What Is Data-Driven Testing? A Detailed Overview by Preflight

Data is the foundation of the efficient work performed by technical products. Whichever apps you use, they perform all their operations on huge sets of data collected through different sources. And, those huge chunks of data are the reason why apps provide you with the best results.

You must also know that artificial intelligence, one of the most important aspects of the future of the tech world, works mainly based on extremely high usage of data. The primary base of AI’s work is letting the computer know about numerous possible conditions using huge data sets so that it can analyze different conditions and make decisions accordingly.

However, here we are going to focus on data-driven testing, which is a highly efficient testing approach that lets you perform multiple tests by using a single test script on multiple data sets. So, let’s move on with the article so that you get a clearer idea.

What Is Data-driven Testing?

Data-driven testing is a software testing technique where a lot of test data is provided in a table or spreadsheet or any other format like an Excel document, MySQL database, an XML file, etc., and a single test script is used to perform the test using those test data. In this approach, the test output is also expected to be received in the same table.

This method can save you a lot of time by exempting you from manually testing each piece of data. And, on top of that, you can use advanced test automation tools like Preflight to automate all your tests so that you can sit back and relax while your tests will automatically get executed and you will receive detailed reports.

Data-driven testing also helps you to set up positive and negative test cases in a single test. That means a single test will analyze whether your input test data satisfies the specified boundaries. That means if the input data is in the correct format, it will turn out to be a positive test case, and if it does not satisfy its boundaries or is in an incorrect format, it will become a negative test case. This is a very important phenomenon for creating useful test cases.

When Should You Perform Data-driven Testing?

From the description above, you can easily understand that data-driven testing is something that is useful for scenarios where the same test steps need to be performed repeatedly with different data. Usually, those tests are for checking the correctness of application logic. Here we have jotted down a few common logics that are tested with data-driven testing.

Shopping Cart Logic

This is probably the most widely used logic nowadays. With the immense growth in eCommerce, it has become a huge necessity for the respective eCommerce websites to perform efficiently. That’s why you must also care about having properly working logic in the shopping carts.

Shopping carts have to deal with numerous items with huge valuations. In such a case, if the cart fails to perform proper operations, it will cost the eCommerce service provider huge losses. Hence, these become ideal use cases for data-driven tests.

eCommerce websites allow you to add various combinations of items from various categories. They also come up with special offers like “Buy 1 Get 1 Free”, and coupon codes are something that comes in various varieties and huge availability. Hence, each of these situations is a potential use case for performing data-driven tests on the shopping cart logic.

Localization Checks

The internet has provided every product with the opportunity to reach out to the whole world. That means most of the popular websites are effectively usable all over the world. As a result of that global usability, those websites have to comply with all languages and cultural norms of multiple regions, and that creates a crucial use case for data-driven tests.

For example, with different guidelines of different regions, the format of writing dates varies throughout the world. Also, the formats of writing numbers, currencies, addresses, etc. are significantly different in different regions of the world. So, to ensure the best performance of the app across the world, you must make sure to perform rigorous data-driven tests on it.

User Management

Every app or website has a certain flow of steps to turn a visitor into a potential user. For that, each of the channelized steps must perform as it should along with guiding the person toward the next step. Also, there are scenarios where the app has to validate the correctness of the users’ input data. That means if the user enters valid data, only then the app should process toward the next step. Else, it should warn the user about the invalid input data.

Then comes the modification capabilities provided to the users. If any data is modified, all other data that is dependent on the modified data should automatically get updated. And, another possible situation to perform a data-driven test is checking the permissions that a user has. For example, while being able to perform some operations, a user might be restricted to perform some actions that he/she doesn’t have permission to. Hence, make sure to have effectively performing data-driven test cases for such situations.

Is Data-driven Testing The Right Choice For You?

You can decide whether you should perform data-driven testing or not based on the following guidelines/considerations.

  • Are you repeating the same steps multiple times in different tests? Usually, when you have many user flows within your UI, you may have to face this scenario.
  • Do you have requirements for testing multiple variations of the same data? Typically, while testing application logic, you may need to have the capability of varying the input data.
  • Are there multiple tests running concurrently/parallelly on the same system? In such cases, you should make sure that different data is used for each test.
  • Are there paths that are either obvious happy or sad that you are trying to test? For example, if one set of data triggers an error message, and a different set doesn’t, that may be a good data-driven test case.
  • Is different data generating different outcomes for a test? For example, login flows will either allow the user to log in or not.

