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Theory of Computing: A Gentle Introduction

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Theory of Computing: A Gentle Introduction

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About

Features

  • “Lead by example” approach.
    • Fundamental theorems are arrived at as generalizations of examples. Ex.___

  • Fundamental concepts behind computation are taught.
    • Explains pattern matching, parsing, and helps to identify unsolvable problems. Ex.___

  • Hundreds of exercises marked according to the level of difficulty.
    • Provides students ample opportunity to apply concepts. Ex.___

  • Hundreds of illustrations.
    • Enhance understanding. Ex.___

  • Only algorithmic proofs are given in the text—Other proof details are left to exercises.
    • Allows readers to calibrate the mathematical depth they want to pursue. Ex.___

Description

  • Copyright 2001
  • Pages: 207
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-027961-7
  • ISBN-13: 978-0-13-027961-3

This book focuses on fundamental issues of computation. The readers can master the content and gain lasting perspective from which to understand computers by carefully worked out examples, illustrations, and algorithmic proofs. KEY TOPICS: Teaches the fundamental concepts behind computation. Hundreds of exercises marked according to the level of difficulty provide readers ample opportunity to apply concepts. Hundreds of illustrations which enhance understanding. Only algorithmic proofs are given in the text allowing readers to calibrate the mathematical depth they want to pursue. MARKET: Appropriate for upper division undergraduate and graduate level courses in Computer Science Theory, Theory of Computation, and Automata and Formal Language Theory.

Sample Content

Table of Contents

(NOTE: Each chapter concludes with Exercises.)

1. Introduction.

Why Study the Theory of Computing? What Is Computation? The Contents of This Book. Mathematical Preliminaries.



2. Finite Automata.

Deterministic Finite Automata. Nondeterministic Finite Automata. Determinism versus Nondeterminism. Regular Expressions. Nonregular Languages. Algorithms for Finite Automata. The State Minimization Problem.



3. Context Free Languages.

Context-Free Grammars. Parsing. Pushdown Automata. Languages and Automata. Closure Properties. Languages That Are Not Context-Free. Chomsky Normal Form. Determinism.



4. Turing Machines.

Definition of a Turing Machine. Computations by Turing Machines. Extensions of Turing Machines. Nondeterministic Turing Machines. Turing Enumerable Languages.



5. Undecidability.

The Church-Turing Thesis. Universal Turing Machines. The Halting Problem. Undecidable Problems.



6. Computational Complexity.

The Definition and the Class P. The Class N P. N P-Completeness.



References.


List of Symbols.


Index.

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