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We design an interpretation-based theory of higher-order functions that is well-suited for the complexity analysis of a standard higher-order functional language a la ml. We manage to express the interpretation of a given program in terms of a least fixpoint and we show that when restricted to functions bounded by higher-order polynomials, they characterize exactly classes of tractable functions known as Basic Feasible Functions at any order.

Higher order interpretation for higher order complexity