We often face scenarios where it becomes necessary to carry out the same tests on diverse data sets. This process can turn out to be both time-intensive and ineffective if we generate individual tests for every data set.
Data-Driven Testing offers a solution to this problem by keeping the data separate from the functional tests and utilizing it when required to extend the automation tests.
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In this tutorial, we will delve into the concept of Data-Driven Testing, understand its working, and shed light on its benefits and drawbacks.
What This Guide Covers:
- What Is Data-Driven Testing?
- The Concept of Data-Driven Script
- The Idea of Keyword-Driven Test Automation
- Understanding the Hybrid Test Automation
- An Example Of DDT
- Creating a Data-Driven Framework In QTP
- Implementing Selenium Webdriver Data-Driven Framework
- Developing Data-Driven Tests via TestNG
- Analyzing the Advantages of Data-Driven Testing
- Understanding the Limitations of Data-Driven Testing
- Wrapping Up
Unraveling Data-Driven Testing
Data-Driven Testing symbolizes a designing strategy for tests and methodology to implement testing wherein the test scripts extract test data from external database sources like files or databases rather than using defined values.
Setting up and controlling the testing environment in this process isn’t hardcoded.
You might also be interested in reading: => Most Well-Known Test Automation Frameworks
Exploring Data-Driven Script
Here are some important features of Data-Driven Scripts:
- Detection of Variables and Hard Coded Components: Test scripts having hardcoded components can collapse when the application undergoes changes. Data-Driven Scripts integrate variable data and often include a combination of variable and hardcoded segments to maintain balance.
- Replication of Test Design: In Data-Driven Scripts, application designs are recreated in both manual and automated test scripts for coordinating references.
Delving into Keyword-Driven Test Automation
Keyword-Driven Test Automation, which is also referred to as Table-Driven Test Automation, is an application-agnostic framework in which tests are developed in the form of a data table using keywords.
The following are some features of Keyword-Driven Test Automation:
- Reusability, Error Correction, and Synchronization: Application-agnostic components accept application-specific data and can be reused across diverse applications.
- An Integrated Record: Each record within the data table lays out the actions to be conducted, the anticipated results, and the actual outcomes.
Understanding Hybrid Test Automation
The Hybrid Test Automation Framework amalgamates elements from both Data-Driven and Keyword-Driven Automation Frameworks.
An Illustration of DDT
For instance, let’s consider the example of Data-Driven Testing using the Login Page of a Flight Reservation website.
1) A test data file named TestData.csv (Comma Separated Values) is crafted.
2) The file comprises inputs for the driver script in addition to the expected results, as demonstrated by the table below:
3) The driver script for the aforementioned data file can be outlined as follows:
data = open(‘TestData.csv’).read()
lines = data.splitlines()
4) The driver script performs the following steps:
- Read Value1
- Read Value2
- Read Operator
5) The result is computed using the operator on Value1 and Value2.
6) Lastly, a comparison happens between the actual result and the expected outcome.
Creating a Data-Driven Framework in QTP
To design a Data-Driven Framework in QTP, you need the below listed components:
- Test Script and Object Repository: They are utilized in reading data from external sources and applying it to the software under test.
- External Data Source: It consists of the necessary test data for the test scripts.
QTP supports different data sources, including Excel files, XML files, text files, and databases.
There are three techniques to develop a Data-Driven Framework in QTP:
- Technique 1: Leverages QTP and data tables for storing and retrieving data.
- Technique 2: Integrates QTP, data tables, and Excel files. The data gets transferred from Excel files to the data table for access.
- Technique 3: It uses QTP and Excel files. All data is stored in Excel files, and QTP directly retrieves the data from these files.
Implementing Selenium Webdriver Data-Driven Framework
1) Selenium Webdriver Data-Driven Framework retrieves test inputs and outputs from ODBC sources, CVS files, and Excel files.
2) The framework encompasses program navigation, reading data files, and registering test statuses.
3) The framework should exhibit the following characteristics:
- Less time required to scrutinize extensive data sets
- Instant, straightforward, and effectual analysis
- Effortless debugging
- Clear architectural design
- Reliable, robust, and stable
- Convenient script maintenance
- Execution of scripts in various testing environments
=> Access this article to learn more about the Data-Driven Framework in Selenium with examples.
Designing Data-Driven Tests via TestNG
1) TestNG is a framework that supports Data-Driven automation testing in Selenium.
2) It is built over JUnit and lays out extra features for executing regression automation testing.
3) TestNG is a popularly preferred and extensively used framework with Selenium Webdriver.
4) It offers features such as parameterization, parallel test execution, and only requires JDK 7 or above.
5) A few of the noteworthy features of TestNG that attribute to its efficiency and user-friendliness are:
- Flexible Test Configuration
- Default JDK functions
- Support for various tools and plugins
- Parameter support
- Data-Driven testing support using DataProviders
- Powerful and secure Execution Model
- Appropriate for all types of testing
6) DataProviders are methods which supply test methods and test data for carrying out execution.
Pros of Data-Driven Testing
- Facilitates the generation of test scripts during the development of applications.
- Decreases redundancy and duplication of test scripts.
- Enables the production of test scripts with lesser code.
- Holds all details, such as inputs, outputs, and expected results in organized text records.
- Grants flexibility in application maintenance.
Cons of Data-Driven Testing
- Requires proficiency in scripting languages.
- Demands a significant number of data files for test cases with countless inputs.
- Creation of a new test case necessitates a new driver script with distinct data, and changes need to be made in both the test case and the driver script.
You would also be interested to read: => Executing Data-Driven Testing using SoapUI
Data-Driven Testing allows automation tests to be performed effectively with diverse input data, guaranteeing thorough application performance testing. Moreover, it boosts business intelligence by minimizing risks and facilitating real-time data analysis and sharing of information.
Data-Driven Testing quickens the decision-making process and encourages swift automation testing. The ability to move smoothly across data sets is yet another vital feature that cuts down testing timeframes.
About the Author: Sanjay Zalavadia – Serving as the Vice President of Client Service for Zephyr, Sanjay presents over 15 years of leadership expertise in IT and Technical Support Services. Throughout his professional journey, he has successfully set up and expanded first-rate IT and Support Services teams across several geographies for numerous small and large businesses.
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