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We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil. Donald Knuth
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You should optimize as you go false! One theory is that if you strive to write the fastest and smallest possible code as you write each routine, your program will be fast and small. This approach creates a forest-for-the-trees situation in which programmers ignore significant global optimizations because they re too busy with micro-optimizations. Here are the main problems with optimizing as you go along:
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It s almost impossible to identify performance bottlenecks before a program is working completely. Programmers are very bad at guessing which 4 percent of the code accounts for 50 percent of the execution time, and so programmers who optimize as they go will, on average, spend 96 percent of their time optimizing code that doesn t need to be optimized. That leaves very little time to optimize the 4 percent that really counts. In the rare case in which developers identify the bottlenecks correctly, they overkill the bottlenecks they ve identified and allow others to become critical. Again, the ultimate effect is a reduction in performance. Optimizations done after a system is complete can identify each problem area and its relative importance so that optimization time is allocated effectively. Focusing on optimization during initial development detracts from achieving other program objectives. Developers immerse themselves in algorithm analysis and arcane debates that in the end don t contribute much value to the user. Concerns such as correctness, information hiding, and readability become secondary goals, even though performance is easier to improve later than these other concerns are. Post-hoc performance work typically affects less than 5 percent of a program s code. Would you rather go back and do performance work on 5 percent of the code or readability work on 100 percent
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In short, premature optimization s primary drawback is its lack of perspective. Its victims include final code speed, performance attributes that are more important than code speed, program quality, and ultimately the software s users. If the development time saved by implementing the simplest program is devoted to optimizing the running program, the result will always be a faster-running program than one in which optimization efforts have been exerted indiscriminately as the program was developed (Stevens 1981). In an occasional project, post-hoc optimization won t be sufficient to meet performance goals, and you ll have to make major changes in the completed code. In those cases, small, localized optimizations wouldn t have provided the gains needed anyway. The problem in such cases isn t inadequate code quality it s inadequate software architecture.
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If you need to optimize before a program is complete, minimize the risks by building perspective into your process. One way is to specify size and speed goals for features and then optimize to meet the goals as you go along. Setting such goals in a specification is a way to keep one eye on the forest while you figure out how big your particular tree is.
8 FURTHER READING For
9 many other entertaining and
enlightening anecdotes, see Gerald Weinberg s Psychol1 ogy of Computer Program2 ming (1998).
A fast program is just as important as a correct one false! It s hardly ever true that programs need to be fast or small before they need to be correct. Gerald Weinberg tells the story of a programmer who was flown to Detroit to help debug a troubled program. The programmer worked with the team who had developed the program and concluded after several days that the situation was hopeless.
On the flight home, he mulled over the situation and realized what the problem was. By the end of the flight, he had an outline for the new code. He tested the code for several days and was about to return to Detroit when he got a telegram saying that the project had been cancelled because the program was impossible to write. He headed back to Detroit anyway and convinced the executives that the project could be completed. Then he had to convince the project s original programmers. They listened to his presentation, and when he d finished, the creator of the old system asked, And how long does your program take That varies, but about ten seconds per input. Aha! But my program takes only one second per input. The veteran leaned back, satisfied that he d stumped the upstart. The other programmers seemed to agree, but the new programmer wasn t intimidated. Yes, but your program doesn t work. If mine doesn t have to work, I can make it run instantly. For a certain class of projects, speed or size is a major concern. This class is the minority, is much smaller than most people think, and is getting smaller all the time. For these projects, the performance risks must be addressed by up-front design. For other projects, early optimization poses a significant threat to overall software quality, including performance.
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