Optimizing Abstract Abstract Machines
| Autor: | Johnson, J. Ian, Labich, Nicholas, Might, Matthew, Van Horn, David |
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| Rok vydání: | 2012 |
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| Druh dokumentu: | Working Paper |
| DOI: | 10.1145/2500365.2500604 |
| Popis: | 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. Comment: Proceedings of the International Conference on Functional Programming 2013 (ICFP 2013). Boston, Massachusetts. September, 2013 |
| Databáze: | arXiv |
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