Customer Reviews

Advanced Compiler Design and Implementation

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This book is the comprehensive text for anyone working on an optimizing compiler for uniprocessor systems. It gives good detail on all major approaches and is up-to-date on important techniques like SSA form and partial redundancy information. As someone working directly in the field, it's saved me the effort of hunting up original research papers in many areas. One drawback for this book as a practical tool: the pseudocode used to illustrate examples is often pretty far from being suitable for real implementations.

A warning: this is not an introductory book, and people who want to learn about the basics of building a compiler should look elsewhere; perhaps Andrew Appel's ``Modern Compilers'' series. Muchnick's book is for people who want to write compilers which generate high-performance code.

I have been working on language processors, interpreters and
compilers for almost twenty years. I try to order all the books
that have something unique to say about compiler design and
implementation. This is one of the best books I have seen on
advanced compiler design. I have owned it since it was first
published. Going back and rereading it I am reminded of what
and excellent book it is, which is what motivated this review.

Advanced compiler design deals with various forms of optimization,
including local, global and loop optimization. This is a complex
topic with thirty years of research behind it (it is interesting
to note that the late Gary Kildall, of CP/M fame, did some early
work on optiimization in the early 1970s). No single book can
provide complete coverage of all optimization issues. However,
this book, along with Allen and Kennedy's equally excellent
"Optimizing Compilers for Modern Architectures" covers almost
everything you need to know.

One of the problems with the academic literature on compiler
optimization is that it can be unnecessarily obscure. Muchnick
writes clearly, with the implementer in mind. He provides a
wide range of techniques, allowing the implementer to choose
the correct one for a given compiler. This approach is both
useful and necessary: there is no single method for building
a compiler, given the range of languages and design objectives.

Muchnick covers everything you need to know about local and
global scalar optimization, including scalar optimization in
loops and optimization for modern processor architecture.
The only thing missing is an indepth coverage of loop dependence
and optimization techniques, which is provided by Allen and
Kennedy.

If you are working on the design, implementation or extension of
a modern compiler, this book should be part of your library.

This the next step after the dragon book (Compilers by Aho, et al). The algorithms contained in this book are a FANTASTIC reference for the compiler professional and i've used them on the job many times. Instuction Scheduling chapter in particular was comprehensive and useful. Covers all the important topics in a practical manner. The key word in the title is "implementation". If you are sitting down to write a compiler, this should be sitting next to you.

Compiler development is more of a craft than a science, although there's plenty of science involved. It involves huge numbers of tradeoffs in features, optimizations, and use of the underlying processor. But, as long as people keep coming up with new computing platforms (and not just instruction set processors), new languages, and new performance demands there will always be need for new compiler developers. If you can't apprentice yourself to masters of the craft, or even if you can, this book is a great introduction 2000-era compiler development.

Muchnik does a clear, thorough job of laying out the basics, starting with the intermediate representation used. (If you get that wrong, nothing else is going to work.) He then moves on to the basics of symbol table structure - an issue that can get immensely complicated in systems like Microsoft's CLR. He also discusses run time support briefly. Although that discussion is good as far as it goes, it skips past a lot of the complexities of dynamic loading, debug symbol tables, simulation support, and related issues. They aren't strictly part of the compiled, executable code, but responsibilities of the compiler developer nonetheless. Next comes a brief description of code generation, crucial in normal environments but tangential to my own needs.

That's just the first quarter of the book, though. The rest is the real meat of the topic: code analysis and optimization techniques, over 600 pages of discussion. It's way too much to summarize here, but even that just an introduction to a huge technology. Still, you have to start somewhere.

By this point, you may be asking "But what about tokens, lexemes, and grammars? Isn't that what compilers do?" Well, yes, but it's done. Tool developers have made lexical analysis a commodity. The easily automated tasks are not where modern compiler distinguishes itself. This book addresses the semantic levels, getting the reader into the shallow end of the industry's huge pool of specialized compilation knowledge.

If you have to self-teach compiler development - good luck. Start here, though, and luck will have a lot less to do with the outcome.

//wiredweird

Having read the dragon book, i was looking around for a book which can give me more information on subjects like code generation & code optimization. This book is exactly that. 90% of the book deals with the code generation & optimization techniques used by the commercial compilers available today. The algorithms are complete and can be implemented without any difficulty. You won't find any book which deals with the code generation & optimization techniques so detailed as this one. This book is certainly not intended for a beginner. This book is for the professionals.

Advances in compiler design do not get much press these days. The reasons for this are unclear, but no doubt the perception that compilers need no further improvement has something to do with this. This book, written by one of the leading experts on compilers, certainly dispels this belief. Once readers get used to the idiosyncratic ICAN (Informal Compiler Algorithm Notation) invented by the author and used throughout the book, they get a comprehensive overview of compilers, especially that of optimization. Compilers for the SPARC, PowerPC, DEC, and Pentium architectures are treated in the book. The predominant emphasis of the book is in optimization, and so a few more recent and important topics in compiler construction, such as partial evaluation, are not discussed. Readers are expected to have a prior background in elementary compiler theory. My primary interest in reading the book was to gain insight into the compilation issues that arise in symbolic programming languages such as LISP and Prolog.

