Compilers: Principles, Techniques and Tools, known to professors, students, and developers worldwide as the "Dragon Book," is available in a new edition. Every chapter has been completely revised to reflect developments in software engineering, programming languages, and computer architecture that have occurred since 1986, when the last edition published. The authors, recognizing that few readers will ever go on to construct a compiler, retain their focus on the broader set of problems faced in software design and software development.
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From the Back Cover
This book provides the foundation for understanding the theory and pracitce of compilers. Revised and updated, it reflects the current state of compilation. Every chapter has been completely revised to reflect developments in software engineering, programming languages, and computer architecture that have occurred since 1986, when the last edition published. The authors, recognizing that few readers will ever go on to construct a compiler, retain their focus on the broader set of problems faced in software design and software development. Computer scientists, developers, and aspiring students that want to learn how to build, maintain, and execute a compiler for a major programming language.
About the Author
Alfred V. Aho is Lawrence Gussman Professor of Computer Science at Columbia University. Professor Aho has won several awards including the Great Teacher Award for 2003 from the Society of Columbia Graduates and the IEEE John von Neumann Medal. He is a member of the National Academy of Engineering and a fellow of the ACM and IEEE.
Monica S. Lam is a Professor of Computer Science at Stanford University, was the Chief Scientist at Tensilica and the founding CEO of moka5. She led the SUIF project which produced one of the most popular research compilers, and pioneered numerous compiler techniques used in industry.
Ravi Sethi launched the research organization in Avaya and is president of Avaya Labs. Previously, he was a senior vice president at Bell Labs in Murray Hill and chief technical officer for communications software at Lucent Technologies. He has held teaching positions at the Pennsylvania State University and the University of Arizona, and has taught at Princeton University and Rutgers. He is a fellow of the ACM.
Jeffrey Ullman is CEO of Gradiance and a Stanford W. Ascherman Professor of Computer Science at Stanford University. His research interests include database theory, database integration, data mining, and education using the information infrastructure. He is a member of the National Academy of Engineering, a fellow of the ACM, and winner of the Karlstrom Award and Knuth Prize.
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Amazon.com:
3.7 out of 5 stars
18 reviews
138 of 147 people found the following review helpful
3.0 out of 5 stars
Warmed over ghost of past excellence
May 18 2007
By Jason Evans
- Published on Amazon.com
Format:Hardcover
I spent some serious quality time with the first edition (the "red dragon book"), in three main episodes over the past dozen years: 1) undergraduate compilers class, 2) industry project, and 3) parser generator implementation. During all three episodes, I was disappointed in various ways, though there is no denying that the book contains a wealth of information. As an undergraduate, I found the book somewhat impenetrable. When in industry, I found the book too abstract. When implementing a parser generator, I discovered that the book excludes important research results with regard to LR parser generation. It is the last disappointment that I will focus on.
The book presents parser generation in layers of increasing complexity, from SLR to LR to LALR, where LALR is presented as the penultimate algorithm, though LALR parsers can only handle a subset of the grammars that LR can handle. The justification for this is that the original Knuth LR algorithm is intractable for large grammars. However, an efficient, fully correct, approach for LR parser generation was published in 1977, and on top of that it appears easier to implement than efficient LALR parser generation! The red dragon book's original authors simply cannot have been unaware of this research result, but I suspect that they elected to warm over the "green dragon book" (published in 1977) rather than incorporate the state of the art as of 1986 into the "red dragon book". Now here we are another 20 years later, and as near as I can tell from reading through available online information, the "purple dragon book" is perpetuating this omission. The result of the red dragon book is that we have an entire generation of computer scientists who have been mislead to think that LALR is somehow superior to LR, and the purple dragon book is setting things up for yet another generation to be mislead.
