Run-time algorithm specialisation

In computer science, run-time algorithm specialization is a methodology for creating efficient algorithms for costly computation tasks of certain kinds. The methodology originates in the field of automated theorem proving and, more specifically, in the Vampire theorem prover project.

The idea is inspired by the use of partial evaluation in optimising program translation. Many core operations in theorem provers exhibit the following pattern. Suppose that we need to execute some algorithm ${\displaystyle {\mathit {alg}}(A,B)}$ in a situation where a value of ${\displaystyle A}$ is fixed for potentially many different values of ${\displaystyle B}$. In order to do this efficiently, we can try to find a specialization of ${\displaystyle {\mathit {alg}}}$ for every fixed ${\displaystyle A}$, i.e., such an algorithm ${\displaystyle {\mathit {alg}}_{A}}$, that executing ${\displaystyle {\mathit {alg}}_{A}(B)}$ is equivalent to executing ${\displaystyle {\mathit {alg}}(A,B)}$.

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