Test(S) is a method proposed by Okabe-Nakano to test if a time series is a realization of a local and weakly stationary process. It evaluates three test values (M) for mean, (V) for variance, and (O) for covariance on subsets of shifted data. The rate at which each test value is accepted over multiple trials is calculated to determine if the data meets the conditions for a stationary process. When applied to an example using KM2O-Langevin data, Test(S) accepted the mean (M) in 80% of trials, variance (V) in 70% of trials, and covariance (O) in 80% of trials.