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copied!<blockquote> <p>Most programs are too complicated — that is, more complex than they need to be to solve their problems efficiently. Why? Mostly it’s because of bad design, but I will skip that issue here because it’s a big one. But programs are often complicated at the microscopic level, and that is something I can address here. </p> <ul> <li><strong>Rule 1.</strong> You can’t tell where a program is going to spend its time. Bottlenecks occur in surprising places, so don’t try to second guess and put in a speed hack until you’ve proven that’s where the bottleneck is. </li> <li><strong>Rule 2.</strong> Measure. Don’t tune for speed until you’ve measured, and even then don’t unless one part of the code overwhelms the rest.</li> <li><strong>Rule 3.</strong> Fancy algorithms are slow when <em>n</em> is small, and <em>n</em> is usually small. Fancy algorithms have big constants. Until you know that <em>n</em> is frequently going to be big, don’t get fancy. (Even if_n_ does get big, use Rule 2 first.) For example, binary trees are always faster than splay trees for workaday problems.</li> <li><strong>Rule 4.</strong> Fancy algorithms are buggier than simple ones, and they’re much harder to implement. Use simple algorithms as well as simple data structures.<br> The following data structures are a complete list for almost all practical programs: array, linked list, hash table, binary tree.<br> Of course, you must also be prepared to collect these into compound data structures. For instance, a symbol table might be implemented as a hash table containing linked lists of arrays of characters.</li> <li><strong>Rule 5.</strong> Data dominates. If you’ve chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming. (See Brooks p. 102.)</li> <li><strong>Rule 6.</strong> There is no Rule 6.</li> </ul> <p><em>-- Rob Pike, <a href="http://www.literateprogramming.com/pikestyle.pdf" rel="nofollow noreferrer">Programming in C</a>: Complexity</em></p> </blockquote>

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