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Computer scientists often need to learn new programming languages quickly. The best way to prepare for this is to understand the foundational principles that underlie even the most complicated industrial languages. This text for an undergraduate programming languages course distills great languages and their design principles down to easy-to-learn 'bridge' languages implemented by interpreters whose key parts are explained in the text. The book goes deep into the roots of both functional and object-oriented programming, and it shows how types and modules, including generics/polymorphism, contribute to effective programming. The book is not just about programming languages; it is also about programming. Through concepts, examples, and more than 300 practice exercises that exploit the interpreter, students learn not only what programming-language features are but also how to do things with them. Substantial implementation projects include Milner's type inference, both copying and mark-and-sweep garbage collection, and arithmetic on arbitrary-precision integers.
Taking readers from elementary number theory, via algorithmic, to applied number theory in computer science, this text introduces basic concepts, results, and methods, before going on to discuss their applications in the design of hardware and software, cryptography, and security. Aimed at undergraduates in computing and information technology, and presupposing only high-school math, this book will also interest mathematics students concerned with applications. XXXXXXX Neuer Text This is an essential introduction to number theory for computer scientists. It treats three areas, elementary-, algorithmic-, and applied number theory in a unified and accessible manner. It introduces basic concepts and methods, and discusses their applications to the design of hardware, software, cryptography, and information security. Aimed at computer scientists, electrical engineers and students the presentation presupposes only an understanding of high-school math.
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