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.
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.
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.
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.
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.
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.
Again taking the example of testing the login functionality on an application to understand it from the perspective of data-driven testing.
Primarily, you have to identify the test cases. Here the test cases will look like the following.
Also, the correctness and incorrectness of the username and password depend on various factors.
Now, let’s see what the steps will be for each of the above-mentioned test cases.
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.
Now, you have to create an excel/CSV file containing the input data in one place.
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.
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.
Many more test cases can also be created here.
Source of example: https://www.guru99.com/data-driven-testing.html#4
If you look at traditional testing methods and data-driven testing side-by-side, you will surely figure out the following benefits.
Here we have jotted down some best practices for data-driven testing.
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.