The team of PIs will investigate technologies that utilize context and self-modifying graphs containing semantic information (semantic networks) to decrease the time to locate historical design information highly relevant to a proposed change request. The research will explore the usefulness of this innovative approach to provide an improved search mechanism for software development artifacts. Such improved searches will be applicable in many circumstances. This project is exploratory and proposes a set of preliminary research tasks on untested and novel ideas. The results will offer a new way to search for existing support information and historical design information that can help avoid or significantly limit project delays due to software changes. The innovative approach consists of techniques which take advantage of contextual information (e.g., user, project, application, environment, and other contexts) and of semantic networks which store relationships between software artifacts and traceability information. The results of the new search approach will provide a more contextualized, applicable, and targeted recommendation for relevant information to software engineers. The project will employ one graduate student and one undergraduate student who will be actively engaged in the research project.
