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Editorial Reviews
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"Intended as an upper-level undergraduate or introductory graduate text in computer science theory," this book lucidly covers the key concepts and theorems of the theory of computation. The presentation is remarkably clear; for example, the "proof idea," which offers the reader an intuitive feel for how the proof was constructed, accompanies many of the theorems and a proof. Introduction to the Theory of Computation covers the usual topics for this type of text plus it features a solid section on complexity theory--including an entire chapter on space complexity. The final chapter introduces more advanced topics, such as the discussion of complexity classes associated with probabilistic algorithms.
Product Description
Michael Sipser's emphasis on unifying computer science theory - rather than offering a collection of low-level details - sets the book apart, as do his intuitive explanations. Throughout the book, Sipser builds students' knowledge of conceptual tools used in computer science, the aesthetic sense they need to create elegant systems, and the ability to think through problems on their own.
See all Editorial Reviews
"Intended as an upper-level undergraduate or introductory graduate text in computer science theory," this book lucidly covers the key concepts and theorems of the theory of computation. The presentation is remarkably clear; for example, the "proof idea," which offers the reader an intuitive feel for how the proof was constructed, accompanies many of the theorems and a proof. Introduction to the Theory of Computation covers the usual topics for this type of text plus it features a solid section on complexity theory--including an entire chapter on space complexity. The final chapter introduces more advanced topics, such as the discussion of complexity classes associated with probabilistic algorithms.
Product Description
Michael Sipser's emphasis on unifying computer science theory - rather than offering a collection of low-level details - sets the book apart, as do his intuitive explanations. Throughout the book, Sipser builds students' knowledge of conceptual tools used in computer science, the aesthetic sense they need to create elegant systems, and the ability to think through problems on their own.
See all Editorial Reviews
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Citations
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66
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- Modern Computer Algebra by Joachim von zur Gathen in Back Matter
- Problem Solving in Automata, Languages, and Complexity by Ding-Zhu Du in Back Matter
- Digital Watermarking: Third International Workshop, IWDW 2004, Seoul, Korea, October 30 - November 1, 2004, Revised Selected Papers (Lecture Notes in Computer Science) by Ingemar J. Cox on page 217
- Elements of Finite Model Theory (Texts in Theoretical Computer Science. An EATCS Series) by Leonid Libkin in Back Matter
- Foundations of Computational Mathematics, Santander 2005 (London Mathematical Society Lecture Note Series) by Luis M. Pardo on page 340
See all 66 books citing this book