  Gradients and subgradients are central to optimization and sensitivity
analysis of buffered failure probabilities. We furnish a characterization of
subgradients based on subdifferential calculus in the case of finite
probability distributions and, under additional assumptions, also a gradient
expression for general distributions. Several examples illustrate the
application of the results, especially in the context of optimality conditions.
