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In common practice, randomized algorithms are approximated using a pseudorandom number generator in place of a true source of random bits; such an implementation may deviate from the expected theoretical behavior and mathematical guarantees which may depend on the existence of an ideal true random number generator.

• Motivation

• Computational complexity

• Early history

• Sorting

• Number theory

• Data structures

• Implicit uses in combinatorics

• Examples

• Quicksort

• Randomized incremental constructions in geometry

• Min cut

• Derandomization

• Where randomness helps

• See also

• Notes

• References

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