From Mathematics To Generic Programming

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From Mathematics to Generic Programming

Author : Alexander A. Stepanov
Publisher : Addison-Wesley Professional
ISBN 13 : 0133491781
Total Pages : 311 pages
Book Rating : 4.1/5 (334 download)

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Book Synopsis From Mathematics to Generic Programming by : Alexander A. Stepanov

Download or read book From Mathematics to Generic Programming written by Alexander A. Stepanov and published by Addison-Wesley Professional. This book was released on 2014-11-13 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this substantive yet accessible book, pioneering software designer Alexander Stepanov and his colleague Daniel Rose illuminate the principles of generic programming and the mathematical concept of abstraction on which it is based, helping you write code that is both simpler and more powerful. If you’re a reasonably proficient programmer who can think logically, you have all the background you’ll need. Stepanov and Rose introduce the relevant abstract algebra and number theory with exceptional clarity. They carefully explain the problems mathematicians first needed to solve, and then show how these mathematical solutions translate to generic programming and the creation of more effective and elegant code. To demonstrate the crucial role these mathematical principles play in many modern applications, the authors show how to use these results and generalized algorithms to implement a real-world public-key cryptosystem. As you read this book, you’ll master the thought processes necessary for effective programming and learn how to generalize narrowly conceived algorithms to widen their usefulness without losing efficiency. You’ll also gain deep insight into the value of mathematics to programming—insight that will prove invaluable no matter what programming languages and paradigms you use. You will learn about How to generalize a four thousand-year-old algorithm, demonstrating indispensable lessons about clarity and efficiency Ancient paradoxes, beautiful theorems, and the productive tension between continuous and discrete A simple algorithm for finding greatest common divisor (GCD) and modern abstractions that build on it Powerful mathematical approaches to abstraction How abstract algebra provides the idea at the heart of generic programming Axioms, proofs, theories, and models: using mathematical techniques to organize knowledge about your algorithms and data structures Surprising subtleties of simple programming tasks and what you can learn from them How practical implementations can exploit theoretical knowledge

Elements of Programming

Author : Alexander Stepanov
Publisher : Lulu.com
ISBN 13 : 0578222140
Total Pages : 282 pages
Book Rating : 4.5/5 (782 download)

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Book Synopsis Elements of Programming by : Alexander Stepanov

Download or read book Elements of Programming written by Alexander Stepanov and published by Lulu.com. This book was released on 2019-06-27 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of Programming provides a different understanding of programming than is presented elsewhere. Its major premise is that practical programming, like other areas of science and engineering, must be based on a solid mathematical foundation. The book shows that algorithms implemented in a real programming language, such as C++, can operate in the most general mathematical setting. For example, the fast exponentiation algorithm is defined to work with any associative operation. Using abstract algorithms leads to efficient, reliable, secure, and economical software.

Programming with Types

Author : Vlad Riscutia
Publisher : Simon and Schuster
ISBN 13 : 1638350264
Total Pages : 531 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Programming with Types by : Vlad Riscutia

Download or read book Programming with Types written by Vlad Riscutia and published by Simon and Schuster. This book was released on 2019-10-31 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Programming with Types teaches you to design safe, resilient, correct software that’s easy to maintain and understand by taking advantage of the power of strong type systems. Designed to provide practical, instantly useful techniques for working developers, this clearly written tutorial introduces you to using type systems to support everyday programming tasks. About the technology Common bugs often result from mismatched data types. By precisely naming and controlling which data are allowable in a calculation, a strong type system can eliminate whole classes of errors and ensure data integrity throughout an application. As a developer, skillfully using types in your everyday practice leads to better code and saves time tracking down tricky data-related errors. About the book Programming with Types teaches type-based techniques for writing software that’s safe, correct, easy to maintain, and practically self-documenting. Designed for working developers, this clearly written tutorial sticks with the practical benefits of type systems for everyday programming tasks. Following real-world examples coded in TypeScript, you’ll build your skills from primitive types up to more-advanced concepts like functors and monads. What's inside Building data structures with primitive types, arrays, and references How types affect functions, inheritance, and composition Object-oriented programming with types Applying generics and higher-kinded types About the reader You’ll need experience with a mainstream programming language like TypeScript, Java, JavaScript, C#, or C++. About the author Vlad Riscutia is a principal software engineer at Microsoft. He has headed up several major software projects and mentors up-and-coming software engineers.

