Risk-Based Adaptive Group Testing of Semantic Web Services

Comprehensive testing is necessary to ensure the quality of complex Web services that are loosely coupled, dynamic bound and integrated through standard protocols. Testing of such web services can be however very expensive due to the diversified user requirements and the large numbers of service combinations delivered by the open platform. Group testing was introduced in our previous research as a selective testing technique to reduce test cost and improve test efficiencies. It applies test cases efficiently so that the largest percent of problematic web service is detected as early as possible. The paper proposes a risk-based approach to group test selection. With this approach, test cases are categorized and scheduled with respect to the risks of their target service features. The approach is based on the assumption that for a service-based system, the tolerance to a featurepsilas failure is an inverse ratio to its risk. The risky features should be tested earlier and with more tests. We specially address the problem in the context of semantic Web Services and report a first attempt for an ontology-based quantitative risk assessment. The paper also discusses risk-based group testing process and strategies for ranking and ruling-out services of the test groups, at each risk level. Runtime monitoring mechanism is incorporated to detect the dynamic changes in service configuration and composition so that the risks can be continuously adjusted online.