The testability of basic DSP datapath structures using pseudorandom built-in self-test techniques is examined. The addition of variance mismatched signals is identified as a testing problem, and the associated fault detection probabilities are derived in terms of signal probability distributions. A method of calculating these distributions is described, and it is shown how these distributions can be used to predict testing problems that arise from the correlation properties of test sequences generated using linear-feedback shift registers. Finally, it is shown empirically that variance matching using associativity transformations can reduce the number of untested faults by a factor of eight over variance mismatched designs.