A Programmer's Introduction to Mathematics

Author : Jeremy Kun
Publisher :
ISBN 13 :
Total Pages : 400 pages
Book Rating : 4.6/5 (253 download)

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Book Synopsis A Programmer's Introduction to Mathematics by : Jeremy Kun

Download or read book A Programmer's Introduction to Mathematics written by Jeremy Kun and published by . This book was released on 2020-05-17 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Programmer's Introduction to Mathematics uses your familiarity with ideas from programming and software to teach mathematics. You'll learn about the central objects and theorems of mathematics, including graphs, calculus, linear algebra, eigenvalues, optimization, and more. You'll also be immersed in the often unspoken cultural attitudes of mathematics, learning both how to read and write proofs while understanding why mathematics is the way it is. Between each technical chapter is an essay describing a different aspect of mathematical culture, and discussions of the insights and meta-insights that constitute mathematical intuition. As you learn, we'll use new mathematical ideas to create wondrous programs, from cryptographic schemes to neural networks to hyperbolic tessellations. Each chapter also contains a set of exercises that have you actively explore mathematical topics on your own. In short, this book will teach you to engage with mathematics. A Programmer's Introduction to Mathematics is written by Jeremy Kun, who has been writing about math and programming for 10 years on his blog "Math Intersect Programming." As of 2020, he works in datacenter optimization at Google.The second edition includes revisions to most chapters, some reorganized content and rewritten proofs, and the addition of three appendices.

Math for Programmers

Author : Paul Orland
Publisher : Manning Publications
ISBN 13 : 1617295353
Total Pages : 686 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis Math for Programmers by : Paul Orland

Download or read book Math for Programmers written by Paul Orland and published by Manning Publications. This book was released on 2021-01-12 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. Summary To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest programming fields. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code! About the book In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. What's inside Vector geometry for computer graphics Matrices and linear transformations Core concepts from calculus Simulation and optimization Image and audio processing Machine learning algorithms for regression and classification About the reader For programmers with basic skills in algebra. About the author Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at www.paulor.land. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks

Datatype-Generic Programming

Author : Roland Backhouse
Publisher : Springer Science & Business Media
ISBN 13 : 3540767851
Total Pages : 379 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Datatype-Generic Programming by : Roland Backhouse

Download or read book Datatype-Generic Programming written by Roland Backhouse and published by Springer Science & Business Media. This book was released on 2007-11-30 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial book presents six carefully revised lectures given at the Spring School on Datatype-Generic Programming, SSDGP 2006. This was held in Nottingham, UK, in April 2006. It was colocated with the Symposium on Trends in Functional Programming (TFP 2006), and the Conference of the Types Project (TYPES 2006). All the lectures have been subjected to thorough internal review by the editors and contributors, supported by independent external reviews.

Basic Category Theory for Computer Scientists

Author : Benjamin C. Pierce
Publisher : MIT Press
ISBN 13 : 0262326450
Total Pages : 117 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Basic Category Theory for Computer Scientists by : Benjamin C. Pierce

Download or read book Basic Category Theory for Computer Scientists written by Benjamin C. Pierce and published by MIT Press. This book was released on 1991-08-07 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Contents Tutorial • Applications • Further Reading

Certified Programming with Dependent Types

Author : Adam Chlipala
Publisher : MIT Press
ISBN 13 : 0262317885
Total Pages : 437 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Certified Programming with Dependent Types by : Adam Chlipala

