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While decision tree compilation is a promising way to carry out guard tests efficiently, the methods given in the literature do not take into account either the execution characteristics of the program or the machine-level tradeoffs between different ways to implement branches. These methods therefore offer little or no guidance for the implementor with regard to how decision trees are to be realized on a particular machine. In this paper, we describe an approach that takes execution frequencies of different program branches, as well as the costs of alternative branch realizations, to generate decision trees. Experiments indicate that the performance of our approach is uniformly better than that of plausible alternative schemes.