- Paperback: 256 pages
- Publisher: Addison-Wesley Professional; 2 edition (October 7, 1999)
- Language: English
- ISBN-10: 0201657880
- ISBN-13: 978-0201657883
- Product Dimensions: 6.2 x 0.6 x 9.3 inches
- Shipping Weight: 12.8 ounces (View shipping rates and policies)
- Average Customer Review: 4.3 out of 5 stars See all reviews (86 customer reviews)
- Amazon Best Sellers Rank: #25,915 in Books (See Top 100 in Books)
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Fourteen years after it was first issued, C++ expert Jon Bentley reinvents a true classic with the second edition of his Programming Pearls. Completely revised and brought up to date with all new code examples in C and C++, this book remains an exceptional tutorial for learning to think like a programmer.
The "pearls" in question center not only on choosing the right algorithms (like binary searches, sorting techniques, or sparse arrays) but also on showing how to solve problems effectively. Each chapter frames a particular programming task--such as sorting numbers, creating anagrams, or counting the words in a block of text--many drawn from Bentley's experiences in his long career as a developer. The book traces the process of arriving at a fast, efficient, and accurate solution, along with code profiling to discover what works best. After refining the correct answer, each chapter enumerates programming principles that you can use on your own.
The author also challenges you to think like an engineer, and each chapter ends with about a dozen problems to get you thinking creatively about design issues. (Sidebars on such historical topics as the first computer solutions to computer chess, spell-checking, and even architectural design help create a perspective on successful problem solving and make for a truly educational and enjoyable tour of how to become a better programmer.) Bentley also asks the reader to think analytically about the world with "back of the envelope" estimation techniques drawn from engineering. Appendices list the algorithms and code rules covered in the book, plus some sample solutions.
Fans of the first edition of this title will be pleased to see this favorite computer text brought up to date for today's faster hardware. Whether you want to improve your command of algorithms or test your problem-solving skills, the new version of Programming Pearl is a challenging, instructive, and thoroughly entertaining resource. --Richard Dragan
Topics covered: Programming and problem-solving tutorial, sorting algorithms, merge sort, bit vectors, binary searches, program correctness and testing, improving performance, engineering and problem-solving techniques, performance estimates, designing for safety, divide-and-conquer and scanning algorithms, tuning code, tips for more efficient memory usage, insertion sort, quicksort algorithms, sparse arrays, searching algorithms, binary search trees, heaps, priority queues, searching text, and generating random text.
From the Inside Flap
Computer programming has many faces. Fred Brooks paints the big picture in
The Mythical Man Month; his essays underscore the crucial role of management
in large software projects. At a finer grain, Steve McConnell teaches good programming
style in Code Complete. The topics in those books are the key to good software
and the hallmark of the professional programmer. Unfortunately, though, the
workmanlike application of those sound engineering principles isn't always thrilling
-- until the software is completed on time and works without surprise.
About the Book
The columns in this book are about a more glamorous aspect of the profession:
programming pearls whose origins lie beyond solid engineering, in the realm
of insight and creativity. Just as natural pearls grow from grains of sand that
have irritated oysters, these programming pearls have grown from real problems
that have irritated real programmers. The programs are fun, and they teach important
programming techniques and fundamental design principles.
Most of these essays originally appeared in my ''Programming Pearls'' column
in Communications of the Association for Computing Machinery. They were
collected, revised and published as the first edition of this book in 1986.
Twelve of the thirteen pieces in the first edition have been edited substantially
for this edition, and three new columns have been added.
The only background the book assumes is programming experience in a high-level
language. Advanced techniques (such as templates in C++) show up now and then,
but the reader unfamiliar with such topics will be able to skip to the next
section with impunity.
Although each column may be read by itself, there is a logical grouping to
the complete set. Columns 1 through 5 form Part I of the book. They review programming
fundamentals: problem definition, algorithms, data structures and program verification
and testing. Part II is built around the theme of efficiency, which is sometimes
important in itself and is always a fine springboard into interesting programming
problems. Part III applies those techniques to several substantial problems
in sorting, searching and strings.
One hint about reading the essays: don't go too fast. Read them carefully,
one per sitting. Try the problems as they are posed -- some of them look easy
until you've butted your head against them for an hour or two. Afterwards, work
hard on the problems at the end of each column: most of what you learn from
this book will come out the end of your pencil as you scribble down your solutions.