Download or read book Certified Programming with Dependent Types written by Adam Chlipala and published by MIT Press. This book was released on 2013-12-06 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: A handbook to the Coq software for writing and checking mathematical proofs, with a practical engineering focus. The technology of mechanized program verification can play a supporting role in many kinds of research projects in computer science, and related tools for formal proof-checking are seeing increasing adoption in mathematics and engineering. This book provides an introduction to the Coq software for writing and checking mathematical proofs. It takes a practical engineering focus throughout, emphasizing techniques that will help users to build, understand, and maintain large Coq developments and minimize the cost of code change over time. Two topics, rarely discussed elsewhere, are covered in detail: effective dependently typed programming (making productive use of a feature at the heart of the Coq system) and construction of domain-specific proof tactics. Almost every subject covered is also relevant to interactive computer theorem proving in general, not just program verification, demonstrated through examples of verified programs applied in many different sorts of formalizations. The book develops a unique automated proof style and applies it throughout; even experienced Coq users may benefit from reading about basic Coq concepts from this novel perspective. The book also offers a library of tactics, or programs that find proofs, designed for use with examples in the book. Readers will acquire the necessary skills to reimplement these tactics in other settings by the end of the book. All of the code appearing in the book is freely available online.

Programming for Computations - Python

Author : Svein Linge
Publisher : Springer
ISBN 13 : 3319324284
Total Pages : 244 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Programming for Computations - Python by : Svein Linge

Download or read book Programming for Computations - Python written by Svein Linge and published by Springer. This book was released on 2016-07-25 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.

Generic Programming and the STL

Author : Matthew H. Austern
Publisher : Addison-Wesley Professional
ISBN 13 :
Total Pages : 584 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Generic Programming and the STL by : Matthew H. Austern

Download or read book Generic Programming and the STL written by Matthew H. Austern and published by Addison-Wesley Professional. This book was released on 1999 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces programmers to the generic programming paradigm and to the C++ Standard Template Library and its use as an extensible framework for generic and interoperable components. Explains ideas underlying generic programming and shows how to create algorithms decoupled from the types and data structures they operate on, and how to write more efficient code that can be used and reused across platforms. Assumes familiarity with C++ and algorithms. Annotation copyrighted by Book News, Inc., Portland, OR

Introduction to Scientific Programming with Python

Author : Joakim Sundnes
Publisher :
ISBN 13 : 3030503569
Total Pages : 157 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Introduction to Scientific Programming with Python by : Joakim Sundnes

Download or read book Introduction to Scientific Programming with Python written by Joakim Sundnes and published by . This book was released on 2020 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.

From Mathematics to Generic Programming

Author : Alexander A. Stepanov
Publisher : Pearson Education
ISBN 13 : 0321942043
Total Pages : 311 pages
Book Rating : 4.3/5 (219 download)

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Book Synopsis From Mathematics to Generic Programming by : Alexander A. Stepanov

Download or read book From Mathematics to Generic Programming written by Alexander A. Stepanov and published by Pearson Education. This book was released on 2014 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a great introduction to the core principles of generic programming for the experienced programmer. The authors work through examples showing how to analyze the requirements of an algorithm and make it as general as possible. The book includes several programming "laws" of particular interest to those building software components. The authors show how programmers can become more effective by learning about the idea of abstraction and the math it relies on. In an engaging and accessible fashion, they describe how these mathematical results were first discovered and are surprisingly useful in programming.

Theoretical Introduction to Programming

Author : Bruce Ian Mills
Publisher : Springer Science & Business Media
ISBN 13 : 1846282632
Total Pages : 366 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Theoretical Introduction to Programming by : Bruce Ian Mills

Download or read book Theoretical Introduction to Programming written by Bruce Ian Mills and published by Springer Science & Business Media. This book was released on 2005-12-19 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Including easily digested information about fundamental techniques and concepts in software construction, this book is distinct in unifying pure theory with pragmatic details. Driven by generic problems and concepts, with brief and complete illustrations from languages including C, Prolog, Java, Scheme, Haskell and HTML. This book is intended to be both a how-to handbook and easy reference guide. Discussions of principle, worked examples and exercises are presented. All concepts outside introductory programming are explained with clear demarcation and dependencies so the experienced programmer can quickly locate material. Readable in a linear manner, with short mono-thematic to encourage dipping and reference. Also included are sections on open problems in software theory and practice. While little other than a novice programmer's knowledge is explicitly assumed, a certain conceptual maturity, either through commercial programming or academic training is required – each language is introduced and explained briefly as needed.

