Introduction to the Theory of Computation

This is a book I would recommend to third year university computer science and third year university pure mathematics students. Rather terse in style densely packed with challenging content, I really will have to take time to read it carefully to fully appreciate it. In my Bachelor of Science at the University of Melbourne years ago I studied some related content in a subject entitled 618-341 Mathematical Logic, and did not take the computer science subject 622-301 Theory Of Computation. Now, from the mathematician's point of view finitism is irrelevant it's a matter of axiom systems being consistent and proving things. The Godel number encoding of theorems and interiority arguments and clever free variable substitution arguments together with model theory were used to establish as true many powerful results ... I note that the terminology has changed since 1982; what was called then 'a recursive formula' is now called Turing decidable and what was called then 'a recursively enumerable formula' is now called 'Turing recognizable'. For example, this author would regard a Turing machine that took a blank tape and churned out the binary representation of pi 3.14159265358979323846 etc in some tape representation to an infinite number of places as a Turing machine that loops, even if such a Turing machine was reasonably well behaved in terms of its generally moving forwards ... This begs the question of real number representation; the bit string 0.11111111111 ... is essentially the same real value as 1.0000000000 ... This suggests to me that Turing theory has taken a more finitistic turn; whether this is to avoid paradoxes recently found I haven't worked out yet. In the real world with its quantum mechanics randomness and lack of apparent finititude it's quite concievable that a multi-tape Turing machine (as described in outline in section 3.2 p176ff) device could resolve a real number function evaluation so as to avoid a value ending in an infinite series of 1's that rightly should be rounded up, and store the real value as a constant in some 'set' device for storing real numbers ... However till we know more about the real truths underlying physics this is mere speculation ... There are a lot of topics that are quite new to me. For example, P less than NP less than PSPACE less than NPSPACE less then EXPTIME seems a rather more complex hypothesis regarding algorithms and their expected time to complete than I've met in other works ... Reading this section I hope will prove rewarding ... Overall it seems that the field has moved on since 1982 in many a way and I hope this book enables me to refresh my knowledge with the latest results. An excellent treatment of the whole field of theory of computation. The only criticism I can think to make is that this work seems to have a finitistic philosophy rather than a mathematical Platonist philosophy ... but then this is essential to the computer science approach rather than a pure mathematical one ...

This is a brilliantly paced and accessible treatment of relatively complex topics.

I purchased this book on the advice of my PhD advisor as an additional resource for a formal language and automata theory course. It is not the textbook for the course I am in, but it could/should be. Prof. Sipser breaks down the subject clearly and when used with the recorded lectures from MIT available for free online, it's a fantastic resource for enriching understanding of the fundamentals of theoretical computer science.

errata not corrected, even the print number shows the book was recently printed. What is the point to repeat the same error? are we not expect the publisher to correct the errata in every new print of the book anymore?

This is a great intro to complexity theory, though expensive for my tastes. I bought it for an autonama class, never read it during the class, but came back to it for the special topics. This only dips into the special topics, but introduces many of the important classes, and their relation to other complexity classes. Such classes as L, BPP, IP, Alternating, NC, and of course P, NP, exptime, PSPACE, and more. It is very well written. It ussually explains the proof ideas before starting, and gives detailed proofs. If you can afford it, this book makes a great intro to complexity theory. However, this is an intro. This book does not discuss advanced topics in depth, just enough to understand the most common comexity classes and their known relationships.

This is a very practical book as well as theoretical. The exercises are great and help reinforce the material. I used this on the job to learn parser theory. It helped me implement an ANTLR parser for SQL. There is nothing more practical than a good theory. The writing is crisp, clear, and the theory easy to follow because of the book's excellent use of examples and diagrams. I highly recommend this book, not just to students taking a course, but for practitioners working in industry. It was expensive, but well worth the price.

Sipser is probably a genius, so I have to give him credit where credit is due. He knows his material inside and out. My criticism of his book is more of the way it's being taught in colleges rather than the quality of the book. The book itself is packed to the brim with more material than you could probably use in two semesters of classes. My class covered only part of the book in one semester. I think only the basics of this class should be taught on the undergraduate level: state machines, context-free languages, turing machines, and a few other things. The high-level proofs and harder material should be reserved for a graduate-level class, not for undergraduates. IMO, most CS graduates will never see hide nor hair of most of the material in this book in their entire careers, so why punish them with it?

One of the best books ever written on the theory of computation. I started seeking different theory of computation books when taking a theory of computation class last semester since I found the other text that we were using so confusing that I felt compelled to seek further explanation elsewhere. I found the previous edition of this book in my school's library and was stunned at how thoroughly this book explained the topics which were confusing me in the required class text. After the semester was over I knew I needed to have this book for my collection. I sold back the text I bought for class and bought this new edition. I am absolutely thrilled with the purchase. The material in this book is extremely dense, but all of the topics covered are extremely well covered. I highly suggest purchasing this book if you are interested in the material or are taking a theory of computation class, even if the suggested text is a different book.

The book is well written, covers FA to Complexity classes and all with nice details. The proofs and language are nice. Exercises are a notch above but worth doing

One of the few university books I can actually read

Great book to get a broad, yet deep introduction to the theory of computation.

Apart from CS lectures, this book is one of the best books that is written for anyone who wants to learn more about computation. I believe this is a book that is hidden unlike D. Knuth’s series.

too mathematical