for uniformly distributed data sets and relatively little additional memory requirement. The original work was published in 1998 by Karl-Dietrich Neubert. [1] Contents The basic idea behind flashsort is that in a data set with a known distribution , it is easy to immediately estimate where an element should be placed after sorting when the range of the set is known. For example, if given a uniform data set where the minimum is 1 and the maximum is 100 and 50 is an element of the set, it’s reasonable to guess that 50 would be near the middle of the set after it is sorted.
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