With a given transformation on a finite domain, we associate a three-dimensional distribution function describing the component size, cycle length, and trajectory length of each point in the domain. We then consider a random transformation on the domain, in which images of points are independent and identically distributed. The three-dimensional distribution function associated with this random transformation is itself random. We show that, under a simple homogeneity condition on the distribution of images, and with a suitable scaling, this random distribution function has a limit law as the number of points in the domain tends to infinity. The proof is based on a Poisson approximation technique for matches in an urn model. The result helps to explain the behavior of computer implementations of
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