%0 Journal Article
%T Optimizing Abstract Abstract Machines
%A J. Ian Johnson
%A Nicholas Labich
%A Matthew Might
%A David Van Horn
%J Computer Science
%D 2012
%I arXiv
%R 10.1145/2500365.2500604
%X The technique of abstracting abstract machines (AAM) provides a systematic approach for deriving computable approximations of evaluators that are easily proved sound. This article contributes a complementary step-by-step process for subsequently going from a naive analyzer derived under the AAM approach, to an efficient and correct implementation. The end result of the process is a two to three order-of-magnitude improvement over the systematically derived analyzer, making it competitive with hand-optimized implementations that compute fundamentally less precise results.
%U http://arxiv.org/abs/1211.3722v4