Statistical analysis of random number generators

In many applications, for example cryptography and Monte Carlo simulation, there is need for random numbers. Any procedure, algorithm or device which is intended to produce such is called a random number generator (RNG). What makes a good RNG? This paper gives an overview on empirical testing of the statistical properties of the sequences produced by RNGs and special software packages designed for that purpose. We also present the results of applying a particular test suite---TestU01---to a family of RNGs currently being developed at the Centro Interdipartimentale Vito Volterra (CIVV), Roma, Italy