A Framework for Data-Driven and Keyword-Driven Test Automation

The growing importance and stringent quality requirements of software systems are increasing demand for efficient software testing. Hiring more test engineers or lengthening the testing time are not viable long-term solutions, rather there is a need to decrease the amount of resources needed. One attractive solution to this problem is test automation, i.e. allocating certain testing tasks to computers. There are countless approaches to test automation, and they work differently in different contexts. This master's thesis focuses on only one of them, large-scale frameworks for automated test execution and reporting, but other key approaches are also briefly introduced.

The thesis opens its discussion of test automation frameworks by defining their high-level requirements. The most important requirements are identified as ease-of-use, maintainability and, of course, the ability to automatically execute tests and report results. More detailed requirements are derived from these high-level requirements: data-driven and keyword-driven testing techniques, for example, are essential prerequisites for both ease-of-use and maintainability.

The next step in the thesis is constructing and presenting a framework concept fulfilling the defined requirements. The concept and its underlying requirements were tested in a pilot where a prototype of the framework and some automated tests for different systems were implemented. Based on the pilot results, the overall framework concept was found to be feasible. Certain changes to the framework and original requirements are presented, however. The most interesting finding is that it is possible to cover all the data-driven testing needs with the keyword-driven approach alone.