Introduction to the theory of computation /

By: Sipser, MichaelMaterial type: TextTextPublication details: Boston, MA : Course Technology Cengage Learning, 2012Edition: 3rd EdDescription: XXII, 458 pISBN: 9781133187790; 113318779XDDC classification: 004.0151
Contents:
Introduction. PART 1: AUTOMATA AND LANGUAGES. 1. Regular Languages. 2. Context-Free Languages. PART 2: COMPUTABILITY THEORY. 3. The Church-Turing Thesis. 4. Decidability. 5. Reducibility. 6. Advanced Topics in Computability Theory. PART 3: COMPLEXITY THEORY. 7. Time Complexity. 8. Space Complexity. 9. Intractability. 10. Advanced Topics in Complexity Theory. Selected Bibliography.
Summary: The number one choice for today's computational theory course, this highly anticipated revision retains the unmatched clarity and thorough coverage that make it a leading text for upper-level undergraduate and introductory graduate students. This edition continues author Michael Sipser's well-known, approachable style with timely revisions, additional exercises, and more memorable examples in key areas. A new first-of-its-kind theoretical treatment of deterministic context-free languages is ideal for a better understanding of parsing and LR(k) grammars. This edition's refined presentation ensures a trusted accuracy and clarity that make the challenging study of computational theory accessible and intuitive to students while maintaining the subject's rigor and formalism. Readers gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs.
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Includes index

Introduction. PART 1: AUTOMATA AND LANGUAGES. 1. Regular Languages. 2. Context-Free Languages. PART 2: COMPUTABILITY THEORY. 3. The Church-Turing Thesis. 4. Decidability. 5. Reducibility. 6. Advanced Topics in Computability Theory. PART 3: COMPLEXITY THEORY. 7. Time Complexity. 8. Space Complexity. 9. Intractability. 10. Advanced Topics in Complexity Theory. Selected Bibliography.

The number one choice for today's computational theory course, this highly anticipated revision retains the unmatched clarity and thorough coverage that make it a leading text for upper-level undergraduate and introductory graduate students. This edition continues author Michael Sipser's well-known, approachable style with timely revisions, additional exercises, and more memorable examples in key areas. A new first-of-its-kind theoretical treatment of deterministic context-free languages is ideal for a better understanding of parsing and LR(k) grammars. This edition's refined presentation ensures a trusted accuracy and clarity that make the challenging study of computational theory accessible and intuitive to students while maintaining the subject's rigor and formalism. Readers gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs.

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