Coverage-oriented, prioritized testing - A fuzzy clustering approach and case study

Abstract

Existing test techniques focus on particular, relevant aspects of the requirements of the system under test (SUT). Real-life SUTs have, however, numerous features to simultaneously be considered, often leading to a large number of tests. In such cases, because of time and cost constraints the entire set of tests cannot be run. It is then essential to prioritize the tests in sense of a ordering of the relevant events entailed in accordance with the importance of their numerous features. This paper proposes a graph-model-based approach to prioritizing the test process. Tests are ranked according to their preference degrees which are determined indirectly, i.e., through classifying the e, vents. To construct the groups of events, Fuzzy c-Means (FCM) clustering algorithm is used. A case study demonstrates and validates the approach. Contrary to other approaches, no prior information is needed about the tests carried out before, e.g., as is case in regression testing.