Step 2: Create Detailed Test Steps

Now, let’s see what the steps will be for each of the above-mentioned test cases.

Test Case Number


Test Steps

Test Data Validation

Expected Results


Test login progress for valid credentials

  1. Launch the application.

  2. Enter the username and password.

  3. Click “Login”.

  4. Check the results.

Username: valid

Password: valid

Login Success


Test login progress for invalid credentials

  1. Launch the application.

  2. Enter the username and password.

  3. Click “Login”.

  4. Check the results.

Username: invalid

Password: valid

Login Failure


Test login progress for invalid credentials

  1. Launch the application.

  2. Enter the username and password.

  3. Click “Login”.

  4. Check the results.

Username: valid

Password: invalid

Login Failure

Step 3: Create Test Scripts

Here as you can see that the test steps remained common through the 3 test steps, you should now create a test script that will perform the task of executing these steps.

// This is Pseudo Code

// Test Step 1: Launch Application
driver.get("URL of the Application"); 

// Test Step 2: Enter Username

// Test Step 3: Enter Password

// Test Step 4: Check Results
If (Next Screen) print success else Fail

Step 4: Create an Excel/CSV File

Now, you have to create an excel/CSV file containing the input data in one place.









Step 5: Modify The Steps In The Script

The script needs to loop over Input Test Data. For that, you need to modify the steps in the script. Also, focus on parameterizing the input commands.

// 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 Username
    // Test Step 3: Enter Password

    // Test Step 4: Check Results
    If(Next Screen) print success
    else Fail

The piece of code written above deals with only 3 test cases. To loop over the following test cases by appending test data values to Excel, this test script can really be effective.

  • Input incorrect username and incorrect password - Login Fail
  • Input correct username and leave password blank - Login Fail
  • Keep both usernames and password blank - Login Fail

Many more test cases can also be created here.

Source of example:

Benefits of Data-driven Testing

If you look at traditional testing methods and data-driven testing side-by-side, you will surely figure out the following benefits.

  • If you have to create a unique test for each data set value, especially hard-coded values, you will end up wasting a huge time & resources and it will also become insanely difficult to maintain.
    On the other hand, data-driven testing completely exempts you from such a scenario.
  • Data-driven tests allow you to keep the data separate from functional tests, and as a result, you become capable of executing the same test script for different combinations.
  • As data-driven testing needs all the information to be documented earlier, the test scripts can be generated with less code. And, as a consequence of that, less duplication of test scripts causes better test coverage.
  • The ultimate result of all these benefits is that data-driven testing enables the testers to spend more time and resources in more valuable places and the flexibility in application maintenance also gets improved.

Best Practices of Data-driven Testing

Here we have jotted down some best practices for data-driven testing.

  • It is a good idea to use realistic information during the data-driven testing process.
  • You should consider driving virtual APIs with meaningful data.
  • Negative outcomes should also be tested besides positive ones.
  • It is a better practice to code test flow navigation inside the test script.
  • Data should be used for driving dynamic assertions.
  • You should consider repurposing data-driven functional tests for security and performance.


Data-driven testing is indeed a highly important testing strategy that solves various testing issues and results in saving a lot of time and resources. After we provided you with a detailed overview of this crucial form of testing in our previous article, here we have discussed an informative guide for performing these tests. So, we must recommend you carefully go through this article to acknowledge yourself more.

Also, you must already know how test automation tools make it so easy for you to not worry about managing the entire testing process by yourself. Then you should also know that Preflight is an extremely powerful AI-based test automation tool that lets you create, run, and manage complex tests within seconds. So, don’t wait more to book a demo.

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