Component Functional Retrieval System Based On Ontology Research And Design

Component Based Software Development is a process of the high-efficiency and high-quality construction of application software system through reusing one or more software component and the means of combination. The goal of CBSD is to simplify development and reduce costs by reusing the existing relationship between the components and fully tested components. At present, the technology of software component has become an important research, which includes the classification and organization of components, and the description and retrieval of components, and so on. With the expansion of the component library, the concept of component is no longer confined to the source code, but rather the needs, the frameworks, the documents, and all other information. As a result, how to carry out the efficient retrieval has become a crucial issue to improve the software system.The main contributions of the paper are described as following:First of all, the paper summarizes the methods of the classification and retrieval of components, and lists the advantages of CBSD, and also compares all kinds of the methods of component retrieval, and finally concludes that the semantic retrieval has been referred to as the trend of the development with the improvement of the technology of the Semantic Web and component.As an application of component semantic retrieval, the paper designs the component functional retrieval by using the theory of ontology. At first, it introduces the definition, the function, the construction, the description and retrieval language, and the example about ontology application. Secondly, it describes the design of function and structure and models. As stated above, it implements the component retrieval and logical reasoning. Finally, it introduces the finished system.The paper creates a quality evaluation model of component, which is used to be a criterion to evaluate the quality of component. It implements the process of self-adaptive study of the quality criterion and index weight by using ID3 Algorithm and Genetic Algorithm.Finally, a conclusion is made in the end of the thesis, and the aspects which need to be improved are analyzed.