Generating random variables from a specific distribution, whether symmetric or asymmetric, is a concern of investigators involved in Monte Carlo studies. Of particular interest to those concerned with robustness is the generation of contaminated symmetric distributions such as those used in the Princeton Robustness Study. A reliable composite uniform U(0,1) generator is described and algorithms for transforming U(0,1) to symmetric long-tailed and contaminated symmetric distributions are given. Goodness-of-fit tests and graphical illustrations demonstrate the adequacy of the empirical distributions.