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25. Code-Tuning Strategies
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25.1 Performance Overview
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More computing sins are committed in the name of efficiency (without necessarily achieving it) than for any other single reason including blind stupidity. W.A. Wulf
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Code tuning is one way of improving a program s performance. You can often find other ways to improve performance more, in less time and with less harm to the code, than by code tuning. This section describes the options.
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Quality Characteristics and Performance
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Some people look at the world through rose-colored glasses. Programmers like you and me tend to look at the world through code-colored glasses. We assume that the better we make the code, the more our clients and customers will like our software. This point of view might have a mailing address somewhere in reality, but it doesn t have a street number, and it certainly doesn t own any real estate. Users are more interested in tangible program characteristics than they are in code quality. Sometimes users are interested in raw performance, but only when it affects their work. Users tend to be more interested in program throughput than raw performance. Delivering software on time, providing a clean user interface, and avoiding downtime are often more significant. Here s an illustration: I take at least 50 pictures a week on my digital camera. To upload the pictures to my computer, the software that came with the camera requires me to select each picture one by one, viewing them in a window that shows only 6 pictures at a time. Uploading 50 pictures is a tedious process that required dozens of mouse clicks and lots of navigation through the 6-picture window. After putting up with this for a few months, I bought a memory-card reader that plugs directly into my computer and that my computer thinks is a disk drive. Now I can use Windows Explorer to copy the pictures to my computer. What used to take dozens of mouse clicks and lots of waiting now requires about two mouse clicks, a CTRL+A, and a drag and drop. I really don t care whether the memory card reader transfers each file in half the time or twice the time as the other software, because my throughput is faster. Regardless of whether the memory card reader s code is faster or slower, it s performance is better. Performance is only loosely related to code speed. To the extent that you work on your code s speed, you re not working on other quality characteristics. Be wary of sacrificing other characteristics in order to make your code faster. Your work on speed may hurt performance rather than help it.
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1 KEY POINT
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25. Code-Tuning Strategies
Page 3
Performance and Code Tuning
Once you ve chosen efficiency as a priority, whether its emphasis is on speed or on size, you should consider several options before choosing to improve either speed or size at the code level. Think about efficiency from each of these viewpoints: Program requirements System design Class and routine design Operating-system interactions Code compilation Hardware Code tuning
Program Requirements
Performance is stated as a requirement far more often than it actually is a requirement. Barry Boehm tells the story of a system at TRW that initially required sub-second response time. This requirement led to a highly complex design and an estimated cost of $100 million. Further analysis determined that users would be satisfied with four-second responses 90 percent of the time. Modifying the response-time requirement reduced overall system cost by about $70 million. (Boehm 2000b). Before you invest time solving a performance problem, make sure that you re solving a problem that needs to be solved.
Program Design
This level includes the major strokes of the design for a single program, mainly the way in which a program is divided into classes. Some program designs make it difficult to write a high-performance system. Others make it hard not to. Consider the example of a real-world data-acquisition program for which the high-level design had identified measurement throughput as a key product attribute. Each measurement included time to make an electrical measurement, calibrate the value, scale the value, and convert it from sensor data units (such as millivolts) into engineering data units (such as degrees). In this case, without addressing the risk in the high-level design, the programmers would have found themselves trying to optimize the math to evaluate a 13th-order polynomial in software that is, a polynomial with 14 terms includ-
For details on designing perform9 ance into a program, see the 0 Additional Resources section at the end of the chapter.
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