CHAPTERS
OVERVIEW
The Data driven testing methodology involves running a sequence of steps repeatedly against different input values retrieved from the corresponding data source. It is widely used for verifying the efficiency and behavior of automated tests when dealing with a wide range of inputs.
The number of tests you run to ensure your code functions appropriately grows along with your software. Your tests could quickly increase with increased complexity, making them difficult to interpret and keep up with. Eventually, you might give up, reducing your testing and paving the way for defective code.
You can execute the same test case using various inputs when using Data driven testing, which increases the coverage of a single test. Data driven testing enables the opportunity to combine positive and negative test cases into a single test, enhancing test coverage.
Data loaded and used to enhance your automated test cases is known as Data driven testing (DDT), which is different from your functional tests. You can run the same test case with as many alternative inputs as you wish to acquire more coverage from a single test. This might be an XML file, a MySQL database, an Excel document, etc.
Testers can enter a single test script that can run tests for all test data from a table and anticipate the test outcome in the same table. It is also known as parameterized testing or table-driven testing.
A development team can save time and money by using Data driven testing since it eliminates the need to manually test each piece of data and automates the testing process with testing software. You can reuse the test case as often as you like in other situations by altering its parameters.
Four significant operations are seen in this process:
The usage of frameworks in DDT enables us to quickly retrieve previously existing code rather than build it from scratch. You don't need to be a skilled programmer to use the software, whether to retrieve a script from a framework or quickly detect and correct mistakes in a script.
The DDT framework is an automation testing platform that enables you to validate a test case against several forms of test data using a single test script. The test script utilizes all these values as inputs to perform the tests and stores the test data for both positive and negative testing in a file. The framework thus offers reused logic that increases test coverage
We would ideally concentrate on how to input data and what to expect as the output data through a type of automated framework described above. Most importantly, how do we go about structuring this data? This is because the agenda is based on test data in an automated framework.
Data driven testing framework
The above-discussed efficient architecture of the DDT framework offers several benefits. The following section goes over this.
Numerous advantages of Data driven approaches are listed below.
Data driven testing is a fantastic approach to checking for quality issues and finding product flaws. Here are a few data driven testing best practices
DDT has no apparent drawbacks or issues. The disadvantages described below are more like restrictions than actual drawbacks.
Test automation and Data driven testing differ slightly from one another. Any necessary information is included in the test itself in a standard test. On the other hand, Data driven testing involves tying your test to a data source. You can use many data sources, including basic CSV files, XML, and even fully functional databases like MySQL.
As you know, DDT covers some applications using classes of iterative data. The process is simple, and test files containing test data are used to run test scripts written in a scripting language.
The way the programming language supports the data file is at the core of this. Based on the kinds of data files it employs, here is where DDT differs slightly from other solutions.
Some of them are as follows -
In an agile test environment if a product is designed to meet the needs of its clients with the highest level of quality, it may speak for itself. As a result, many people, rather than just one, are accountable for quality!
However, this task rarely falls under the purview of a single unit inside an organization; rather, it should be a team effort. Most organizations find this problematic without efficient communication throughout, which is difficult to come by. This issue either directly or indirectly impacts the functionality of the product. Agile resolves this!
Agile is a methodology that encourages the iterative creation of effective software. The philosophy supports the readiness to adjust to that change quickly and encourages periodic inspection to determine what needs to change. Through a set of engineering best practices, it promotes teamwork in the layout of requirements and solutions.
The Waterfall and Agile approaches are not intended to be replaced by the Agile Data driven methodology. It intends to introduce a real-time, quantified perspective of engineering output to the existing Agile processes by adding a layer of data. Managers and executives can see possible barriers, spend less time preparing reports and deliver work more quickly by transitioning to the Agile Data driven methodology.
You can run tests with various data inputs in automated testing to achieve more test coverage. The fundamental principle of Data driven testing is that you run your test using a variety of input data to make sure that the application will function as intended for a range of different values. Using data as inputs to your script operations is how this strategy works. Every data set in the script serves as a test case. Therefore, the number of test cases increases as additional data sets are provided
On the other hand, the fundamental principle of Keyword driven testing is that a term represents an action. A series of keywords drive a script. Therefore, you can create a range of test scripts using the same keywords.
Below are some of the highlighted differences:
Data driven Testing (DDT) | Keyword Driven Testing (KDT) |
---|---|
Data driven testing runs tests utilizing a variety of variables, values, and stored data. | Keyword driven testing carries out tests using particular keywords. |
It requires extensive programming and technical expertise. | Even without programming experience, this test can be performed. |
It is less time-consuming. | It is more time-consuming. |
DDT offers a variety of formats for storing data, including CSV files, excel sheets, databases, tables, script arrays, etc. | KDT is limited to using Excel sheets to store its data. |
DDT can occur in many phases. | KDT may develop in two different phases. |
All test scripts are decoded using human input. | The user encodes every test script. |
In this Data driven Testing tutorial, we'll examine how to do data driven tests on our websites or online applications.
