RISK ASSESSMENT AND ADAPTIVE GROUP TESTING OF SEMANTIC WEB SERVICES

Abstract

Testing is necessary to ensure the quality of web services that are loosely coupled, dynamic bound and integrated through standard protocols. Exhaustive testing of web services is usually impossible due to unavailable source code, diversified user requirements and large number of possible service combinations delivered by the open platform. This paper proposes a risk-based approach for selecting and prioritizing test cases for testing service-based systems. We specially address the problem in the context of semantic web services. Semantic web services introduce semantics to service integration and interoperation using ontology models and specifications. Semantic errors are considered more difficult to detect than syntactic errors. Due to the complexity of conceptual uniformity, it is hard to ensure the completeness, consistency and unified quality of ontology model. A failure of the semantic service-based software may result from many factors such as misused data, unsuccessful service binding, and unexpected usage scenarios. This work analyzes the two factors of risk estimation: failure probability and importance, from three aspects: ontology data, service and composite service. With this approach, test cases are associated to semantic features, and are scheduled based on the risks of their target features. Risk assessment is used to control the process of Web Services progressive group testing, including test case ranking, test case selection and service ruling out. This paper discusses the control architecture and adaptive measurement mechanism for adaptive group testing. As a statistical testing technique, the proposed approach aims to detect, as early as possible, the problems with highest impact on the users.