About: Knowledge Based Software Assistant is a research topic. Over the lifetime, 18 publications have been published within this topic receiving 410 citations.
TL;DR: In this paper, the authors present an approach that embedshuman-computer cooperative problem-solving tools intodomain-oriented, knowledge-based design environments to reduce the conceptual distance between problem-domain semantics and software artifacts.
Abstract: The field of knowledge-based software engineering has been undergoing a shift in emphasis from automatic programming to human augmentation and empowerment. In our research work, we support this shift with an approach that embedshuman-computer cooperative problem-solving tools intodomain-oriented, knowledge-based design environments. Domain orientation reduces the large conceptual distance between problem-domain semantics and software artifacts. Integrated environments support the coevolution of specification and construction while allowing designers to access relevant knowledge at each stage within the software development process.
TL;DR: A knowledge-based software assistant that provides for the capture of, and reasoning about, software activities to support this new paradigm, which will dramatically improve productivity, reliability, adaptability, and functionality in software systems.
Abstract: This report presents a knowledge-based, life-cycle paradigm for the development, evolution, and maintenance of large software projects. To resolve current software development and maintenance problems, this paradigm introduces a fundamental change in the software life cycle — maintenance and evolution occur by modifying the specifications and then rederiving the implementation, rather than attempting to directly modify the optimized implementation. Since the implementation will be rederived for each change, this process must be automated to increase its reliability and reduce its costs. Basing the new paradigm on the formalization and machine capture of all software decisions allows knowledge-based reasoning to assist with these decisions. This report describes a knowledge-based software assistant (KBSA) that provides for the capture of, and reasoning about, software activities to support this new paradigm. This KBSA will provide a corporate memory of the development history and act throughout the life cycle as a knowledgeable software assistant to the human involved (e.g., the developers, maintainers, project managers, and end-users. In this paradigm, software activities, including definition, management, and validation will be carried out primarily at the specification and requirements level, not the implementation level. The transformation from requirements to specifications to implementations will be carried out with automated, knowledge-based assistance. The report presents descriptions for several of the facets (areas of expertise) of the software assistant including requirements, specification validation, performance analysis, development, testing, documentation, and project management. The report also presents a plan for the development of the KBSA, along with a description of the necessary supporting technology. This new paradigm will dramatically improve productivity, reliability, adaptability, and functionality in software systems.
TL;DR: This paper summarizes one potential solution to this software problem, the Knowledge-Based Software Assistant, which would allow the DoD to continue to field modern, complex systems despite current software productivity and quality limitations.
Abstract: Computer software dominates the functioning of most new defense systems and is a rapidly increasing share of the budget. The ability of the Department of Defense (DoD) to continue to field modern, complex systems depends upon its success in overcoming current software productivity and quality limitations. This paper summarizes one potential solution to this software problem, the Knowledge-Based Software Assistant.
Abstract: A new way to acquire knowledge, H.-Y. Wang an SPN knowledge representation scheme, J. Gattiker and N. Bourbakis on the deep structures of word problems and their construction, F. Gomez resolving conflicts in inheritance reasoning with statistical approach, C. Lee integrating high and low level computer vision for scene understanding, R. Malik and S. So the evolution of commercial AI tools - the first decade, F. Hayes-Roth reengineering - the AT generation - billions on the table, J.S. Minor, Jr. an intelligent tool for discovering data dependencies in relational DBS, P. Gavaskar and F. Golshani a case-based reasoning (CBR) tool to assist traffic flow, B. Das and S. Bayles a study of financial expert system based on flops, T. Kaneko and K. Takenaka an associative data parallel compilation model for tight integration of high performance knowledge retrieval and computation, A. Bansal software automation - from silly to intelligent, X. Jiafu et al software engineering using artificial intelligence - the knowledge based software assistant, D. White knowledge based derivation of programmes from specs, T. Weight et al automatic functional model generation for parallel fault design error simulations, S.E. Chang and S. Szygenda visual reverse engineering using SPN for automated diagnosis and functional simulation of digital circuits, J. Gattiker and S. Mertoguno the impact of AI in VLSI design automation, M. Mortazavi and N. Bourbakis the automated acquisition of subcategorization of verbs, nouns and adjectives from sample sentences, F. Gomez general method for planning and rendezvous problems, K. Trovato learning to improve path planning performance, P.C. Chen incremental adaptation as a method to improve reactive behaviour, A.J. Hendriks and D.M. Lyons an SPN-neural planning methodology for coordination of multiple robotic arms with constrained placement, N. Bourbakis and A. Tascillo.