HandBooks Professional Java-C-Scrip-SQL part 122 pptx

http://developer.apple.com/techpubs/macosx/Cocoa/CocoaTopics.html Web site for documentation of the Cocoa class library. http://www.gnustep.org Web site for releases and documentation for the GNUstep library, an open source version of Cocoa. http://cocoa.mamasam.com A searchable archive that combines several Cocoa developer mailing lists. Cocoa Programming for Mac OS X An introduction to both Objective-C and the Cocoa framework. By Aaron Hillegass. Addison-Wesley. Learning Cocoa with Objective-C An introduction to both Objective-C and the Cocoa framework. By James Duncan Davidson. O'Reilly & Associates. Cocoa Programming A more advanced guide to the Cocoa framework. By Scott Anguish, Erik Buck, and Donald A. Yacktman. SAMS. [NEXT] ISBN: 0-13-977430-0 Copyright 1999 by Prentice-Hall PTR Copyright 2000 by Chrysalis Software Corporation Would you like to discuss interesting topics with intelligent people? If so, you might be interested in Colloquy, the world's first internet-based high-IQ society. I'm one of the Regents of this society, and am responsible for the email list and for membership applications. Application instructions are available here. Imagine that you are about to finish a relatively large program, one that has taken a few weeks or months to write and debug. Just as you are putting the finishing touches on it, you discover that it is either too slow or runs out of memory when you feed it a realistic set of input data. You sigh, and start the task of optimizing it. But why optimize? If your program doesn't fit in memory, you can just get more memory; if it is too slow, you can get a faster processor. I have written Optimizing C++ because I believe that this common attitude is incorrect, and that a knowledge of optimization is essential to a professional programmer. One very important reason is that we often have little control over the hardware on which our programs are to be run. In this situation, the simplistic approach of adding more hardware is not feasible. Optimizing C++ provides working programmers and those who intend to be working programmers with a practical, real-world approach to program optimization. Many of the optimization techniques presented are derived from my reading of academic journals that are, sadly, little known in the programming community. This book also draws on my nearly 30 years of experience as a programmer in diverse fields of application, during which I have become increasingly concerned about the amount of effort spent in reinventing optimization techniques rather than applying those already developed. The first question you have to answer is whether your program needs optimization at all. If it does, you have to determine what part of the program is the culprit, and what resource is being overused. Chapter 1 indicates a method of attack on these problems, as well as a real-life example. All of the examples in this book were compiled with both Microsoft's Visual C++ 5.0 and the DJGPP compiler, written and copyrighted by DJ Delorie. The latter compiler is available here. The source code for the examples is available here. If you want to use DJGPP, I recommend that you also get RHIDE, an integrated development environment for the DJGPP compiler, written and copyrighted by Robert Hoehne, which is available here. All of the timings and profiling statistics, unless otherwise noted, were the result of running the corresponding program compiled with Visual C++ 5.0 on my Pentium II 233 Megahertz machine with 64 megabytes of memory. I am always happy to receive correspondence from readers. If you wish to contact me, the best way is to visit my WWW home page. If you prefer, you can email me. In the event that you enjoy this book and would like to tell others about it, you might want to write an on-line review on Amazon.com, which you can do here. I should also tell you how the various typefaces are used in the book. HelveticaNarrow is used for program listings, for terms used in programs, and for words defined by the C++ language. Italics are used primarily for technical terms that are found in the glossary, although they are also used for emphasis in some places. The first time that I use a particular technical term that you might not know, it is in bold face. Now, on with the show! Dedication Acknowledgements Prologue A Supermarket Price Lookup System A Mailing List System Cn U Rd Ths (Qkly)? A Data Compression Utility Free at Last: An Efficient Method of Handling Variable-Length Records Heavenly Hash: A Dynamic Hashing Algorithm Zensort: A Sorting Algorithm for Limited Memory Mozart, No. Would You Believe Gershwin? About the Author This book is dedicated to Susan Patricia Caffee Heller, the light of my life. Without her, this book would not be what it is; even more important, I would not be what I am: a happy man. Acknowledgements I'd like to thank all those readers who have provided feedback on the first two editions of this book, especially those who have posted reviews on Amazon.com; their contributions have made this a better book. I'd also like to thank Jeff Pepper, my editor at Prentice-Hall, for his support and encouragement. Without him, this third edition would never have been published. Finally, I would like to express my appreciation to John P. Linderman at AT&T Labs Research for his help with the code in the chapter on sorting immense files. Prologue Introduction to Optimization What is optimization anyway? Clearly, we have to know this before we can discuss how and why we should optimize programs. Definition Optimization is the art and science of modifying a working computer program so that it makes more efficient use of one or more scarce resources, primarily memory, disk space, or time. This definition has a sometimes overlooked but very important corollary (The First Law of Optimization): The speed of a nonworking program is irrelevant. Algorithms Discussed Radix40 Data Representation, Lookup Tables 1 Deciding Whether to Optimize Suppose you have written a program to calculate mortgage payments; the yearly run takes ten minutes. Should you spend two hours to double its speed? Probably not, since it will take twenty-four years to pay back the original investment of time at five minutes per year. 2 On the other hand, if you run a program for three hours every working day, even spending thirty hours to double its speed will pay for itself in only twenty working days, or about a month. Obviously the latter is a much better candidate for optimization. Usually, of course, the situation is not nearly so unambiguous: even if your system is overloaded, it may not be immediately apparent which program is responsible. 3 My general rule is not to optimize a program that performs satisfactorily. If you (or the intended users) don't become impatient while waiting for it to finish, don't bother. Of course, if you just feel like indulging in some recreational optimization, that's another matter. Why Optimization Is Necessary Assuming that our programs are too big, or too slow, why don't we just add more memory or a faster processor? If that isn't possible today, then the next generation of processors should be powerful enough to spare us such concerns. Let's examine this rather widely held theory. Although the past is not an infallible guide to the future, it is certainly one source of information about what happens when technology changes. A good place to start is to compare the computers of the late 1970's with those of the late 1990's. The first diskette-based computer I ever owned was a Radio Shack TRS-80 Model III TM , purchased in 1979. 4 It had a 4 MHz Z80 TM processor, 48 Kbytes of memory, and Basic TM in ROM. The diskettes held about 140 Kbytes apiece. Among the programs that were available for this machine were word processors, assemblers, debuggers, data bases, and games. While none of these were as advanced as the ones that are available today on 80x86 or 680x0 machines, most of the basic functions were there. The Pentium II TM machines of today have at least 1000 times as much memory and 20000 times as much disk storage and are probably 1000 times as fast. Therefore, according to this theory, we should no longer need to worry about efficiency. Recently, however, several of the major microcomputer software companies have had serious performance problems with new software releases of both application . that this common attitude is incorrect, and that a knowledge of optimization is essential to a professional programmer. One very important reason is that we often have little control over the. answer is whether your program needs optimization at all. If it does, you have to determine what part of the program is the culprit, and what resource is being overused. Chapter 1 indicates a. glossary, although they are also used for emphasis in some places. The first time that I use a particular technical term that you might not know, it is in bold face. Now, on with the show!