Information theory applied to the conversion of decision tables to computer programs

Using ideas from information theory, this paper develops a heuristic algorithm that converts a limited entry decision table to a tree structured computer program with near minimum average processing time. The method is applicable to any limited entry decision table and does not require that actions have single rules or that the cost of testing conditions be equal. It is thus more general than the previously published heuristic algorithms. Compared to the optimal algorithm of Reinwald and Soland, this algorithm is easy to code and takes a much smaller translation time; it is thus felt that it is more useful in practice. The algorithm is well suited for manual conversion of decision tables to flowcharts.

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