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A groundbreaking book in this field, Software Engineering Foundations: A Software Science Perspective integrates the latest research, methodologies, and their applications into a unified theoretical framework. Based on the author's 30 years of experience, it examines a wide range of underlying theories from philosophy, cognitive informatics, denotational mathematics, system science, organization laws, and engineering economics. The book contains in-depth information, annotated references, real-world problems, heuristics, and research opportunities.

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.
The denotational and expressive needs in cognitive informatics, computational intelligence, software engineering, and knowledge engineering have led to the development of new forms of mathematics collectively known as denotational mathematics. Denotational mathematics is a category of mathematical structures that formalize rigorous expressions and long-chain inferences of system compositions and behaviors with abstract concepts, complex relations, and dynamic processes. Typical paradigms of denotational mathematics are concept algebra, system algebra, Real-Time Process Algebra (RTPA), Visual Semantic Algebra (VSA), fuzzy logic, and rough sets. A wide range of applications of denotational mathematics have been identified in many modern science and engineering disciplines that deal with complex and intricate mathematical entities and structures beyond numbers, Boolean variables, and traditional sets. This issue of Springer’s Transactions on Computational Science on Denotational Mathematics for Computational Intelligence presents a snapshot of current research on denotational mathematics and its engineering applications. The volume includes selected and extended papers from two international conferences, namely IEEE ICCI 2006 (on Cognitive Informatics) and RSKT 2006 (on Rough Sets and Knowledge Technology), as well as new contributions. The following four important areas in denotational mathem- ics and its applications are covered: Foundations and applications of denotational mathematics, focusing on: a) c- temporary denotational mathematics for computational intelligence; b) deno- tional mathematical laws of software; c) a comparative study of STOPA and RTPA; and d) a denotational mathematical model of abstract games.
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