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Product details
File Size: 23062 KB
Print Length: 548 pages
Simultaneous Device Usage: Up to 4 simultaneous devices, per publisher limits
Publisher: Cambridge University Press (December 13, 1997)
Publication Date: December 13, 1997
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B00D2WQAE8
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Appel's stated goal in writing this book was, rather than to provide a laundry list of compiler algorithms that could potentially be used to implement a compiler, to use the algorithms that now dominate modern compilers. His thorough and authoritative approach starts with building a complete working compiler in the first half of the book before exploring deeper specialized topics in the last half of the book. Each chapter comes with example ML code from the chapter along with programming exercises which build off of the chapter's code so that at the end you have built a working optimizing compiler.The book is an enjoyable read the whole way through. I particularly enjoyed the chapters on Instruction Selection, Register Allocation, Functional Languages, Loop Optimizations, and the Memory Hierarchy. This book gave me a new appreciation for how sophisticated a compiler's job is. If you're looking for an introduction or refresher on compilers, start with this book.
I find this a nice textbook for a first compiler class. However, more than the book I find the author's assignments, available on his course website on Princeton, very valuable. The assignments are well thought out, and well written. They help you pace the lectures very well. Search for "Princeton COS 320".
I took Prof. Appel's course in the spring and the book was a great companion for the lectures. It's quite comprehensive and building the compiler is a lot of fun.I also have the the sister-book, Modern Compiler Implementation in C. So if you're choosing between the C, Java and ML versions, I strongly recommend using ML.
The book is very clear, well written and the author guides the reader with simplicity through all the steps required to implement a compiler. The code in ML to implement the most important routines is given with complete explanations.For the other side the writing style is not enlightening, I did not fall in love of this book, but it is an excellent book for learning and understand.
An alright reference book but definitely isn't a good way to learn the material.
This book has a lot of valuable information with regard to the construction of a compiler, that fact is overshadowed by the amazingly poor editing.This is supposedly the "first edition reprint with corrections", but it seems like the vast majority of errors are yet to be corrected.
Terrible. It is very confusing to read and to keep track of all of the code pieces provided and their role in the program. Some of the provided code does not work. Some code could use more comments. Not good for a first experience in Compilers or SML.
This book aims at teaching the reader how to write compilers and interpreters. Compared to other books (most notably the Dragon book - Aho, Sethi & Ullman: Compilers - Principles, Techniques and Tools) the structure and organization of the compiler he teaches are better and more in sync with modern compiler research. So although ML is not a language that is used much in practice it is well choosen for teaching compilers.The first part of the book is intended for undergraduate Computer Science university student and the second part is for graduate students. I have only read the first part and browsed the second part. The first part is founded on the development of a compiler - the Tiger compiler - and that is the main flaw of the book. The Tiger compiler is fairly advanced and it is built up one phase at the time (see the chapter headings in the synopsis). A undergraduate reader who has never read anything about compiler design before will be very confused. The book is good in the way that it presents many good compiler design ideas and I learned some from it, but for me it was not the first book on compiler. I just think that the first part of the book has too steep a learning curve - even if you are proficient with ML, which is an absolute must. Recommended for serious readers who already know something about compiler construction before reading it. For other people I recommend the older but somewhat outdated book: Aho, Sethi & Ullman: Compilers - Principles, Techniques and Tools.
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