We sometimes have to perform the same experiments on a variety of data sets. It’s also time-consuming and costly to write a new test for each data set’s values. Data-Driven testing solves this problem by maintaining data separate from test cases and loading it only when the automation tests need to be extended.
So the question that arises here is, “How Do You Write Data-Driven Test Cases?”
A data-driven test case can be thought of as a prototype for a group of test cases. Data-driven test cases are written to run the same test case several times, one with each data combination contained in every single data source. The data is transferred as a reference to the test case.
“There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days.”Eric Schmidt, Executive Chairman of Google.
What Is Test Data?
In a nutshell, test data is information that is needed to properly execute test cases and validate the predicted output in any software program under test.
In a tester’s day-to-day life, test data is a widely used term. He requires some data to input when running test cases in order to get the predicted results. Huge data is often needed to load the system with data (Load testing) or to verify the application’s breakpoint (Stress testing). This information may be correct or incorrect.
We want to validate the login method with 2000 different data sets and several input fields. You can try the following methods to see if this is true:
- Create 2000 files, one for each dataset, and run each test individually.
- Adjust the value in the test script by hand and run it many times.
- Import data from an excel document. Run the script after extracting test data from excel columns one by one.
The first two of the three cases are laborious and time-consuming. As a consequence, the third strategy is the better alternative.
As a result, the third solution is simply a Data-Driven framework.
The following video sheds light on the basics of data-driven testing.
Why Is Data-Driven Testing Important?
It allows testing applications with many sets of data at a time. It also helps in keeping a whole lot of data in one file.
For example, to test mobile apps, you’ll need a variety of input data, including images in various formats, music files in both supported and incompatible formats, videos, contacts files, and multiple emails, among other things. Without this test evidence, the tester will be unable to complete the test and will not receive the required results.
Types Of Test Data
Test data can be divided into the following sets:
- The word “blank files” or “no data” applies to files that contain no data, i.e., no input to the program, and this validates that the application handles errors and catches the required exception.
- The term “valid collection of test data” refers to the application’s valid or supported files. When provided as input, these should generate the desired outcome.
- The word “invalid collection of test files” applies to any of the unsupported file formats that are used to ensure that the program manages them all correctly and alerts the user with the required error message.
- “Large test data” for load, efficiency, and quality assurance cannot be created during execution and must be planned before setting up the test environment. For instance, if a tester wants to load an application, they will need a huge number of format files that can be either generated from an automated script or the existing data.
- Data for all possible variations of boundary values were used in the test data to guarantee that all boundary conditions are met. If a text box could hold numbers 2-20, for example, enter 2 (minimum) and 20 (maximum) values. Limited values are only enough for the application to handle; if the tester goes past them, the application will fail.
The ideal test data contains all possible variations of data, ensuring that no significant flaws are overlooked.
How to write Data-Driven Test Cases?
Let’s look at a simple example of generating test data for a new customer on a web application’s “develop user page.” So there will be text boxes for the First Name, Gender, Date of birth, Email Address, Contact information, Password, and Confirm password on this screen.
To generate Test data for such an application, we must first determine which fields are required and which can be ignored. Invalid inputs could include using alphabets other than “M” and “F” in the gender section or using alphabets in the phone number field instead of numbers. More than 10 digits of a phone number could be a limit. As a result, test data will contain actual values, null values, model parameters, and blank data in the example above.
One of the sample test data that can be used as a guideline can be seen below:
|Test Case No#||Description||Test Steps||Test Data||Expected Results|
|1||Check Login for valid credentials||Launch the applicationEnter Username passwordClick OkayCheck Results||Username: valid password: valid||Login Success|
|2||Check Login for invalid credentials||Launch the applicationEnter Username passwordClick OkayCheck Results||Username: invalid password: valid||Login Fail|
|3||Check Login for invalid credentials||Launch the applicationEnter Username passwordClick OkayCheck Results||Username: valid password: invalid||Login Fail|
For more in-depth information about writing data-driven test cases, you may have a look at this video.
Data-Driven Testing Best Practices
Good practices for Data-Driven testing are described below:
- Using accurate data during the data-driven testing phase is optimal.
- The navigation of the test flow should be coded inside the test script.
- Use meaningful data to power virtual APIs.
- Make Dynamic Assertions with data.
- Examine both positive and negative effects.
- Data-driven functional tests may be repurposed for security and efficiency.
