Research On Semantic Web-based Software Engineering Data Query Processing

The development of software brings huge amount of data which has complicated structure and rich semantics. Building a flexible semantic model is the foundation of the management on various types of software engineering data. In the progress of such management, how to make high performance query is a big challenge for many project administrators and research people. The rise of semantic web technology provides a new idea to resolve such problems. RDF and OWL are the important parts of the semantic web which have strong ability on describing and modeling complex data. Since software engineering data has related and heterogeneous structure, it can be denoted easily with RDF and OWL. In the field of semantic web, RDF query optimization is also a hot spot. We focus how to denote and query software engineering data using semantic web technology. The novelty and contributions of this dissertation can be summarized as following:We discuss the management strategy of software engineering data in semantic web environment. We make a classification for the queries on software engineering data and give some representative query scene.We define an ontology model for software engineering data to give an integrated description on such data. We collect a number of software engineering data according to the ontology. These data can be used on future research and experiment.We summarize existing techniques of semantic web query optimization; propose a novel optimization method using ontology statistical data. The method improves query performance by reducing the cost of join operation in query. Experimental results confirm that the method has better performance than existing approach.The work of this dissertation presents a new idea for managing software engineering data efficiently.it is also the core techniques of developing a storage and search platform for massive software engineering data.