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on 24 January 2003
This is a good book - but as a revision of a much-revered classic of
the field, it's a bit of a disappointment.
Hopcroft & Ullman wrote the classic text way back in 1969, and then
revised it in 1979. It was pretty much the standard text the world
over for an introduction to the theory of computation.
But over the last two decades, more and more people have been studying
Computer science, and many of them have no time for theory and
formalism and all the 'dry stuff' ..........
The authors point out that because of such reasons and also because
nowadays there's little research in the theory of computation per se,
and more in its applications, they've written a book to cater to today's
students.
Which, in other words, means they've simplified the presentation, tried
to provide intuition whenever possible, given lots more examples and
done away with some of the more difficult material.
This approach puts the book into direct competition with Michael Sipser's
excellent 'Introduction to the theory of computation', a contest it
cannot win, though it might be a respectable second.
Almost all topics are motivated by giving examples of how they're
related to applications in the 'real world', and similar to
Sipser's 'proof idea' approach, the authors first present a topic
informally and then formally, thus gently leading the reader to
the formal proofs.
This book sets out to do pretty much the same as what Sipser's book
does, ie to provide a readable, user-friendly introduction to the
theory of computation with lots of examples and intuitive approach
to problems wherever possible, but Sipser's already done an
'optimal' job.
Moreover, this book tries to be 'chatty', which i'm afraid is just
not the authors' style - the 'economy of expression', which has long
which has long been the hallmark of the legendary textbooks by
Aho,Hopcroft and Ullman, is sadly missing here.
Which means that this may not be the book for you if you're pressed
for time - but on the other hand, if you want to led gently to the
proofs and results with lots of examples and motivation, then this
might be just the book for you.
So all in all, it definitely worth a read - in fact, i'd say
it's still among the top textbooks around.
In fact, i would suggest that you read both this and Sipser, if you
have the time. Otherwise Sipser's the better choice for most of the
part, though it may not cover all the topics you need.
And if you're comfortable with a terse, concise & rigorous
presentation, then the earlier edition of this book is still
unbeatable - and you'll surely need it if you want to pursue research
in this area.
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on 23 November 2013
This edition of this great book have almost all the images wrong. I have read it until page 70 and I lost most of the time trying to understand the examples until I realize, comparing with regular editions, that I was reading descriptions that don't have nothing to do with the images.....
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on 14 April 1999
A predecessor of the book was published in 1969 titled "Formal Languages and Their Relation to Automata." It was re-written in 1979. This is a classical textbook for last year undergraduate students or postgraduate students in computer science, especially those who are going to deal with computer languages, artificial intellegence, compiler design, computational complexity and so on. One of the author, J. E. Hopcroft, is the Turing Award winner of 1987.
I have both versions of the book and I'd like recommend every computer science student spend some time on reading it.
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on 30 June 1999
The book is a great book if you are a beginner in automata theory. The exercises are also very good and the book makes your fundamentals very strong. It is a must for any student of theoretical computer science.
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on 5 October 1998
This slim volume is the standard reference for research in automata theory, languages, and computation (especially regular and context-free languages). For that, it gets five stars. As a textbook for students, however, it is dense, uneven, and confusing throughout. Generations of novice computer scientists have been soured forever on theory by being forced to endure this book in their undergraduate- and graduate-level theory courses.
Conclusion: buy this book and keep it on your shelf, with the other essential references, but if you want to *learn* the material, look elsewhere -- for example, Michael Sipser's excellent new textbook, _Introduction to the Theory of Computation_.
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on 4 November 2013
This is an Indian print of this classic text. The quality of the paper/printing is not great, but certainly OK. And, of course, this version is MUCH cheaper than the normal version.

The book itself is written in a style that spells out the proofs quite patiently - it's quite easy to follow in comparison with other books I have on the same subject.
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on 4 December 1998
A classic text on the subject and a must have for any student of computer science. If you have taken a course in discrete math as taught by most CS departments then this book should pose no overwhelming challenges. It also makes a great companion to Aho, Sethi and Ullman's "Dragon" book.
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on 27 February 2003
I've just passed my exam on Theory of Computation, and I've used both editions of this text. Frankly speaking, I couldn't choose one of the two should I keep only one of them.
Whereas the first was full of strict formalism, the second has traded this for a more discursive approach. Whereas the first reported theorems name (of their authors), the second has traded this for a richer bibliography at the end of the chapters. And more objectively, the first edition covered more "classical" topics with shorter treatments than the second, but this last treats survived topics with richer details (starting from the first chapter on mathematical basis for the course) and with updated examples of applications (XML and Markup Languages, e-commerce for DFA, etc).
This said, you know why I can't decide. A discursive approach is of course always desiderable, especially if you're completely new to a subject, but a strong notation is helpful in my mind because it improves communication and removes ambiguities. Hence, the best approach would probably have been a mix of the two, or halfway the two.
As a second matter, having a rich bibliography is surely helpful both for further studies and as a reference, but it's quite tedious to look at the index and be unable to find something like "Kleene theorem": you've to dive into bibligraphy to discover that "L is an L(DFA) if and only if it also is L(REG)" is something that has been studied by Kleene.
Finally, I surely can't question the reduction of the complexity theory part since it is in the right of the authors to remove "optional topics" (if you use the book for a course on Theory of Computation only) and give a more focused target to the book, but removing stuff like the Myhill-Nerode theorem make things annoying since virtually every course on Automata theory and Computation includes it (like my one did, as well as the course on Languages and Compilers), so you have to look for it elsewhere if your only one book is this second edition.
I would give four stars, should I keep in heavy account the radical changes they made over the first edition and that includes the removal of some stuff, important on my opinion. But ... as this is just my opinion, and since it is a very well written and informative book (rich of many details that other texts lack of) and surely one of the bests in the area (I've had 4-5 books in my hands for this course), that's why I gave it 5 stars.
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on 11 May 2015
Received as described.
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on 22 June 2002
This books covers the basics well but in an overly formal way. Obvious facts get rigorous proof, straightforward concepts get defined by complex algebraic formula (with all sorts of obscure symbols).
This has the disadvantage of making the book hard to read, let alone understand. I've covered most of this material before but found myself having to reread sections to follow what was going on. It also means the book covers much less ground than could have been the case.
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