Introduction to Automata Theory, Languages, and Computation
(Sprache: Englisch)
This classic book on formal languages, automata theory, and computational complexity has been updated to present theoretical concepts in a concise and straightforward manner with the increase of hands-on, practical applications. This new edition comes with...
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Produktinformationen zu „Introduction to Automata Theory, Languages, and Computation “
This classic book on formal languages, automata theory, and computational complexity has been updated to present theoretical concepts in a concise and straightforward manner with the increase of hands-on, practical applications. This new edition comes with Gradiance, an online assessment tool developed for computer science. Gradiance is the most advanced online assessment tool developed for the computer science discipline. With its innovative underlying technology, Gradiance turns basic homework assignments and programming labs into an interactive learning experience for students. By using a series of "root questions" and hints, it not only tests a student's capability, but actually simulates a one-on-one teacher-student tutorial that allows for the student to more easily learn the material. Through the programming labs, instructors are capable of testing, tracking, and honing their students' skills, both in terms of syntax and semantics, with an unprecedented level of assessment never before offered. For more information about Gradiance, please visit www.aw.com/gradiance.
Inhaltsverzeichnis zu „Introduction to Automata Theory, Languages, and Computation “
Table of Contents Chapter 1 - Automata: The Methods and the Madness 1.1 Why Study Automata Theory 1.2 Introduction to Formal Proof 1.3 Additional Forms of Proof 1.4 Inductive Proofs 1.5 The Central Concepts of Automata Theory 1.6 Summary of Chapter 1 1.7 Gradiance Problems for Chapter 1 1.8 References for Chapter 1 Chapter 2 - Finite Automata 2.1 An Informal Picture of Finite Automata 2.2 Deterministic Finite Automata 2.3 Nondeterministic Finite Automata 2.4 An Application_ Text Search 2.5 Finite Automata With EpsilonTransitions 2.6 Summary of Chapter 2 2.7 Gradiance Problems for Chapter 2 2.8 References for Chapter 2 Chapter 3 - Regular Expressions and Languages 3.1 Regular Expressions 3.2 Finite Automata and Regular Expressions 3.3 Applications of Regular Expressions 3.4 Algebraic Laws for Regular Expressions 3.5 Summary of Chapter 3 3.6 Gradiance Problems for Chapter 3 3.7 References for Chapter 3 Chapter 4 - Properties of Regular Languages 4.1 Proving Languages Not to Be Regular 4.2 Closure Properties of Regular Languages 4.3 Decision Properties of Regular Languages 4.4 Equivalence and Minimization of Automata 4.5 Summary of Chapter 4 4.6 Gradiance Problems for Chapter 4 4.7 References for Chapter 4 Chapter 5 -- Context-Free Grammars and Languages 5.1 Context-Free Grammars 5.2 Parse Trees 5.3 Applications of Context-Free Grammars 5.4 Ambiguity in Grammars and Languages 5.5 Summary of Chapter 5 5.6 Gradiance Problems for Chapter 5 5.7 References for Chapter 5 Chapter 6 - Pushdown Automata 6.1 Definition of the Pushdown Automaton 6.2 The Languages of a PDA 6.3 Equivalence of PDA's and CFG's 6.4 Deterministic Pushdown Automata 6.5 Summary of Chapter 6 6.6 Gradiance Problems for Chapter 6 6.7 References for Chapter 6 Chapter 7 - Properties of Context-Free Languages 7.1 Normal Forms for Context-Free Grammars 7.2 The Pumping Lemma for Context-Free Languages 7.3 Closure Properties of Context-Free Languages 7.4 Decision Properties of CFL's 7.5 Summary of Chapter 7 7.6
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Gradiance Problems for Chapter 7 7.7 References for Chapter 7 Chapter 8 - Introduction to Turing Machines 8.1 Problems That Computers Cannot Solve 8.2 The Turing Machine 8.3 Programming Techniques for Turing Machines 8.4 Extensions to the Basic Turing Machine 8.5 Restricted Turing Machines 8.6 Turing Machines and Computers 8.7 Summary of Chapter 8 8.8 Gradiance Problems for Chapter 8 8.9 References for Chapter 8 Chapter 9 - Undecidability 9.1 A Language That Is Not Recursively Enumerable 9.2 An Undecidable Problem That Is RE 9.3 Undecidable Problems About Turing Machines 9.4 Post's Correspondence Problem 9.5 Other Undecidable Problems 9.6 Summary of Chapter 9 9.7 Gradiance Problems for Chapter 9 9.8 References for Chapter 9 Chapter 10 - Intractable Problems 10.1 The Classes P and NP 10.2 An NP-Complete Problem 10.3 A Restricted Satisfiability Problem 10.4 Additional NP-Complete Problems 10.5 Summary of Chapter 10 10.6 Gradiance Problems for Chapter 10 10.7 References for Chapter 10 Chapter 11 - Additional Classes of Problems 11.1 Complements of Languages in NP 11.2 Problems Solvable in Polynomial Space 11.3 A Problem That Is Complete for PS 11.4 Language Classes Based on Randomization 11.5 The Complexity of Primality Testing 11.6 Summary of Chapter 11 11.7 Gradiance Problems for Chapter 11 11.8 References for Chapter 11 Index
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Autoren-Porträt von John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman
Prof. Jeffrey D. Ullman, geboren 1942, ist Professor der Informatik (Emeritus). Er lehrte an der Stanford University, Californien, USA, Computerwissenschaften. Sein Interesse gilt v.a. der Datenbanktheorie und Datenbankintegration.
Bibliographische Angaben
- Autoren: John E. Hopcroft , Rajeev Motwani , Jeffrey D. Ullman
- 2006, 3rd ed., XIV, 521 Seiten, mit Abbildungen, Maße: 16,4 x 24 cm, Gebunden, Englisch
- Verlag: Addison-Wesley Longman, Amsterdam
- ISBN-10: 0321514483
- ISBN-13: 9780321514486
Sprache:
Englisch
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