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Modern Compiler Implementation in ML [Hardcover]

Andrew W. Appel (Author)
3.0 out of 5 stars  See all reviews (11 customer reviews)


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Book Description

0521582741 978-0521582742 December 13, 1997 Revised edition
This new, expanded textbook describes all phases of a modern compiler: lexical analysis, parsing, abstract syntax, semantic actions, intermediate representations, instruction selection via tree matching, dataflow analysis, graph-coloring register allocation, and runtime systems. It includes good coverage of current techniques in code generation and register allocation, as well as functional and object-oriented languages, that are missing from most books. In addition, more advanced chapters are now included so that it can be used as the basis for two-semester or graduate course. The most accepted and successful techniques are described in a concise way, rather than as an exhaustive catalog of every possible variant. Detailed descriptions of the interfaces between modules of a compiler are illustrated with actual C header files. The first part of the book, Fundamentals of Compilation, is suitable for a one-semester first course in compiler design. The second part, Advanced Topics, which includes the advanced chapters, covers the compilation of object-oriented and functional languages, garbage collection, loop optimizations, SSA form, loop scheduling, and optimization for cache-memory hierarchies.

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Editorial Reviews

Review

"Contains most up-to-date compiler techniques. Contains good programming assignment." Professor Zhong Shao, Yale University

Book Description

This new, expanded textbook describes all phases of a modern compiler, including current techniques in code generation and register allocation, for imperative, functional and object-oriented languages. In a concise and practical way the author describes the fundamentals of compilation and then moves on to advanced topics such as SSA form, loop scheduling, and optimization for cache-memory hierarchies. A unique feature is a compiler implementation project in ML, including front-end and 'high-tech' back-end phases.

Product Details

  • Hardcover: 548 pages
  • Publisher: Cambridge University Press; Revised edition edition (December 13, 1997)
  • Language: English
  • ISBN-10: 0521582741
  • ISBN-13: 978-0521582742
  • Product Dimensions: 9.5 x 7.7 x 1.2 inches
  • Shipping Weight: 2.4 pounds
  • Average Customer Review: 3.0 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #1,911,276 in Books (See Top 100 in Books)

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Customer Reviews

11 Reviews
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Average Customer Review
3.0 out of 5 stars (11 customer reviews)
 
 
 
 
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21 of 21 people found the following review helpful:
5.0 out of 5 stars One of the better compiler texts, July 3, 2006
This book covers a remarkably broad territory of compiler issues, with a good balance of clarity and depth. It spends long enough on each topic to work through examples of functioning code, but doesn't dwell on any for so long that the reader loses interest. A decent set of variations on language design, runtime organization, and machine architecture are also discussed and implemented.

An important caveat is that readers ought to know some dialect of ML. If not, this book does not teach it; there are alternative renditions of the same text in C and Java, but I have not read them. Apparently many reviewers find those confusing. The java rendition, for example, has many angry reviewers. Possibly disgruntled students who had a hard time with their coursework, possibly people with valid complaints about the text.

All I can say is that I quite enjoyed it, and return to it regularly for its clear presentation, when working with related algorithms.
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14 of 15 people found the following review helpful:
4.0 out of 5 stars Good, but not an introduction to either compilers or ML, November 7, 2002
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This review is from: Modern Compiler Implementation in ML (Hardcover)
Appel explains the structure of a compiler in a very clear and precise fashion, including a lot of quite modern techniques. *However* it is only clear and precise if you have a rough high-level understanding of compilers and a good knowledge of ML beforehand. (If you understand one of the two, it is an excellent book for learning the other but you will need to do some thinking for yourself.)

If you're looking to learn about compilers from the very beginning, buy something else (I liked "Crafting A Compiler" as a starting point). If you're wanting to get a lot more precise about the way you build compilers, buy this book.

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10 of 10 people found the following review helpful:
5.0 out of 5 stars Extremely valuable, but not for the faint of heart, August 1, 2007
I love this book. Having experimented with compiler construction for some time (though never seriously), and being a long-time ML user, Modern Compiler Implementation in ML was the perfect companion to my compiler-construction project. I largely ignored the "Tiger" language described in the book - I had my own ideas about what I wanted to create. Relying on the book to give you code for a whole compiler is asking far too much. The general concepts are explained, and then reinforced with sample code. I suspect the people who have complained bitterly about this book are actually just looking for a source code print out.

All in all, very worthwhile. Read a chapter, try to implement the concepts, and then either re-read the same chapter, or move on.
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Inside This Book (learn more)
First Sentence:
This book describes techniques, data structures, and algorithms for translating programming languages into executable code. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
stm goto, predictive parsing table, static nesting depth, escaping variables, memo slot, functional intermediate form, generational collection, reachable data, dominator tree, liveness analysis, semantic analysis phase, coalesced node, dataflow equations, loop preheader, dynamic method lookup, bool ref, precedence directives, immediate dominator, register allocator, dominance frontier, pointer reversal, interference graph, dataflow information, dataflow analyses, predictive parser
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Maximal Munch, Webster's Dictionary, Perform Algorithm, Analyze Algorithm, New Jersey Library
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