Synopses & Reviews
Gain a clear understanding of even the most complex, highly theoretical computational theory topics in the approachable presentation found only in the market-leading INTRODUCTION TO THE THEORY OF COMPUTATION, 3E. The number one choice for today's computational theory course, this revision continues the book's well-know, approachable style with timely revisions, additional practice, 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. You 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. INTRODUCTION TO THE THEORY OF COMPUTATION, 3E's comprehensive coverage makes this a valuable reference for your continued studies in theoretical computing.
"The text meets my objectives very well. The author presents the material in an appealing manner, making a hard subject accessible and intuitive to the students. He manages to do that while maintaining the rigor and formalism that the subject warrants. The book has a lot of information packed in it, and can serve as a reference book for students interested in research in theoretical CS."
"As one of my students puts it, the book is 'fun to read and helps him learn the subject better'."
"This is a model for readability, with sensitivity for what students find difficult."
"Excellent prose (simple and succinct) with very good diagrams. It is by far the best presentation of automata in the business."
About the Author
Michael Sipser has taught theoretical computer science and mathematics at the Massachusetts Institute of Technology for the past 32 years. He is a Professor of Applied Mathematics, a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), and the current head of the mathematics department. He enjoys teaching and pondering the many mysteries of complexity theory.
Table of 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.