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Abstract. This paper describes an algorithm that determines the minimal sets of variables that determine the values of a discrete partial function. The Apriori-like algorithm is based on the dual hereditary property of determining sets. Experimental results are provided that demonstrate the efficiency of the algorithm for functions with up to 24 variables. The dependency of the number of minimal determining sets on the size of the specification of the partial function is also examined.

This paper describes an algorithm that determines the minimal sets of variables that determine the values of a discrete partial function. The algorithm is based on the notion of entropy of a partition and is able to achieve an optimal solution. A limiting factor is introduced to restrict the search, thereby providing the option to reduce running time. Experimental results are provided that demonstrate the efficiency of the algorithm for functions with up to 24variables. The effect of the limiting factor on the optimality of the algorithm for different sizes of partial functions is also examined.

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