Abstract

Let ξξ be a random integer vector, having uniform distribution P{ξ=(i1,i2,...,in)=1/nn} for 1≤i1,i2,...,in≤n.\mathbf{P} \{ξ= (i_1,i_2,...,i_n) = 1/n^n \} \ \hbox{for} \ 1 \leq i_1,i_2,...,i_n\leq n. A realization (i1,i2,...,in)(i_1,i_2,...,i_n) of ξξ is called \textit{good}, if its elements are different. We present algorithms \textsc{Linear}, \textsc{Backward}, \textsc{Forward}, \textsc{Tree}, \textsc{Garbage}, \textsc{Bucket} which decide whether a given realization is good. We analyse the number of comparisons and running time of these algorithms using simulation gathering data on all possible inputs for small values of nn and generating random inputs for large values of nn.

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