An introduction to formal languages and automata / Peter Linz.

By: Linz, PeterMaterial type: TextTextPublication details: Sudbury, Mass. : Jones and Bartlett Publishers, c2006Edition: 4th edDescription: xiii, 415 p. : ill. ; 25 cmISBN: 0763737984 (casebound); 9780763737986Subject(s): Formal languages | Machine theoryDDC classification: 005.13/1
Contents:
Introduction to the Theory of Computation 1.1 Mathematical Preliminaries and Notation Sets Functions and Relations Graphs and Trees Proof Techniques 1.2 Three Basic Concepts Languages Grammars Automata 1.3 Some Applications* Finite Automata 2.1 Deterministic Finite Accepters Deterministic Accepters and TVansition Graphs Languages and Dfa's Regular Languages 2.2 Nondeterministic Finite Accepters Definition of a Nondeterministic Accepter Why Nondeterminism? 2.3 Equivalence of Deterministic and Nondeterministic Finite* Accepters 2.4 Reduction of the Number of States in Finite Automata* . 3 Regular Languages and Regular Grammars 3.1 Regular Expressions Formal Definition of a Regular Expression Languages Associated with Regular Expressions 3.2 Connection Between Regular Expressions and Regular Languages Regular Expressions Denote Regular Languages Regular Expressions for Regular Languages Regular Expressions for Describing Simple Patterns 3.3 Regular Grammars Right- and Left-Linear Grammars Right-Linear Grammars Generate Regular Languages Right-Linear Grammars for Regular Languages Equivalence of Regular Languages and Regular Grammars . 4 Properties of Regular Languages 4.1 Closure Properties of Regular Languages Closure under Simple Set Operations Closure under Other Operations 4.2 Elementary Questions about Regular Languages 4.3 Identifying Nonregular Languages Using the Pigeonhole Principle A Pumping Lemma 5 Context-Free Languages 5.1 Context-Free Grammars Examples of Context-Free Languages Leftmost and Rightmost Derivations Derivation Trees Relation between Sentential Forms and Derivation Trees 5.2 Parsing and Ambiguity Parsing and Membership Ambiguity in Grammars and Languages 5.3 Context-Free Grammars and Programming Languages 6 Simplification of Context-Free Grammars and Normal Forms 6.1 Methods for Transforming Grammars A Useful Substitution Rule Removing Useless Productions Removing A-Productions Removing Unit-Productions 6.2 Two Important Normal Forms Chomsky Normal Form Greibach Normal Form 6.3 A Membership Algorithm for Context-Free Grammars* 7 Pushdown Automata 7.1 Nondeterministic Pushdown Automata Definition of a Pushdown Automaton The Language Accepted by a Pushdown Automatoi 7.2 Pushdown Automata and Context-Free Languages Pushdown Automata for Context-Free Languages Context-Free Grammars for Pushdown Automata 7.3 Deteritiinistic Pushdown Automata and Deterministic Context-Free Languages 7.4 Grammars for Deterministic Context-Free Languages* 8 Properties of Context-Free Languages 8.1 Two Pumping Lemmas A Pumping Lemma for Context-Free Languages A Pumping Lemma for Linear Languages 8.2 Closure Properties and Decision Algorithms for Context- Free Languages Closure of Context-Free Languages Some Decidable Properties of Context-Free Languages 9 Turing Machines 9.1 The Standard Turing Machine Definition of a Turing Machine Turing Machines as Language Accepters Turing Machines as Transducers 9.2 Combining Turing Machines for Complicated Tasks 9.3 Turing's Thesis 10 Other Models of Turing Machines 10.1 Minor Variations on the Turing Machine Theme Equivalence of Classes of Automata Turing Machines with a Stay-Option Turing Machines with Semi-Infinite Tape The Off-Line Turing Machine 10.2 Turing Machines with More Complex Storage Multitape Turing Machines Multidimensional Turing Machines 10.3 Nondeterministic Turing Machines 10.4 A Universal Turing Machine 10.5 Linear Bounded Automata 11 A Hierarchy of Formal Languages and Automata 11.1 Recursive and Recursively Enumerable Languages Languages That Are Not Recursively Enumerable A Language That Is Not Recursively Enumerable A Language That Is Recursively Enumerable but Not Recursive 11.2 Unrestricted Grammars 11.3 Context-Sensitive Grammars and Languages Context-Sensitive Languages and Linear Bounded Automata Relation Between Recursive and Context-Sensitive Languages 11.4 The Chomsky Hierarchy 12 Limits of Algorithmic Computation 12.1 Some Problems That Cannot Be Solved by Turing Machines Computability and Decidability The Turing Machine Halting Problem Reducing One Undecidable Problem to Another 12.2 Undecidable Problems for Recursively Enumerable Languages 12.3 The Post Correspondence Problem 12.4 Undecidable Problems for Context-Free Languages 12.5 A Question of Efficiency 13 Other Models of Computation 13.1 Recursive Functions Primitive Recursive Functions Ackermann's Function p Recursive Functions 13.2 Post Systems 13.3 Rewriting Systems Matrix Grammars Markov Algorithms L-Systems 14 An Overview of Computational Complexity 14.1 Efficiency of Computation 14.2 Turing Machine Models and Complexity . 14.3 Language Families and Complexity Classes 14.4 The Complexity Classes P and NP 14.5 Some NP Problems 14.6 Polynomial-Time Reduction 14.7 NP-Completeness and an Open Question
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Includes bibliographical references (p. 409) and index.