The Book of R

Author : Tilman M. Davies
Publisher : No Starch Press
ISBN 13 : 1593277792
Total Pages : 833 pages
Book Rating : 4.5/5 (932 download)

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Book Synopsis The Book of R by : Tilman M. Davies

Download or read book The Book of R written by Tilman M. Davies and published by No Starch Press. This book was released on 2016-07-16 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Mathematics for Machine Learning

Author : Marc Peter Deisenroth
Publisher : Cambridge University Press
ISBN 13 : 1108569323
Total Pages : 392 pages
Book Rating : 4.1/5 (85 download)

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Book Synopsis Mathematics for Machine Learning by : Marc Peter Deisenroth

Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Mathematics and Computation

Author : Avi Wigderson
Publisher : Princeton University Press
ISBN 13 : 0691189137
Total Pages : 434 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Mathematics and Computation by : Avi Wigderson

Download or read book Mathematics and Computation written by Avi Wigderson and published by Princeton University Press. This book was released on 2019-10-29 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to computational complexity theory, its connections and interactions with mathematics, and its central role in the natural and social sciences, technology, and philosophy Mathematics and Computation provides a broad, conceptual overview of computational complexity theory—the mathematical study of efficient computation. With important practical applications to computer science and industry, computational complexity theory has evolved into a highly interdisciplinary field, with strong links to most mathematical areas and to a growing number of scientific endeavors. Avi Wigderson takes a sweeping survey of complexity theory, emphasizing the field’s insights and challenges. He explains the ideas and motivations leading to key models, notions, and results. In particular, he looks at algorithms and complexity, computations and proofs, randomness and interaction, quantum and arithmetic computation, and cryptography and learning, all as parts of a cohesive whole with numerous cross-influences. Wigderson illustrates the immense breadth of the field, its beauty and richness, and its diverse and growing interactions with other areas of mathematics. He ends with a comprehensive look at the theory of computation, its methodology and aspirations, and the unique and fundamental ways in which it has shaped and will further shape science, technology, and society. For further reading, an extensive bibliography is provided for all topics covered. Mathematics and Computation is useful for undergraduate and graduate students in mathematics, computer science, and related fields, as well as researchers and teachers in these fields. Many parts require little background, and serve as an invitation to newcomers seeking an introduction to the theory of computation. Comprehensive coverage of computational complexity theory, and beyond High-level, intuitive exposition, which brings conceptual clarity to this central and dynamic scientific discipline Historical accounts of the evolution and motivations of central concepts and models A broad view of the theory of computation's influence on science, technology, and society Extensive bibliography

Fundamental Proof Methods in Computer Science

Author : Konstantine Arkoudas
Publisher : MIT Press
ISBN 13 : 0262342502
Total Pages : 1223 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Fundamental Proof Methods in Computer Science by : Konstantine Arkoudas

Download or read book Fundamental Proof Methods in Computer Science written by Konstantine Arkoudas and published by MIT Press. This book was released on 2017-04-28 with total page 1223 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook that teaches students to read and write proofs using Athena. Proof is the primary vehicle for knowledge generation in mathematics. In computer science, proof has found an additional use: verifying that a particular system (or component, or algorithm) has certain desirable properties. This book teaches students how to read and write proofs using Athena, a freely downloadable computer language. Athena proofs are machine-checkable and written in an intuitive natural-deduction style. The book contains more than 300 exercises, most with full solutions. By putting proofs into practice, it demonstrates the fundamental role of logic and proof in computer science as no other existing text does. Guided by examples and exercises, students are quickly immersed in the most useful high-level proof methods, including equational reasoning, several forms of induction, case analysis, proof by contradiction, and abstraction/specialization. The book includes auxiliary material on SAT and SMT solving, automated theorem proving, and logic programming. The book can be used by upper undergraduate or graduate computer science students with a basic level of programming and mathematical experience. Professional programmers, practitioners of formal methods, and researchers in logic-related branches of computer science will find it a valuable reference.