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An accessible yet rigorous crash course on recursive programming using Python and JavaScript examples. Recursion has an intimidating reputation: it’s considered to be an advanced computer science topic frequently brought up in coding interviews. But there’s nothing magical about recursion. The Recursive Book of Recursion uses Python and JavaScript examples to teach the basics of recursion, exposing the ways that it’s often poorly taught and clarifying the fundamental principles of all recursive algorithms. You’ll learn when to use recursive functions (and, most importantly, when not to use them), how to implement the classic recursive algorithms often brought up in job interviews, and how recursive techniques can help solve countless problems involving tree traversal, combinatorics, and other tricky topics. This project-based guide contains complete, runnable programs to help you learn: How recursive functions make use of the call stack, a critical data structure almost never discussed in lessons on recursion How the head-tail and “leap of faith” techniques can simplify writing recursive functions How to use recursion to write custom search scripts for your filesystem, draw fractal art, create mazes, and more How optimization and memoization make recursive algorithms more efficient Al Sweigart has built a career explaining programming concepts in a fun, approachable manner. If you’ve shied away from learning recursion but want to add this technique to your programming toolkit, or if you’re racing to prepare for your next job interview, this book is for you.
What can computers do in principle? What are their inherent theoretical limitations? The theoretical framework which enables such questions to be answered has been developed over the last fifty years from the idea of a computable function - a function whose values can be calculated in an automatic way.
Recursive Functions and Metamathematics deals with problems of the completeness and decidability of theories, using as its main tool the theory of recursive functions. This theory is first introduced and discussed. Then Gödel's incompleteness theorems are presented, together with generalizations, strengthenings, and the decidability theory. The book also considers the historical and philosophical context of these issues and their philosophical and methodological consequences. Recent results and trends have been included, such as undecidable sentences of mathematical content, reverse mathematics. All the main results are presented in detail. The book is self-contained and presupposes only some knowledge of elementary mathematical logic. There is an extensive bibliography. Readership: Scholars and advanced students of logic, mathematics, philosophy of science.
Traces the development of recursive functions from their origins in the late nineteenth century to the mid-1930s, with particular emphasis on the work and influence of Kurt Gödel.
Formal Systems and Recursive Functions
Start building fast and robust applications with the power of Rust by your side About This Book Get started with the language to build scalable and high performance applications This book will help C#/C++ developers gain better performance and memory management Discover the power of Rust when developing concurrent applications for large and scalable software Who This Book Is For The book is for absolute beginners to Rust, who want to build high performance, concurrent applications for their projects. It is suitable for developers who have a basic knowledge of programming and developers who are using the C#/C++ language to write their applications. No knowledge of Rust is expected. What You Will Learn Set up Rust for Windows, Linux, and OS X Write effective code using Rust Expand your Rust applications using libraries Interface existing non-Rust libraries with your Rust applications Use the standard library within your applications Understand memory management within Rust and speed efficiency when passing variables Create more complex data types Study concurrency in Rust with multi-threaded applications and sync threading techniques to improve the performance of an application problem In Detail Rust is a highly concurrent and high performance language that focuses on safety and speed, memory management, and writing clean code. It also guarantees thread safety, and its aim is to improve the performance of existing applications. Its potential is shown by the fact that it has been backed by Mozilla to solve the critical problem of concurrency. Learning Rust will teach you to build concurrent, fast, and robust applications. From learning the basic syntax to writing complex functions, this book will is your one stop guide to get up to speed with the fundamentals of Rust programming. We will cover the essentials of the language, including variables, procedures, output, compiling, installing, and memory handling. You will learn how to write object-oriented code, work with generics, conduct pattern matching, and build macros. You will get to know how to communicate with users and other services, as well as getting to grips with generics, scoping, and more advanced conditions. You will also discover how to extend the compilation unit in Rust. By the end of this book, you will be able to create a complex application in Rust to move forward with. Style and approach This comprehensive book will focus on the Rust syntax, functions, data types, and conducting pattern matching for programmers. It is divided into three parts and each part of the book has an objective to enable the readers to create their own applications at an appropriate level, ultimately towards creating complex applications.
Recursion is one of the most fundamental concepts in computer science and a key programming technique that allows computations to be carried out repeatedly. Despite the importance of recursion for algorithm design, most programming books do not cover the topic in detail, despite the fact that numerous computer programming professors and researchers in the field of computer science education agree that recursion is difficult for novice students. Introduction to Recursive Programming provides a detailed and comprehensive introduction to recursion. This text will serve as a useful guide for anyone who wants to learn how to think and program recursively, by analyzing a wide variety of computational problems of diverse difficulty. It contains specific chapters on the most common types of recursion (linear, tail, and multiple), as well as on algorithm design paradigms in which recursion is prevalent (divide and conquer, and backtracking). Therefore, it can be used in introductory programming courses, and in more advanced classes on algorithm design. The book also covers lower-level topics related to iteration and program execution, and includes a rich chapter on the theoretical analysis of the computational cost of recursive programs, offering readers the possibility to learn some basic mathematics along the way. It also incorporates several elements aimed at helping students master the material. First, it contains a larger collection of simple problems in order to provide a solid foundation of the core concepts, before diving into more complex material. In addition, one of the book's main assets is the use of a step-by-step methodology, together with specially designed diagrams, for guiding and illustrating the process of developing recursive algorithms. Furthermore, the book covers combinatorial problems and mutual recursion. These topics can broaden students' understanding of recursion by forcing them to apply the learned concepts differently, or in a more sophisticated manner. The code examples have been written in Python 3, but should be straightforward to understand for students with experience in other programming languages. Finally, worked out solutions to over 120 end-of-chapter exercises are available for instructors.
The aim of this textbook is to present an account of the theory of computation. After introducing the concept of a model of computation and presenting various examples, the author explores the limitations of effective computation via basic recursion theory. Self-reference and other methods are introduced as fundamental and basic tools for constructing and manipulating algorithms. From there the book considers the complexity of computations and the notion of a complexity measure is introduced. Finally, the book culminates in considering time and space measures and in classifying computable functions as being either feasible or not. The author assumes only a basic familiarity with discrete mathematics and computing, making this textbook ideal for a graduate-level introductory course. It is based on many such courses presented by the author and so numerous exercises are included. In addition, the solutions to most of these exercises are provided.