Home → Magazine Archive → November 2015 (Vol. 58, No. 11) → It Probably Works → Abstract

It Probably Works

By Tyler Mcmullen

Communications of the ACM, Vol. 58 No. 11, Pages 50-54

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Probabilistic algorithms exist to solve problems that are either impossible or unrealistic (too expensive or too time consuming, and so on) to solve precisely. In an ideal world, you would never actually need to use probabilistic algorithms. To programmers who are not familiar with them, the idea can be positively nerve-wracking: "How do I know it will actually work? What if it is inexplicably wrong? How can I debug it? Maybe we should just punt on this problem, or buy a whole lot more servers ..."

However, to those who either deeply understand probability theory or at least have used and observed the behavior of probabilistic algorithms in large-scale production environments, these algorithms are not only acceptable, but it is also worth seeking out opportunities to use them. This is because they can help solve problems and create systems that are less expensive, more predictable, and can do things that could not be done otherwise.


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