If your response is yes to most of the above-mentioned questions, you have potential requirements for data-driven tests.

When Should You Avoid Data-driven Testing?

Well, though data-driven testing is a highly advantageous practice, there are some scenarios where performing it does not turn out to be a good decision. Let’s see some of such scenarios.

Less Frequent Tests

Although you know that data-driven testing is a great choice for the test cases that you have to repeat multiple times, there are tests that do not have that much frequency. So, if you are repeating a few tests occasionally, there is no point in wasting a lot of time and money on setting up data-driven testing for them.

Similarly, if you have the requirement for using a single set of data and occasionally varying it, then you can surely avoid performing data-driven testing there.

Highly Complex Results

One prime condition of data-driven testing is that you are capable of specifying the expected outcome for each set of test data. Now, in some scenarios, the outcome varies tremendously, making it difficult to specify the expected outcomes. This can happen when different outcomes bring up different page views.

However, the point is that such insane complexity in the test results should guide you to avoid data-driven testing.

Besides these large reasons, there may be numerous more reasons to avoid data-driven testing. For example, if your testing team does not have the necessary skills to perform such an important form of testing, or if you are just beginning to test a new product and do not know whether performing data-driven tests here will be a good idea or not, or you are not noticing significant benefits of data-driven tests, you should not perform those tests there. There may be numerous reasons for not performing data-driven tests, and being responsible for a smooth testing experience for your product, you must make the assessments carefully.

Advantages of Data-driven Testing

Among the many advantages of data-driven testing, the most important ones are -

  • It allows application testing with multiple sets of data values during regression testing.
  • If your tool allows, data-driven testing makes it possible to have all the test scripts in a single repository. As a result, the texts become easy to understand, maintain, and manage.
  • There are some tools that can automatically generate test data. When tests need large volumes of random test data, this feature becomes highly useful in saving time.
  • It enables you to organize test data and verification data in just one file, and you can also keep it separate from the test case logic.
  • You can reuse the actions and functions in different tests.
  • As previously mentioned, it allows developers and testers to have a clear separation of the logic of their test cases/scripts from the test data.
  • It makes sure that any change in the test script does not affect the test data.
  • You can perform data-driven testing at any phase of the development cycle. Merging data-driven test cases in a single process is a common practice but it can easily be used in multiple test cases.
  • You can execute the same test cases several times because it can help reduce test cases and scripts.

Disadvantages of Data-driven Testing

Besides amazing advantages, data-driven testing also has some disadvantages that are -

  • The quality of the test depends on the automation skills of the implementing team.
  • As data-driven testing involves large amounts of coding, it becomes difficult to maintain them.
  • It involves a high volume of documentation that is mostly related to testing infrastructure, script management, and test results.
  • While testing large amounts of data, it takes an insane amount of time to validate the data.
  • It needs the testers to have high-level technical skills. For example, testers may often have to learn a new programming language.
  • You will require a text editor (e.g. notepad) to create and maintain data files.


This article tells you a lot about data-driven testing so that you can get your ideas about it. If you carefully go through every point in this article, you can easily figure out the following conclusions -

  • Data-driven testing works based on the approach of storing test data in a table or spreadsheet format.
  • In this form of testing, input data can be provided from single or multiple data sources such as XML files, Xls, CSV, and databases.
  • The main objective of data-driven testing is to get rid of the lengthy and time-consuming process of creating an individual test for each data set. To resolve that issue, data-driven tests keep the data separate from functional tests.
  • It is always a good idea to use realistic information in data-driven testing.
  • Data-driven tests enable you to test applications with multiple sets of data during regression testing.
  • This approach comes with a significant drawback that it depends on the automation skills of the implementing team.

You can clearly see that data-driven testing is overall a highly beneficial form of software testing but you must know that no form of testing can be favorably effective without efficiently automating them using advanced test automation tools like Preflight. This simple yet highly powerful browser extension lets anyone without any coding knowledge create, run, and manage complex test cases within seconds. To experience such ease in testing, all you need to do is get started with us.

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