Perspectives In Computation
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Physical Perspectives on Computation, Computational Perspectives on Physics
Offers an accessible yet cutting-edge tour of the many conceptual interconnections between physics and computer science.
Computational Thinking in Education
Computational Thinking in Education explores the relevance of computational thinking in primary and secondary education. As today’s school-aged students prepare to live and work in a thoroughly digitized world, computer science is providing a wealth of new learning concepts and opportunities across domains. This book offers a comprehensive overview of computational thinking, its history, implications for equity and inclusion, analyses of competencies in practice, and integration into learning, instruction, and assessment through scaffolded teacher education. Computer science education faculty and pre- and in-service educators will find a fresh pedagogical approach to computational thinking in primary and secondary classrooms.
Computability and Complexity
Computability and complexity theory should be of central concern to practitioners as well as theorists. Unfortunately, however, the field is known for its impenetrability. Neil Jones's goal as an educator and author is to build a bridge between computability and complexity theory and other areas of computer science, especially programming. In a shift away from the Turing machine- and G�del number-oriented classical approaches, Jones uses concepts familiar from programming languages to make computability and complexity more accessible to computer scientists and more applicable to practical programming problems. According to Jones, the fields of computability and complexity theory, as well as programming languages and semantics, have a great deal to offer each other. Computability and complexity theory have a breadth, depth, and generality not often seen in programming languages. The programming language community, meanwhile, has a firm grasp of algorithm design, presentation, and implementation. In addition, programming languages sometimes provide computational models that are more realistic in certain crucial aspects than traditional models. New results in the book include a proof that constant time factors do matter for its programming-oriented model of computation. (In contrast, Turing machines have a counterintuitive "constant speedup" property: that almost any program can be made to run faster, by any amount. Its proof involves techniques irrelevant to practice.) Further results include simple characterizations in programming terms of the central complexity classes PTIME and LOGSPACE, and a new approach to complete problems for NLOGSPACE, PTIME, NPTIME, and PSPACE, uniformly based on Boolean programs. Foundations of Computing series