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CHECKLIST: Code-Tuning Strategy
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Have you considered improving performance by changing the program requirements Have you considered improving performance by modifying the program s design Have you considered improving performance by modifying the class design Have you considered improving performance by avoiding operating system interactions
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25. Code-Tuning Strategies
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Have you considered improving performance by avoiding I/O Have you considered improving performance by using a compiled language instead of an interpreted language Have you considered improving performance by using compiler optimizations Have you considered improving performance by switching to different hardware Have you considered code tuning only as a last resort
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Is your program fully correct before you begin code tuning Have you measured performance bottlenecks before beginning code tuning Have you measured the effect of each code-tuning change Have you backed out the code-tuning changes that didn t produce the intended improvement Have you tried more than one change to improve performance of each bottleneck, i.e., iterated
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Performance is only one aspect of overall software quality, and it s usually not the most important. Finely tuned code is only one aspect of overall performance, and it s usually not the most significant. Program architecture, detailed design, and data-structure and algorithm selection usually have more influence on a program s execution speed and size than the efficiency of its code does. Quantitative measurement is a key to maximizing performance. It s needed to find the areas in which performance improvements will really count, and it s needed again to verify that optimizations improve rather than degrade the software. Most programs spend most of their time in a small fraction of their code. You won t know which code that is until you measure it. Multiple iterations are usually needed to achieve desired performance improvements through code tuning. The best way to prepare for performance work during initial coding is to write clean code that s easy to understand and modify.
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26. Code-Tuning Techniques
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Code-Tuning Techniques
Contents 26.1 Logic
26.2 Loops 26.3 Data Transformations 26.4 Expressions 26.5 Routines 26.6 Recoding in Assembler 26.7 The More Things Change, the More They Stay the Same
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Related Topics Code-tuning strategies: 28
Refactoring: 24 CODE TUNING HAS BEEN a popular topic during most of the history of computer programming. Consequently, once you ve decided that you need to improve performance and that you want to do it at the code level, you have a rich set of techniques at your disposal. This chapter focuses on improving speed and includes a few tips for making code smaller. Performance usually refers to both speed and size, but size reductions tend to come more from redesigning classes and data than from tuning code. Code tuning refers to small-scale changes rather than changes in larger-scale designs. Few of the techniques in this chapter are so generally applicable that you ll be able to copy the example code directly into your programs. The main purpose of the discussion here is to illustrate a handful of code tunings that you can adapt to your situation. The code-tuning changes described in this chapter might seem cosmetically similar to the refactorings described in 24. But refactorings are changes that improve a program s internal structure (Fowler 1999). The changes in this chapter might better be called anti-refactorings. Far from improving the
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26. Code-Tuning Techniques
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internal structure, these changes degrade the internal structure in exchange for gains in performance. This is true by definition. If they didn t degrade the internal structure, we wouldn t consider them to be optimizations; we would use them by default and consider them to be standard coding practice. Some books present code tuning techniques as rules of thumb or cite research that suggests that a specific tuning will produce the desired effect. As you will soon see, the concept of rules of thumb applies poorly to code tuning. The only reliable rule of thumb is to measure the effect of each tuning in your environment. Thus this chapter presents a catalog of things to try many of which won t work in your environment but some of which will work very well indeed.
Cod e tunings are heuristics. For 6 more on heuristics, see 7 Section 5.3, Design 8 Building Blocks: Heuristics.
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