If possible, discuss your ideas with friends and colleagues before peeking at
the hints and solutions in the back of the book. The further reading at the
end of each chapter isn't intended as a scholarly reference list; I've recommended
some good books that are an important part of my personal library.
This book is written for programmers. I hope that the problems, hints, solutions,
and further reading make it useful for individuals. The book has been used in
classes including Algorithms, Program Verification and Software Engineering.
The catalog of algorithms in Appendix 1 is a reference for practicing programmers,
and also shows how the book can be integrated into classes on algorithms and
The pseudocode programs in the first edition of the book were all implemented,
but I was the only person to see the real code. For this edition, I have rewritten
all the old programs and written about the same amount of new code. The programs
are available at this book's web site. The code includes much of the scaffolding
for testing, debugging and timing the functions. The site also contains other
relevant material. Because so much software is now available online, a new theme
in this edition is how to evaluate and use software components.
The programs use a terse coding style: short variable names, few blank lines,
and little or no error checking. This is inappropriate in large software projects,
but it is useful to convey the key ideas of algorithms. Solution 5.1 gives more
background on this style. The text includes a few real C and C++ programs, but
most functions are expressed in a pseudocode that takes less space and avoids
inelegant syntax. The notation for i = 0, n) iterates i from
0 through n-1. In these for loops, left and right parentheses denote
open ranges (which do not include the end values), and left and right square
brackets denote closed ranges (which do include the end values). The phrase
function(i, j) still calls a function with parameters i and j,
and arrayi, j still accesses an array element.
This edition reports the run times of many programs on ''my computer'', a 400MHz
Pentium II with 128 megabytes of RAM running Windows NT 4.0. I timed the programs
on several other machines, and the book reports the few substantial differences
that I observed. All experiments used the highest available level of compiler
optimization. I encourage you to time the programs on your machine; I bet that
you'll find similar ratios of run times.
To Readers of the First Edition
I hope that your first response as you thumb through this edition of the book
is, ''This sure looks familiar.'' A few minutes later, I hope that you'll observe,
''I've never seen that before.''
This version has the same focus as the first edition, but is set in a larger
context. Computing has grown substantially in important areas such as databases,
networking and user interfaces. Most programmers should be familiar users of
such technologies. At the center of each of those areas, though, is a hard core
of programming problems. Those programs remain the theme of this book. This
edition of the book is a slightly larger fish in a much larger pond.
One section from old Column 4 on implementing binary search grew into new Column
5 on testing, debugging and timing. Old Column 11 grew and split into new Columns
12 (on the original problem) and 13 (on set representations). Old Column 13
described a spelling checker that ran in a 64-kilobyte address space; it has
been deleted, but its heart lives on in Section 13.8. New Column 15 is about
string problems. Many sections have been inserted into the old columns, and
other sections were deleted along the way. With new problems, new solutions,
and four new appendices, this edition of the book is 25 percent longer.
Many of the old case studies in this edition are unchanged, for their historical
interest. A few old stories have been recast in modern terms.
Acknowledgments for the First Edition
I am grateful for much support from many people. The idea for a Communications
of the ACM column was originally conceived by Peter Denning and Stuart Lynn.
Peter worked diligently within ACM to make the column possible and recruited
me for the job. ACM Headquarters staff, particularly Roz Steier and Nancy Adriance,
have been very supportive as these columns were published in their original
form. I am especially indebted to the ACM for encouraging publication of the
columns in their present form, and to the many CACM readers who made
this expanded version necessary and possible by their comments on the original
Al Aho, Peter Denning, Mike Garey, David Johnson, Brian Kernighan, John Linderman,
Doug McIlroy and Don Stanat have all read each column with great care, often
under extreme time pressure. I am also grateful for the particularly helpful
comments of Henry Baird, Bill Cleveland, David Gries, Eric Grosse, Lynn Jelinski,
Steve Johnson, Bob Melville, Bob Martin, Arno Penzias, Marilyn Roper, Chris
Van Wyk, Vic Vyssotsky and Pamela Zave. Al Aho, Andrew Hume, Brian Kernighan,
Ravi Sethi, Laura Skinger and Bjarne Stroustrup provided invaluable help in
bookmaking, and West Point cadets in EF 485 field tested the penultimate draft
of the manuscript. Thanks, all.