Introduction to the Theory of Computation
1.1 Mathematical Preliminaries and Notation
Sets
Functions and Relations
Graphs and Trees
Proof Techniques
1.2 Three Basic Concepts
Languages
Grammars
Automata
1.3 Some Applications*
Finite Automata
2.1 Deterministic Finite Accepters
Deterministic Accepters and TVansition Graphs
Languages and Dfa's
Regular Languages
2.2 Nondeterministic Finite Accepters
Definition of a Nondeterministic Accepter
Why Nondeterminism?
2.3 Equivalence of Deterministic and Nondeterministic Finite*
Accepters
2.4 Reduction of the Number of States in Finite Automata* .
3 Regular Languages and Regular Grammars
3.1 Regular Expressions
Formal Definition of a Regular Expression
Languages Associated with Regular Expressions
3.2 Connection Between Regular Expressions and Regular
Languages
Regular Expressions Denote Regular Languages
Regular Expressions for Regular Languages
Regular Expressions for Describing Simple Patterns
3.3 Regular Grammars
Right- and Left-Linear Grammars
Right-Linear Grammars Generate Regular Languages
Right-Linear Grammars for Regular Languages
Equivalence of Regular Languages and Regular
Grammars .
4 Properties of Regular Languages
4.1 Closure Properties of Regular Languages
Closure under Simple Set Operations
Closure under Other Operations
4.2 Elementary Questions about Regular Languages
4.3 Identifying Nonregular Languages
Using the Pigeonhole Principle
A Pumping Lemma
5 Context-Free Languages
5.1 Context-Free Grammars
Examples of Context-Free Languages
Leftmost and Rightmost Derivations
Derivation Trees
Relation between Sentential Forms and Derivation
Trees
5.2 Parsing and Ambiguity
Parsing and Membership
Ambiguity in Grammars and Languages
5.3 Context-Free Grammars and Programming Languages
6 Simplification of Context-Free Grammars and Normal
Forms
6.1 Methods for Transforming Grammars
A Useful Substitution Rule
Removing Useless Productions
Removing A-Productions
Removing Unit-Productions
6.2 Two Important Normal Forms
Chomsky Normal Form
Greibach Normal Form
6.3 A Membership Algorithm for Context-Free Grammars*
7 Pushdown Automata
7.1 Nondeterministic Pushdown Automata
Definition of a Pushdown Automaton
The Language Accepted by a Pushdown Automatoi
7.2 Pushdown Automata and Context-Free Languages
Pushdown Automata for Context-Free Languages
Context-Free Grammars for Pushdown Automata
7.3 Deteritiinistic Pushdown Automata and Deterministic
Context-Free Languages
7.4 Grammars for Deterministic Context-Free Languages*
8 Properties of Context-Free Languages
8.1 Two Pumping Lemmas
A Pumping Lemma for Context-Free Languages
A Pumping Lemma for Linear Languages
8.2 Closure Properties and Decision Algorithms for Context-
Free Languages
Closure of Context-Free Languages
Some Decidable Properties of Context-Free Languages
9 Turing Machines
9.1 The Standard Turing Machine
Definition of a Turing Machine
Turing Machines as Language Accepters
Turing Machines as Transducers
9.2 Combining Turing Machines for Complicated Tasks
9.3 Turing's Thesis
10 Other Models of Turing Machines
10.1 Minor Variations on the Turing Machine Theme
Equivalence of Classes of Automata
Turing Machines with a Stay-Option
Turing Machines with Semi-Infinite Tape
The Off-Line Turing Machine
10.2 Turing Machines with More Complex Storage
Multitape Turing Machines
Multidimensional Turing Machines
10.3 Nondeterministic Turing Machines
10.4 A Universal Turing Machine
10.5 Linear Bounded Automata
11 A Hierarchy of Formal Languages and Automata
11.1 Recursive and Recursively Enumerable Languages
Languages That Are Not Recursively Enumerable
A Language That Is Not Recursively Enumerable
A Language That Is Recursively Enumerable but Not
Recursive
11.2 Unrestricted Grammars
11.3 Context-Sensitive Grammars and Languages
Context-Sensitive Languages and Linear Bounded
Automata
Relation Between Recursive and Context-Sensitive
Languages
11.4 The Chomsky Hierarchy
12 Limits of Algorithmic Computation
12.1 Some Problems That Cannot Be Solved by Turing
Machines
Computability and Decidability
The Turing Machine Halting Problem
Reducing One Undecidable Problem to Another
12.2 Undecidable Problems for Recursively Enumerable
Languages
12.3 The Post Correspondence Problem
12.4 Undecidable Problems for Context-Free Languages
12.5 A Question of Efficiency
13 Other Models of Computation
13.1 Recursive Functions
Primitive Recursive Functions
Ackermann's Function
p Recursive Functions
13.2 Post Systems
13.3 Rewriting Systems
Matrix Grammars
Markov Algorithms
L-Systems
14 An Overview of Computational Complexity
14.1 Efficiency of Computation
14.2 Turing Machine Models and Complexity .
14.3 Language Families and Complexity Classes
14.4 The Complexity Classes P and NP
14.5 Some NP Problems
14.6 Polynomial-Time Reduction
14.7 NP-Completeness and an Open Question

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