In this thesis, the overall conclusion is that combination strategies, (i.e., test case selection methods that manage the combinatorial explosion of possible things to test), can improve the software testing in most organizations. The research underlying this thesis emphasizes relevance by working in close relationship with industry.

Input parameter models of test objects play a crucial role for combination strategies. These models consist of parameters with corresponding parameter values and represent the input space and possibly other properties, such as state, of the test object. Test case selection is then defined as the selection of combinations of parameter values from these models.

This research describes a complete test process, adapted to combination strategies. Guidelines and step-by-step descriptions of the activities in process are included in the presentation. In particular, selection of suitable combination strategies, input parameter modeling and handling of conflicts in the input parameter models are addressed. It is also shown that several of the steps in the test process can be automated.

The test process is validated through a set of experiments and case studies involving industrial testers as well as actual test problems as they occur in industry. In conjunction with the validation of the test process, aspects of applicability of the combination strategy test process (e.g., usability, scalability and performance) are studied. Identification and discussion of barriers for the introduction of the combination strategy test process in industrial projects are also included.

This research also presents a comprehensive survey of existing combination strategies, complete with classifications and descriptions of their different properties. Further, this thesis contains a survey of the testing maturity of twelve software-producing organizations. The data indicate low test maturity in most of the investigated organizations. Test managers are often aware of this but have trouble improving. Combination strategies are suitable improvement enablers, due to their low introduction costs.