Synopses & Reviews
Finally, you can learn computation theory and programming language design in an engaging, practical way. Understanding Computation explains theoretical computer science in a context youll recognize, helping you appreciate why these ideas matter and how they can inform your day-to-day programming.
Rather than use mathematical notation or an unfamiliar academic programming language like Haskell or Lisp, this book uses Ruby in a reductionist manner to present formal semantics, automata theory, and functional programming with the lambda calculus. Its ideal for programmers versed in modern languages, with little or no formal training in computer science.
- Understand fundamental computing concepts, such as Turing completeness in languages
- Discover how programs use dynamic semantics to communicate ideas to machines
- Explore what a computer can do when reduced to its bare essentials
- Learn how universal Turing machines led to todays general-purpose computers
- Perform complex calculations, using simple languages and cellular automata
- Determine which programming language features are essential for computation
- Examine how halting and self-referencing make some computing problems unsolvable
- Analyze programs by using abstract interpretation and type systems
Synopsis
Finally, you can learn computation theory and programming language design in an engaging, practical way. Understanding Computation explains theoretical computer science in a context youll recognize, helping you appreciate why these ideas matter and how they can inform your day-to-day programming.
Rather than use mathematical notation or an unfamiliar academic programming language like Haskell or Lisp, this book uses Ruby in a reductionist manner to present functional programming and lambda calculus. Its ideal for programmers versed in modern languages, with little or no formal training in computer science. Discover the theoretical underpinnings of your work with Understanding Computation.
- Learn fundamental computing concepts, such as Turing equivalence in languages
- Discover how programs can handle difficult or impossible problems
- Explore how many features a programming language needs
- Examine how computers can help you write correct programs
- Understand how to build data structures without mutation of state
- Learn how programmers can make a simple language like the lambda calculus actually run on a computer
About the Author
Tom is chief scientist at Expert Human. He is an experienced, passionate computer scientist and programmer. He work as a freelance consultant, mentor and trainer, helping all kinds of companies to improve the quality and clarity of their approach to creating software products, usually on the web. Sometimes this means spending a month writing code for them; at other times it means encouraging them to rethink their product, re-educate their teams, rewrite their tests, or ruthlessly refactor their code. He has lectured on compilers at the University of Cambridge, helped organize the Ru3y Manor conference, and is a member and speaker of the London Ruby User Group.
Table of Contents
Preface; Who Should Read This Book?; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments; Chapter 1: Just Enough Ruby; 1.1 Interactive Ruby Shell; 1.2 Values; 1.3 Control Flow; 1.4 Objects and Methods; 1.5 Classes and Modules; 1.6 Miscellaneous Features; Programs and Machines; Chapter 2: The Meaning of Programs; 2.1 The Meaning of "Meaning"; 2.2 Syntax; 2.3 Operational Semantics; 2.4 Denotational Semantics; 2.5 Formal Semantics in Practice; 2.6 Implementing Parsers; Chapter 3: The Simplest Computers; 3.1 Deterministic Finite Automata; 3.2 Nondeterministic Finite Automata; 3.3 Regular Expressions; 3.4 Equivalence; Chapter 4: Just Add Power; 4.1 Deterministic Pushdown Automata; 4.2 Nondeterministic Pushdown Automata; 4.3 Parsing with Pushdown Automata; 4.4 How Much Power?; Chapter 5: The Ultimate Machine; 5.1 Deterministic Turing Machines; 5.2 Nondeterministic Turing Machines; 5.3 Maximum Power; 5.4 General-Purpose Machines; Computation and Computability; Chapter 6: Programming with Nothing; 6.1 Impersonating the Lambda Calculus; 6.2 Implementing the Lambda Calculus; Chapter 7: Universality Is Everywhere; 7.1 Lambda Calculus; 7.2 Partial Recursive Functions; 7.3 SKI Combinator Calculus; 7.4 Iota; 7.5 Tag Systems; 7.6 Cyclic Tag Systems; 7.7 Conway's Game of Life; 7.8 Rule 110; 7.9 Wolfram's 2,3 Turing Machine; Chapter 8: Impossible Programs; 8.1 The Facts of Life; 8.2 Decidability; 8.3 The Halting Problem; 8.4 Other Undecidable Problems; 8.5 Depressing Implications; 8.6 Why Does This Happen?; 8.7 Coping with Uncomputability; Chapter 9: Programming in Toyland; 9.1 Abstract Interpretation; 9.2 Static Semantics; 9.3 Applications; Afterword; Colophon;