Acknowledgments for the Second Edition
Dan Bentley, Russ Cox, Brian Kernighan, Mark Kernighan, John Linderman, Steve
McConnell, Doug McIlroy, Rob Pike, Howard Trickey and Chris Van Wyk have all
read this edition with great care. I am also grateful for the particularly helpful
comments of Paul Abrahams, Glenda Childress, Eric Grosse, Ann Martin, Peter
McIlroy, Peter Memishian, Sundar Narasimhan, Lisa Ricker, Dennis Ritchie, Ravi
Sethi, Carol Smith, Tom Szymanski and Kentaro Toyama. I thank Peter Gordon and
his colleagues at Addison-Wesley for their help in preparing this edition.
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Top Customer Reviews
This book has a list of hand picked real problems solved by various developers at times when RAM was counted in kilobytes and megabytes and CPU frequency in megahertz rather than in gigahertz. The examples aren't untrue, they're just not intuitive to a modern reader. It's nothing that ruins the book, it just seems slightly silly today like "big" computers with just a meg or two of memory available. But these algorithms are still very important, because current computer systems are limited by memory access times rather than by CPU frequency. It means that in many cases you may gain a serious performance boost by using these "out of date" algorithms.
This book can not replace any of well-known algorithm text books, but this is probably the best practical programming/algorithms book I've read. And the most important part is, it is easy and interesting to read. So if you are a programmer, read it.
What Bentley does in each of these columns is take some part of the field of programming--something that every one of us will have run into at some point in our work--and dig underneath it to reveal the part of the problem that is permanent; that doesn't change from language to language. The first two parts cover problem definition, algorithms, data structures, program verification, and efficiency (performance, code tuning, space tuning); the third part applies the lessons to example pseudocode, looking at sorting, searching, heaps, and an example spellchecker.
Bentley writes clearly and enthusiastically, and the columns are a pleasure to read. But the reason so many people love this book is not for the style, it's for the substance--you can't read this book and not come away a better programmer. Inefficiency, clumsiness, inelegance and obscurity will offend you just a little more after you've read it.
It's hard to pick a favourite piece, but here's one nice example from the algorithm design column that shows how little the speed of your Pentium matters if you don't know what you're doing. Bentley presents a particular problem (the details don't matter) and multiple different ways to solve it, calculating the relationship between problem size and run time for each algorithm. He gives, among others, a cubic algorithm (run time equal to a constant, C, times the cube of the problem size, N--i.e. t ~ CN^3), and a linear algorithm with constant K (t ~ KN). He then implemented them both: the former in fine-tuned FORTRAN on a Cray-1 supercomputer; the latter in BASIC on a Radio Shack TRS-80. The constant factors were as different as they could be, but with increasing problem size the TRS-80 eventually has to catch up--and it does. He gives a table showing the results: for a problem size of 1000, the Cray takes three seconds to the TRS-80's 20 seconds; but for a problem size of 1,000,000, the TRS-80 takes five and a half hours, whereas the Cray would take 95 years.
The book is informative, entertaining, and will painlessly make you a better programmer. What more can you ask?
Each column has been reorganized as a chapter. Chapters usually start with the presentation of a practical problem. Then various solutions are presented and are used as lessons to be learned. The writing style is clear and fun.
Programming Pearls is not a usual book teaching new programming concepts. Although it contains good and sometimes quite novel ideas, the aim of the book is not to teach something new. For example, the search and sort algorithms presented are well-known. The aim is to remind programmers to think hard before starting writing code. The book has great chapter on back-of-the-envelope computation for example which is useful when comparing various solutions. The easy solutions to the column's problems are usually very slow. The `good' solutions are lightening fast but require thinking hard about the problems. I would recommend having a book about algorithms nearby when reading Programming Pearls.
The book is full of little (and some not so little) exercises that are given throughout the chapters. Solutions or hints are given at the end. The exercises usually take a few hours to do properly and are a great resource. Again the emphasis is on making the reader think.
If you consider programming a repetitious activity, Programming Pearls will provoke you into thinking harder about finding elegant solutions. I recommend this book.
Most Recent Customer Reviews
The content is a perfect combination of algorithm design and engineering implementation.Read more