The Data-Driven Framework is a test automation system that reads values from data files and stores them in test script parameters. It encourages testers to mix true and false test cases in one test. Data can be housed in a data or several information sources, such as.xls,.xml,.csv, and databases, in a data-based environment.
Causal analysis is a research technique that can help businesses get to the root of specific behaviors or events. It’s like detective work, where you try to figure out what
Have you ever spent hours fine-tuning a machine learning model, only to find that it falls apart when faced with new data? Or maybe you’ve tried training an algorithm on
Let’s consider smartphones for a moment – have you noticed the sharp trajectory of human-like features they’re packing and how they’ve been able to do so many things on their
Data-Driven Test Cases Writing Example
You may use data-driven test cases to run the same test case several times, one with each data combination contained in a data source. The data is transferred as a parameter to the test case. A data-driven test case can be thought of as a prototype for a group of test cases. The below are some of the advantages of using data-driven test cases:
- In a test schedule, they minimize redundancy.
- It’s easier to manage scripts if you write a single test case with a set of related test cases.
- They can be reused; adding new tests just necessitates the addition of new evidence.
The primary method for generating a data-driven test case, independent of the methodology you use, is as follows:
- Make a typical evaluation case. It would be very beneficial to clearly understand what you will verify and how you will conduct the verification.
- Determine the data in the test case as well as the 4Test data types used to store it.
- Replace the hard data with variables in the test case.
- Modify the test case to provide input arguments for passing in results. Variables can be used to replace the hard coded data in the test case.
- Use one of four various tactics to call the test case and transfer in the data:
- To run the test case, you’ll need a database and the Data-Driven Process. This approach is recommended by Micro Focus for data-driven research.
- Type the data into the Run Testcase dialogue box by pressing Run > Testcase.
- In a Quality Assurance Organizer test schedule, incorporate the data as a reference to a test summary.
- If the data is stored in an external file, construct a function to read the file and execute the test case using the main() function.
Tips And Tricks To Write Data-Driven Test Case
Here are a few pointers on how to produce test data:
- Be sure the Test data files aren’t compromised at all times. This will result in incorrect performance and the absence of critical flaws.
- On a daily basis, test data can be modified. This will have a good view of what to do.
- To save time and reach deadlines, test data should be generated before test cases are conducted.
- It is a safe idea to use an automated platform to produce vast volumes of test data since manually will be more complicated and time-consuming.
- To test negative scenarios, test data should have invalid inputs.
- To build test results, the tester may seek the assistance of the developer.
- To ensure optimum test coverage, it is often the best idea to use all possible combinations of supported and incompatible formats in test results.
Data-Driven Testing Workflow
Advantages Of Data-Driven Testing
Data-driven testing has a number of benefits, including:
- During the testing process, it is possible to analyze the program for different sets of data values.
- The test data and proof data should be kept separate from the test case rational in a single file.
- The test scripts can be placed in a single directory depending on the platform. This makes the texts simple to comprehend, update, and handle.
- The same Actions and Functions could be seen in several experiments.
- Some programs produce test results on their own. This is helpful when massive amounts of random test data are required, as it saves time.
- Data-driven experimentation can take place at any stage of the production process. In most cases, data-driven test cares are combined into a single operation. It will, however, be seen in a variety of test cases.
- Enables managers and reviewers to keep the theory of their test cases/scripts apart from the evidence they’re testing.
- The same test cases can be run several times, minimizing the number of test cases and scripts.
- Any modifications to the test script have little effect on the test results.
Data-Driven Testing Drawbacks
The following are some disadvantages of the Data-Driven Automation Testing method:
- The test’s quality is determined by the Implementing team’s automation abilities.
- When checking vast amounts of data, validation is a time-consuming process.
- As a result of the vast volume of coding required for Data-Driven research, maintenance is a significant concern.
- Technical knowledge at a high level is expected. It is possible that a tester would have to master a whole new code base.
- More documents will be provided. Script maintenance, testing systems, and testing performance are the most popular topics.
- To build and manage data files, you’ll need a text editor like Notepad.
A test automation system that stores test data in a table or distributed spreadsheet format is known as data-driven. In a computer-driven test automation environment, input data may be contained in one or more data sources, such as xls, XML, csv, and databases. It takes a long time and effort to construct an independent test for each data collection. By maintaining data apart from functional experiments, the Data-Driven Testing system addresses this issue.
It’s a brilliant thing to use objective evidence in Data-Driven Research. During regression testing, it helps you to analyze an application with different sets of data values. The disadvantage of this approach is that it is dependent on the Implementing team’s automation expertise.