Dr. Leonard McCoy in Star Trek: The Devil in the Dark Computer scientists talk knowledgeably about “Turing-complete” programming languages, by which they mean a language that can be shown to be equivalent to a Turing machine and therefore provably able to solve any computation that can be expressed as an algorithm. A Turing machine is a hypothetical device invented by Alan Turing, and consists of a long tape passing under a read/write head that is capable of reading and printing characters on the tape according to a table of rules specifying what to do. Unfortunately, no implementation of any programming language does or ever could live up to the strict definition of “Turing-complete,” since Turing specified that his machine was equipped with an infinitely long tape. He also specified that the machine was allowed an arbitrary amount of time to solve a problem, which is a luxury that few people outside of academia can afford. This chapter is about what to do when your finite resources are too finite. We’ll discuss how to react when you run out of time, memory, or disk space. 11.1 Optimize for People First, Resources Later Note that we didn’t say, ” how to avoid running out of .” There’s a good reason for this: If you worry about it from the beginning, you’re optimizing for the wrong thing. While you’ll see a lot of carping from seasoned professionals on Usenet arguing that such-and-such code isn’t as efficient as their latest mutation of it, understand that they’re coming from a place where the mind-bending code they’ve just written is as clear to them as anything else. More often than not, they’re coming up with these performance enhancements to make the problem more interesting for themselves. They would not disagree with the advice we’re about to give, however:
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