Keyword-Driven and Data-Driven Framework: Differences You Must Know



The test framework is a collection of guidelines that could be followed for creating test cases and related procedures. These guidelines could be about coding practices, storage and retrieval of test data and test results, interaction with outside resources, and many other things. A test framework generally contains internal libraries and reusable code modules that implement a foundation for test automation and could be leveraged for building test automation systems for different applications. So, without wasting any time, let’s jump onto the benefits and difference data-driven framework and keyword-driven framework.

Benefits of a test automation framework

A test automation framework offers several benefits, and some of them are mentioned as follows:

Efficiency: Test automation framework implement structure for test automation tasks like test creation, test execution, organization of tests, test data creation, or reporting. It assists complexity, duplication of efforts, and repetition. Thus, using a test automation framework executes developing a test automation system more productive.

Easy maintenance: As all test cases are created following the same structure as debugging bugs and isolation becomes easier.

Reduced manual interactions: The main purpose of automatic any process is to reduce manual labour. Implementing a test automation framework will help reduce the manual labour involved in the execution of test cases.

Flexibility to run selective test cases: A test automation framework usually presents the versatility of executing a single test case, a suite of test cases for all test cases. Such flexibility helps during the development and debugging sessions of test scripts and for selective testing.

The requirement for a data-driven framework for test automation

Data is embedded on test scripts that make it difficult to update the test data at any point of time in a non-data driven testing framework. It becomes a festering problem in product life cycle test data may need to be updated several times for various reasons.

Test data and test scripts are separated, making it easier for maintaining and updating the test data at any point in time without altering the test scripts in data-driven testing frameworks. Thus, testers can make any changes to the test scripts without modifying the test data.

Data-Driven Framework

Source: Primesoft Solutions

Benefits of a data-driven framework for test automation

Several benefits are offered by a data-driven framework such as:

Less number of test scripts: As we can execute the same test scripts using multiple test data sets, the total count of test scripts needed is greatly decreased.

Less error-prone: As test data and test scripts are separate objects, each of them could be updated individually without conflicting with others. It reduces uncertainty by introducing errors in the test automation system by updating either test data or scripts.

More flexibility: Sense test data is stored externally; it is very easy to perform positive and negative testing by using the same test scripts just by updating the test data.

Easier maintenance: Data-driven test automation systems are easy to maintain than non-data-driven test automation systems where data and test scripts are tightly linked and cannot be updated independently.

The requirement for a keyword-driven framework for test automation

In a keyword-driven framework writing and managing the test, the script becomes the principal duty of QA automation experts in the team. In contrast, automation experts in the team who do have a much better understanding of the product are left out. A bottleneck in the testing team’s productivity is created by it as the team members creating the test scripts are always under pressure for writing more scripts to build the test automation system quickly.

On the other hand, team members who are not building the test scripts do not have much confidence in the quality of test scripts created as they know the product better than the team members building the test scripts and try to be dependent on manual testing.

The keyword-driven framework helps eliminate these bottlenecks and generates a balance between all team members with and without the programming language to continue contributing towards creating the product’s test automation system. Test scripts are a series of keywords mapped to what functions define specific behaviours in a keyword-driven framework.

Data-Driven Framework

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Benefits of a keyword-driven framework for test automation

Few benefits of the keyword-driven frameworks are:

Application abstraction: Test scripts could be designed with or without the application under test. It is very useful when test cases must be developed before the application is ready for testing.

Enhanced team productivity: As everyone on the team is allowed to be a part of the automation journey in a keyword-driven framework, it boosts the team’s productivity and confidence.

More suited for agile: Keyword driven framework is very helpful when products are developed using agile methodologies. When there is a modification in the product’s requirements, we only need to update the function’s implementation to accommodate the new behaviour rather than changing the whole test script.

Platform independent test scripts: If the product’s behaviour is expected to be the same on different platforms, testers can reuse the same test scripts. Platform-specific changes will be required only in the implementations of functions mapped to these keywords.

Code reusability: As multiple test scripts could be defined using the same set of keywords, the code is reused to a great extent.

Difference between data-driven and keyword-driven framework

The difference between data-driven and keyword-driven framework can be summarised as follows:

The need for programming expertise in the team: As both frameworks require programming expertise in the team, the keyword-driven framework can leverage non-programming expertise in the team. Such as manual testers full AC in programming expertise well-versed with the product. It allows everyone in the team to contribute to developing the test automation system of the product they are working on. At the same time, a data-driven framework doesn’t allow such flexibility.

To build a test automation system implementing a data-driven framework, we need programming experts in the team who can write test scripts using a programming language.

Non-programming experts of the product don’t have many opportunities for developing the test automation system of the product they are working on.

Need after that for developing test scripts: It becomes easier for developing test scripts using the keyword-driven framework when the product development is not complete. Only the application of keywords depends upon the actual product development. On the other hand, for developing test scripts using a data-driven framework, the actual product is required.

Planning: More extensive planning when compared to a data-driven framework is required by a keyword-driven framework. We only need the plan for what test data and test scripts are needed with a data-driven framework square as with keyword driven framework we are required to plan for keywords and their applications along with test data and scripts.

Management: Test automation systems using a keyword-driven framework would be much harder for managing then data-driven framework if they are not properly planned.

Maintenance: A well-planned keyword-driven test automation system is more comfortable maintaining as it has well-defined layers of abstraction between test data, test scripts, keywords, and their implementation. Also, data-driven test automation system has abstraction only between test data and test scripts.

Conclusion

Different types of testing frameworks could be suitable for different types of products and teams. Before finalizing any framework for building our test automation system for the product, it is important for us to analyze our needs from a framework and what are our strengths as a team for working with the framework. This was all about the difference between data-driven and keyword-driven framework. Stay in touch with us for more interesting technophile articles.