Software Engineering Processes: Principles and Applications does just that. Within a unified framework, this book presents a comparative analysis of current process models and formally describes their algorithms. It systematically enables comparison between current models, avoidance of ambiguity in application, and simplification of manipulation for practitioners.
The authors address a broad range of topics within process-based software engineering and the fundamental theories and philosophies behind them. They develop a software engineering process reference model (SEPRM) to show how to solve the problems of different process domains, orientations, structures, taxonomies, and methods. They derive a set of process benchmarks-based on a series of international surveys-that support validation of the SEPRM model. Based on their SEPRM model and the unified process theory, they demonstrate that current process models can be integrated and their assessment results can be transformed between each other.
Software development is no longer just a black art or laboratory activity. It is an industrialized process that requires the skills not just of programmers, but of organization and project managers and quality assurance specialists. Software Engineering Processes: Principles and Applications is the key to understanding, using, and improving upon effective engineering procedures for software development.
The fifth volume of the Transactions on Computational Science journal, edited by Yingxu Wang and Keith C.C. Chan, is devoted to the subject of cognitive knowledge representation. This field of study focuses on the internal knowledge representation mechanisms of the brain and how these can be applied to computer science and engineering. The issue includes the latest research results in internal knowledge representation at the logical, functional, physiological, and biological levels and describes their impacts on computing, artificial intelligence, and computational intelligence.
Highlighting the inherent limitations of the historical programming-language-centered approach, the author explores an interdisciplinary approach to software engineering. He identifies fundamental cognitive, organizational, and resource constraints and the need for multi-faceted and transdisciplinary theories and empirical knowledge. He then synergizes theories, principles, and best practices of software engineering into a unified framework and delineates overarching, durable, and transdisciplinary theories as well as alternative solutions and open issues for further research. The book develops dozens of Wang's laws for software engineering and outlooks the emergence of software science.
The author's rigorous treatment of the theoretical framework and his comprehensive coverage of complicated problems in software engineering lay a solid foundation for software theories and technologies. Comprehensive and written for all levels, the book explains a core set of fundamental principles, laws, and a unified theoretical framework.
This volume in LNCS (subseries of Computational Intelligence), LNCI 323, edited by Y. Wang, D. Zhang, and W. Kinsner, presents the latest development in cognitive informatics and cognitive computing. The book focuses on the explanation of cognitive models of the brain, the layered reference model of the brain, the fundamental mechanisms of abstract intelligence, and the implementation of computational intelligence by autonomous inference and learning engines based on CCs.