编译原理->nice time to spend(Compilers: Principles, Techniques, and Tools (2nd Edition))

Compilers: Principles, Techniques, and Tools (2nd Edition)

By Alfred V. Aho, Monica S. Lam, Ravi Sethi, Jeffrey D. Ullman,

Publisher: Addison Wesley
Number Of Pages: 1000
Publication Date: 2006-08-31
Sales Rank: 7660
ISBN / ASIN: 0321486811
EAN: 9780321486813
Binding: Hardcover
Manufacturer: Addison Wesley
Studio: Addison Wesley
Average Rating: 4

First introduce the summary of this book:

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.

Review:

The best for getting the theoretical foundation of compilers

This is the classical reference book for compiler design. This is not an easy text because of its heavy use of mathematical notation and the algorithms are presented only in pseudo code but you will not find a more complete collection of compiler related algorithms than in this book.

Review:

Warmed over ghost of past excellence

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.

 

Another there is a description 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.