On transforming a program by substituting constants for free variables
The correct title of this article is Sm n theorem. It appears incorrectly here due to technical restrictions.
In computability theory the Sm n theorem, written also as "smn-theorem" or "s-m-n theorem" (also called the translation lemma, parameter theorem, and the parameterization theorem) is a basic result about programming languages (and, more generally, Gödel numberings of the partial computable functions) (Soare 1987, Rogers 1967). It was first proved by Stephen Cole Kleene (1943). The name Sm n comes from the occurrence of an S with subscript n and superscript m in the original formulation of the theorem (see below).
In practical terms, the theorem says that for a given programming language and positive integers m and n, there exists a particular algorithm that accepts as input the source code of a program with m + nfree variables, together with m values. This algorithm generates source code that in essence substitutes the values for the first m free variables, leaving the rest of the variables free.
Details
The basic form of the theorem applies to functions of two arguments (Nies 2009, p.6). Given a Gödel numbering of partial computable functions, there is a primitive recursive functions of two arguments with the following property: for every Gödel number e of a partial computable function f with two arguments, the expressions and are defined for the same combinations of natural numbers x and y, and their values are equal for any such combination. In other words, the following extensional equality of functions holds for every x:
More generally, for any m, n > 0, there exists a primitive recursive function of m + 1 arguments that behaves as follows: for every Gödel number e of a partial computable function with m + n arguments, and all values of x1, …, xm:
The function s described above can be taken to be .
Formal statement
Given arities m and n, for every Turing Machine of arity and for all possible values of inputs , there exists a Turing machine of arity n, such that
Furthermore, there is a Turing machine S that allows k to be calculated from x and y; it is denoted .
Informally, S finds the Turing Machine that is the result of hardcoding the values of y into . The result generalizes to any Turing-complete computing model.