Semantic Web Services (SWS) introduce a semantic layer to the current web infrastructure, enabling the automated processing of web tasks. Different frameworks have been proposed for designing SWS, however, there has been little research in the area of testing SWS. Generating test cases for SWS is challenging due to its dynamic nature and abstract views, evaluating the test cases is equally essential in order to ensure the quality of the test suite. In this paper, we propose a goal oriented generation and mutation based evaluation approach towards SWS testing. This way, the generation (model-based) and evaluation (code-based) procedures are totally independent to each other, which further provides a much accurate measurement on the results. In addition, a tool support has been developed to automate the major steps in the proposed solution.

Web services, the reusable software components, have brought automation to Internet computing. However, since they are currently described syntactically using XML standards, i.e., SOAP, WSDL and UDDI, the automation of web services tasks, e.g., web service discovery, selection, composition and execution, is still a challenge. In order to make the most of automation in Service Oriented Architecture (SOA), the concept of the semantic web services (SWS), which are described semantically using an ontology language, have been introduced. The research related to testing and quality assurance aspects of web services is not mature. This is especially true for semantic web services, since research to-date has mainly focused the automation of WS tasks. Furthermore, some semantic web service frameworks promote the client-oriented SOA, by formally specifying user requirements, called "goal specification", and automatically resolve it by appropriate web service detection. Keeping this in mind, we propose a novel approach for testing semantic web services based on user goal specifications. We believe this type of testing would add real value to web service users, unlike tradition web service testing.