The book presents parser generation in layers of increasing complexity, from SLR to LR to LALR, where LALR is presented as the penultimate algorithm, though LALR parsers can only handle a subset of the grammars that LR can handle. The justification for this is that the original Knuth LR algorithm is intractable for large grammars. However, an efficient, fully correct, approach for LR parser generation was published in 1977, and on top of that it appears easier to implement than efficient LALR parser generation! The red dragon book's original authors simply cannot have been unaware of this research result, but I suspect that they elected to warm over the "green dragon book" (published in 1977) rather than incorporate the state of the art as of 1986 into the "red dragon book". Now here we are another 20 years later, and as near as I can tell from reading through available online information, the "purple dragon book" is perpetuating this omission. The result of the red dragon book is that we have an entire generation of computer scientists who have been mislead to think that LALR is somehow superior to LR, and the purple dragon book is setting things up for yet another generation to be mislead.
29 of 30 people found the following review helpful
2.0 out of 5 stars
DO NOT BUY the kindle version - many errors!
Jan 13 2012
By Erich Blume
- Published on Amazon.com
Format:Kindle Edition|Amazon Verified Purchase
Aho, Ullman et. al's "Compilers" is a fantastic book and well worth studying for all computer programmers - implementing a compiler compiler will yield tangental benefits to anyone who writes programs for a living or for fun.
However, the Amazon Kindle edition of this book is *awful*. First and foremost, I discovered at least one error in an algorithm that is not present in the standard edition that causes the book's proposed algorithms to be incorrect (in this case, it was algorithm 4.31 - in step 1, you should compute FIRST(alpha), not FIRST(A).)
On top of that, there are spacing issues and font issues throughout the book. It appears that in many places where the standard edition had a word separated across lines, the Kindle edition merely has that word split in two with a space between its halves. Worse, the font choice used to typeset algorithms doesn't easily distinguish many greek lowercase letters from their modern English equivalents, the result being that it is fiendishly difficult to understand some algorithms (the book uses greek letters to indicate a 'sentential form', so they appear a *lot* and tend to be right next to their modern equivalents.)
In other words, I would give Compilers (the Standard edition) a 5/5 (or maybe a 4/5 - it could stand to use a bit more real-world code), but this Kindle edition is rubbish and you SHOULD NOT BUY.
However, the Amazon Kindle edition of this book is *awful*. First and foremost, I discovered at least one error in an algorithm that is not present in the standard edition that causes the book's proposed algorithms to be incorrect (in this case, it was algorithm 4.31 - in step 1, you should compute FIRST(alpha), not FIRST(A).)
On top of that, there are spacing issues and font issues throughout the book. It appears that in many places where the standard edition had a word separated across lines, the Kindle edition merely has that word split in two with a space between its halves. Worse, the font choice used to typeset algorithms doesn't easily distinguish many greek lowercase letters from their modern English equivalents, the result being that it is fiendishly difficult to understand some algorithms (the book uses greek letters to indicate a 'sentential form', so they appear a *lot* and tend to be right next to their modern equivalents.)
In other words, I would give Compilers (the Standard edition) a 5/5 (or maybe a 4/5 - it could stand to use a bit more real-world code), but this Kindle edition is rubbish and you SHOULD NOT BUY.
48 of 55 people found the following review helpful
4.0 out of 5 stars
Is the reputaton deserved?
Jan 31 2007
By A Student
- Published on Amazon.com
Format:Hardcover
This book has the reputation as being THE book on compilers. I'll grant that. It covers everything and the kitchen sink, at a theoretical level. This is NOT the book on implementation details. Without prior exposure to the basic principals and problems in compiler implemenation, it can be difficult to see why the theory, as presented, is relavent. Why is left recursion bad? What good are handles? How is the type system significant? How do symbol tables relate to scoping? This stuffs in there, but if one is not expecting it, one won't appreciate the terse presentation. But that's the kind of learner I am, I have to know why something is relavent before I get it. So, I don't recommend this book as a first book on languages and compilers.
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3.7 out of 5 stars
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