Rating: 
Summary: Excellent book
Review: I must concur with the majority of other reviewers, this is an excellent book. It was the textbook we used in a course I followed on complexity theory at university and I found the explanations of concepts remarkably clear and concise. Michael Sipser is one of the few authors of theoretical books around who has a firm and even natural grasp of writing text that explains completely, gets the point across easily and does so without drowning the reader in the sorts of details that should be banished to examples and sidenotes, but that find their way into the main text of so many other books. Highly recommended (by me, at least).
Rating:
Summary: Fantastic book to introduce theory of computation.
Review: I think that this book is by far the best introductory text on theory of computation and complexity that I have read so far. I would recommend the aho ulmann book as a companion after having gone through this book to strengthen your knowledge. But, this book introduces stuff like never before. Simply amazing.. buy it even if you are planning to take a course and the instructor is using some other textbook, its that good!!
Rating:
Summary: Life saver
Review: I used this book as a supplement in a college class. It was VERY helpful in understanding computability theory, Turing Machines, and finite languages. Everything is put forth in a straightforward easy to understand manner. The main thing that made this book stand out above the rest is that it's written in language that is easily understood, while other text books burden you down with a multitude of symbols and equations. The proof ideas are very helpfull in understanding concepts Thank you Mr. Sipser!
Rating:
Summary: You will have trouble putting this book down!
Review: I was extremely surprised at how enjoyable this book was to read. Who would have thought that a book explaining a difficult topic can flow with such ease and actually be exciting to read. It is concise but NOT to a fault. There are plenty of examples and the author makes everything easy to understand. FINALLY! A complex subject explained with grace and simplicity. Thank you Michael Sipser!!
Rating:
Summary: inspired
Review: I was trying to understand quantum computing and i read
this book as a preliminary material on classical computation. I found it very clear, concise and informative. It is highly
recommended for combining simplicity and depth. I found one problem though; the book has three great
divisions: computability, complexity automata. There is no doubt that in modern computing, coding theory is considered as important as the previous three branches.
I think that the author should augment his book with
a division on coding (information, error-correction, cryptography) in order to give a complete theory of computing.
Rating: 
Summary: Terrible, Unbelievably Confusing
Review: I'm confused about how this book got such a good rating. Hmmm. Personally, I think it is the absolute worst book that I have ever read, or should I say "tried" to read. Seldom can I read a page (after chapter 2), or even a paragraph for that matter, without having to read it again . . . and again, trying to figure out what Sipser is trying to say. The book is incredibly difficult to read, has very few "down to earth" examples, and many important topics are ommited - left for the reader as "exercises." For those of you who think I am just a slow learner, my gpa is in excess of 3.9 after more than 5 years of college (I am working on a second degree in Computer Science). If I didn't have to read this book for my Theory class at UGA, I would certainly either send it back for a refund, or throw it in the circular filing cabinet, where I think it belongs. It is obvious that my instructor has never read this book!
Rating:
Summary: Probably the best computation theory text for students
Review: In my opinion this is one of the best written books in the CS discipline, a must have for every computer scientist. The topics are presented clearly, with emphasis in understanding the concept, which most of the times is missed in other books amongst the equation line up of theorems that nobody will further investigate. Probably not comprehensive enough for a researcher of the field, but definately the right text to start on the subject and comprehend the basics, which is more than most students in the CS field will need.
Rating:
Summary: Excellent for Pre- to Post Grad Computer Science!
Review: It has been a privelage to use Sipser's book in 1998, during my final year - Bachelor of Science (Computer Science, Course: 'Formal Languages'). The book covers the subject of 'Formal Languages' brilliantly, using an extremely logical structure, easy-to-follow proofs, helpful Proof Ideas and a colourful text layout clearly indicating the different aspects of the subject matter. The text IS as good as the best reviews make it out to be (ignore the single 1-star rating). Unfortunately, I do not have the book with me now, otherwise my praise would have taken up the whole 1000 word maximum of the review.
Rating:
Summary: Great book
Review: Michael Sipser has an undoubted gift for writing on this subject. The book is a coincise and easy read. But be cautious, this doesn't mean superficial and poor. The book contains all the material needed for a good course on Theory of Computation and Complexity. Perhaps it has not plenty of details like other books as Hopcroft & Ullman or Kozen or Papadimitrou, but don't underestimate the vastity of the treated topics, what is important is that every time you finish a chapter, you have the sensation that you've learned what you should have to. And probably you did due to Sipser's writing style, provided that you can afford to skip "some" more detailed/advanced topics. Or you might just be looking for some further stuff like Myhill-Nerode or Rabin-Shepherdson theorems or Chomsky Hierarchy for example, and you would have to look elsewhere for them. However, I've never been told that the best book is the most complete one. As long as I've learned, the best book is the one that best fits your needs, and that fitting these needs it suceeds to transmit the knowledge you're looking for in an effective way. That's why if this stuff is not required by your course, you would be perfectly fine with this book in your hands. Proofs on theorems are given virtually always in two steps: first you're presented with the idea that lies behind the proof, and then you get the proof itself in a more rigorous fashion. Again, Sipser strikes here because it's harder NOT to understand one of his proofs than the contrary simply because the presentation is always clear and understandable.
As a matter of fact, Sipser (as he point out in the preface) almost always avoid to overload proofs given by construction with more rigorous following proofs (e.g. induction on the constructed machine to prove its equivalence with ...). This has a strong impact on the attention you can keep when studying throghout a chapter: avoiding to dive into tedious details when the proof (by construction) has been clear enough help to keep you attention high and boredom away. This is a way of learning, an effective way. Sipser uses sometime a notation that's different from the somewhat standard one (e.g. the description of delta or transition function on various machines), but it is coherent throughout the whole book, and that's what does count, together with the note that this notation is noway more complex or hard to understand than the "standard" one. Should I name two books on Theory of Computation (not Complexity), one just a little less rigorous and one just a little more rigorous than this, I would suggest Coehn's "Introduction to computer Theory" and Kozen's "Automata and Computability" respectively. My conclusion is that this is a great book, worth the price (especially if confronted with others ...) and a stable place in my bookshelf.
Rating:
Summary: Second printing excellent
Review: One of the best textbooks I've ever read, in any subject. Michael Sipser having a bad day is the second best teacher I've ever had. The second printing corrects the healthy share of errata from the first. Note that the author maintains an active list of active errata on his homepage.
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