The main objective of Data driven testing is to watch how users behave in real-world situations. For the greatest user experience, test your online and mobile applications on real devices, os, and browsers.
Setting up an internal testing infrastructure is expensive and rife with operational challenges and scalability issues. Therefore, leveraging a real device cloud rather than an internal device lab for Data driven testing is preferable and more cost-effective.
Your testing needs can be met in this situation by cloud testing platforms like LambdaTest. You can test your websites and web applications with over 3000+ desktop and mobile browsers available online.
It makes the cloud environment accessible and simple, which makes software testing a controllable and scalable process. For your mobile and web testing requirements, cross browser testing platform like LambdaTest gives you access to an online device farm.
Let's look at the steps for performing Data driven testing on the LambdaTest platform in this tutorial:
LambdaTest's Real Time Testing is an excellent choice for manual live testing of your web pages. Simply create an account on the LambdaTest Registration Page if you haven't to experiment with the features.
Follow the below steps to perform manual testing:
Step 1: Log in to your LambdaTest account.
Step 2: Go to Real Time Testing → Browser Testing.
Step 3: Select a desktop or mobile device to test on after entering the website's URL. If you wish to test on a desktop, choose the RESOLUTION, OS, and VERSION of the browser. Then, click START.
A cloud-based virtual machine will launch, running a real operating system. Here you can perform Data driven testing of your web applications.
As a tester, you can change the resolution, the browser versions, or the OS version whenever you like throughout the test. Depending on your choice, your environment session will automatically change.
You can subscribe to the LambdaTest YouTube Channel and stay updated with the latest tutorials around Selenium testing, Cypress E2E testing, CI/CD, and more.
Follow the below steps to perform automation testing:
Step 1: Sign up on the LambdaTest platform. You can sign up for free if you've never used the platform before.
Step 2: Select Automation → Builds tab from the left menu.
Step 3: If Java is selected as the language, you must set up the project and the OS/Browser on the following page. You can execute your test case after setting up the required data.
Now that you know the fundamentals behind automated testing, you can explore the LambdaTest platform for performing data driven Testing.
Here is a list of best practices to remember to make data driven testing as effective as it can be:
Testing is crucial to producing high-quality apps. The most interesting testing has always been Data driven because there is no limit to your creativity and knowledge. Data driven testing from a next-generation QA and independent software testing services provider should be used by businesses to speed up the deployment of high-quality software and create a great user experience.
The most crucial thing to remember from the information presented above is to learn how to make the most of the advantages of Data driven testing and use it to enhance both the quality of the test process as a whole and the end product.
A software testing technique called 'Data driven testing' stores test data in table or spreadsheet form. Testers can input a single test script that can run tests for all test data from a table and anticipate the test output in the same table when using Data driven testing.
Data driven testing pulls input data from xls, csv, and xml files as data sources. Through the use of automated test scripts, the input data is entered into the web application. It contrasts the actual outcomes with what was anticipated.
The term 'Data Driven Testing' (DDT) refers to an approach to the architecture of automated tests (unit, integration, and most frequently backend testing), where the test is able to accept a set of inputs and an expected result or expected state with which it must compare the actual result received after the inputs run.
Data-driven testing in Selenium is a way to run tests using different sets of data. Instead of writing separate code for each test case, you can store the test data in external files like Excel or CSV. This allows you to reuse the test code and easily test multiple scenarios without rewriting the entire test case.
Data-driven testing is when you use data from external sources like files or databases to run tests with different sets of input values. For example, instead of using fixed values for testing a login feature, you can read usernames and passwords from a file to test different combinations. It makes tests easier to modify and maintain.
Data-driven testing is useful when you want to repeat the same test steps with different data. It is especially beneficial for testing application logic and functionality that require testing with multiple data sets or variations.
In data-driven testing, test scripts are designed to read test data and expected output from data files instead of using fixed values. This allows testers to easily test the application with different inputs and verify how it handles them. The data files can be in various formats like Excel, CSV, or databases.
Data-driven testing in manual testing is a technique where test cases are designed to use external data sources, such as spreadsheets or databases, to drive the test execution. It allows testers to easily modify test inputs and expected outcomes without changing the test case structure.
Yes, TestNG is a data-driven testing framework. It provides the DataProviders feature, which allows you to supply different values to a test case during a single execution. This enables running a single test case with multiple sets of data.
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