A detailed review of this book cannot be done for lack of space, but some of the helpful aspects and interesting discussions in the book include: 1. The "wrap-up" section at the end of each chapter, giving a compact summary of what was done in the chapter. 2. Generating loads and stores: The author shows how to move values to and from registers using routines more sophisticated than simply loading values into registers before using them or storing values as soon as they have been computed. 3. The main issues in the use of registers, such as variable allocation, efficiency of procedural calls, and scoping. The author lists the different categories that will result in contention for registers, such as stack, frame, and global offset table pointers and dynamic and static links. 4. The local stack frame and its uses, such as holding indexed variables (arrays, etc.) and debugging. 5. The five different parameter-passing mechanisms: call by value, call by result, call by value-result, call by reference, and call by name. A thorough discussion is given of their properties and what languages make use of them. In particular, the author notes that in the languages C and C++, call by value is the only parameter-passing mechanism, but that the address of an object may be passed, thus emulating essentially call by reference. This can be a source of confusion to those who program in C and C++. The most exotic of these mechanisms is call by name, which is a form of "lazy evaluation" in functional programming languages. The author gives a code example of the call by name parameter passing in ALGOL 60. I don't know of any modern practical programming languages that make use of call by name. 6. Shared libraries and the role of semantic linking and position independent code. 7. The compilation issues that arise in symbolic languages, such as LISP and Prolog. These languages typically have run-time type checking and function polymorphism, which gives them their power and ease of use. The author discusses how to produce efficient code for these languages. Since heap storage is utilized heavily by these languages, the allocation and recovering of it is very important. "Generation scavenging" is mentioned as the most efficient method for doing garbage collection in these languages. This method has been advertised in the literature as one that minimizes the time needed for storage reclamation in comparison with other approaches. In addition, the use of "on-the-fly" recompilation for polymorphic-language implementations is discussed. 8. Dynamic programming and its role in automatic production of code generators, as contrasted with the "greedy approach". The author explains the need for "uniform register machines" in the dynamic programming algorithm. 9. Interval analysis and its use in the analysis of control flow. This technique has been used in the field called "abstract interpretation" in recent years, the aim of which is too automatically and intelligently test program code. 10. Dependencies between dynamically allocated objects, such as links between graph structures in LISP and Prolog. The author describes the Hummel-Hendren-Nicolau technique for doing this, which involves naming schemes for locations in heap memory, a collection of axioms for characterizing aliasing locations among locations, and lastly, and most interestingly, utilizes a theorem prover to establish the properties of the data structures. The author emphasizes though that this technique, and others developed for doing dependence analysis of dynamically allocated objects, are very computationally intensive. 11. Individual optimizations, which the author divides into four groups in order of importance. 12. Induction-variable optimizations and their role in loop optimizations. The author shows how to identify induction variables, and how to transform them using various techniques, going by the name strength reduction, induction-variable removal, and linear-function test replacement. 13. Procedure integration and its role in "inlining" procedures in languages such as C++. The author emphasizes the drawbacks in using inlining, such as its impact on cache misses. 14. The trade-off between object abstraction and optimization, which occurs in object-oriented languages such as C++. The author discusses in detail the role of interprodecural optimizations in dealing with abstraction in the object-oriented modular approach to programming, particularly the identification of "side effects" in making procedure calls. 15. Code optimization that takes advantage of the memory hierarchy, such as data and instruction caches, and how to improve register allocation for arrays. The author gives a detailed and highly interesting discussion of scalar replacement for array elements. 16. Future trends and research in compiler design. The author mentions a few which he believes will dominate in the upcoming decade, such as scalar-oriented and data-cache optimizations. Scalar compilation will be he most active research area in his opinion. At the present time, there has been discussion of "intelligent compilers" that will interact with the user to develop optimal code, or even produce correct programs. These compilers will understand the intentions of the program and warn the user if these are violated, as well as reduce the time and cost needed for testing programs.

This is a very good intermediate/advanced text for codegen & optimization.

Having spent nearly 15 years working on compiler development, with most of it spent on codegen & optimization in compiler backends, I was very happy to see this book published ten years ago when I was relatively new to the field and hungry for more information.

The good: Coverage of many important topics, and a better discussion of the phase ordering issues than I've seen in other texts.

The bad: The writing style is okay, but not great. Little insight is typically given for the problems discussed. A very annoying aspect of the book is that the author sometimes goes into great detail about one technique, and then later mentions another (often superior, IMO) way to solve the problem at hand, without going into much detail. As a working compiler writer, I would have preferred it be the other way around.

The very very bad: The ICAN notation used throughout the book is verbose, unintuitive, and ultimately takes away from the presentation. Compare the complicated detail-filled ICAN listings in this book to the simple, elegant algorithms in the Dragon Book or Cooper/Torczon's text.

I was excited when I first scanned through a friends copy of this book because of its treatment of modern compiler design issues. I ran out, ordered the book, read through it more carefully and realized that it was nothing more than a collection of papers. There would be nothing wrong with this if it were so advertised. The book lacks original analysis. I wouldn't stedfastly say DON'T by this, but, I would say you might be better off just going to your local college CS library and grabbing all the relevant papers referened in the book.

This is, without doubt, an excellent book to understand the structure and the concepts involved in an optimising compiler. Some aspects of the book are better understood either if the reader is attending a course on optimising compilers or if the reader re-reads the section a second time. Once the user gets through the initial 10 chapters and understands the concepts, the rest should be good to read and understand. Any person who already has a good knowledge of "Data-flow" analysis and "dependence" will find this book very easy to read as the reader can directly jump to the 11th chapter.
Overall, it is a great book.

The book does its job and does it well. But, it's only fair to warn that the book concentrates on code generation, optimization, instruction scheduling, etc. If you're looking for attribute grammars, etc., look somewhere else. When you're done looking for that stuff, get this book.