Abstract

Two methods for proving the correctness of data representations are presented which employ a mathematical relation between the data values in a representation and those in its abstract model. One method reflects the behavioural equivalence relation of abstract data type theory, and the other a new “behavioural inclusion” notion that formalizes the idea of a “partial representation” of a data type. These correctness concepts and proof methods are strictly more general than the conventional ones based on abstraction functions, and they are no longer affected by “implementation bias” in specifications.

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