There is no limit to what technology-led solutions can do for businesses and consumers. That is why organizations are spending a large share of their IT budget on application development.
In a seamless software development cycle, Quality Assurance (QA) has a major role to play. It ensures that a bug-free, performance-oriented application is delivered that aligns with the need of the targetted persona.
However, as software applications become large, complex, and interdependent; testing them manually poses challenges to the QA team. For example, regression testing for existing and new features become time-consuming and liable to errors as the application extends in scope. To deal with the limitations of manual (regression) testing, automation testing has become an indispensable part of large-scale applications.
Automation testing combines with regression testing to allow testers to automate the routine and repetitive test cases. It frees the valuable time of testing resources so that they can focus on intricate test scenarios.
To support automation testing, there are test frameworks. These frameworks are guidelines or rules that are used for creating/designing test cases, which include coding standards for writing test cases, object repositories, test-data handling method, etc.
Automation testing frameworks are good-to-have in a quality analysis cycle. They help to improve testing efficiency, lower maintenance costs, and minimize manual intervention. In the latter segment, we will discuss 6 testing frameworks that help the quality analysts to test with accuracy at a large scale.
- Linear Automation Framework
This framework is meant for small-sized projects or when the time span to get started with the testing procedure is quite low (days or hours). Instead of writing the test scripts, the already recorded scripts are in the test automation tool.
However, there are a few challenges that come along the ease. For example, the data is hardcoded into the scripts. That means, the test cases cannot be re-run with multiple sets and if there are any changes to the data, the test scripts need to be modified.
- Modular Based Testing Framework
In this testing framework, an application is divided into separate units, functions, and sections. Test scrips are then created for each section and are combined to build a larger test hierarchy. For large-size projects, modularity helps in breaking down the test load and achieving more accurate results with minimal time investment. Such an approach is highly beneficial for testing applications built on modern, modular architectures like microservices.
The modular approach to testing ensures that after a change in the application, test scripts for only a module are fixed, without having to run the test cases for the entire application. Another advantage of the modular testing framework is that the test scripts can be used for multiple modules of the application.
- Library Architecture Testing Framework
This is an extension of the modular framework. Instead of dividing the application into various scripts, similar tasks within the scripts are identified and grouped by functions. The functions are kept in a library and called by test scripts, whenever needed. Utilizing this architecture for automation will help to achieve high-level modularity, making it easy for the quality assurance team to manage testing scalability.
- Data-Driven Testing Framework
This testing approach is successful when a function or scenario has to be tested with a different data set (while keeping the internal test logic the same). The data-driven testing framework decouples the logic and data, giving high reusability to the scripts.
- Keyword-Driven Testing Framework
The keyword-driven approach is an extension of the data-driven testing framework. Here, specific keywords that are associated with the GUI and application functionality are stored externally. The keywords are independent entities and the developers write code to prompt necessary keyword-based action.
Which is the Best Test Automation Framework?
Application complexity, scalability, and test code reusability are some of the factors that help in the selection of the right framework. While frameworks are not must-haves, having them in the test cycle helps to ensure discipline, which guarantees accuracy in results.
Today, when the development approach is Agile and there is continuous feedback & improvements in the application, having an active testing approach in place is critical. At Daffodil, test automation frameworks are an important part of our software testing services.
To know more about how our quality analysts execute regression and automation testing for our large-scale projects, refer to some of our customer success stories. Here are links to a few of them:
- Performance and scalability testing for an India based unicorn e-commerce portal
- Automation Testing for a UAE based lottery application