Documentation Driven Software Development

Abstract

The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Our objective is to develop an integrated, systematic, documentation centric approach to software development, known as Documentation Driven Software Development (DDD). The research issues for DDD are creation and application of three key documenting technologies that will drive the development process and a Document Management System (DMS) that will support them. These technologies address (1) representations for active documents; (2) representations for repositories; (3) methods for analysis, transformation, and presentation of this ABSTRACTOur objective is to develop an integrated, systematic, documentation centric approach to software development, known as Documentation Driven Software Development (DDD). The research issues for DDD are creation and application of three key documenting technologies that will drive the development process and a Document Management System (DMS) that will support them. These technologies address (1) representations for active documents; (2) representations for repositories; (3) methods for analysis, transformation, and presentation of this information.In addition, we explored new possibilities for computer-aided interfaces that help humans with routine tasks. In doing so we applied Cognitive Science and machine learning methods to design user interfaces that can learn and assist users. We also expanded our work in the area of integration of ontologies from heterogeneous sources. Specifically, we studied Knowledge System Integration Ontology (KSIO) that aligns data and information systems with current situational context for the efficient knowledge collection, integration and transfer. The role of ontology is to organize and structure knowledge (e.g. by standardized terminology) so that semantic queries and associations become more efficient. We assessed the degree to which natural language processing can be usefully applied to the analysis of requirement changes and their impact on system structure and implementation.(a) Papers published in peer-reviewed journals (N/A for none)