Q: Using Metatheory.jl for code optimization


After going through the rather terse Metatheory.jl documentation, there are a number of concepts that are novel and unfamilair to me, so I’m unable to discern if the package can do the following:

It is possible to use Metatheory.jl for code optimization in the sense of reducing the number of basic operations {+, -, x, /, ^} for large polynomial and polynomial -like expressions?

With Sympy, I had used FORM 4.2.1 which performs a stochastic local search via stochastic hill climbing to find the near-minimal number of operations for a multivariate Horner scheme combined with CSEE [Common Subexpression Elimination].

Is it possible to use Metatheory.jl to do the same or equivalent?

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