Portland State University. Department of Computer Science
Mark P. Jones
Date of Award
Master of Science (M.S.) in Computer Science
1 online resource (ix, 138 pages)
Haskell, Monad, Hoopl, Data flow computing, Functional programming languages, Program transformation (Computer programming)
Our work applies the dataflow algorithm to an area outside its traditional scope: functional languages. Our approach relies on a monadic intermediate language that provides low-level, imperative features like computed jumps and explicit allocations, while at the same time supporting high-level, functional-language features like case discrimination and partial application. We prototyped our work in Haskell using the HOOPL library and this dissertation shows numerous examples demonstrating its use. We prove the efficacy of our approach by giving a novel description of the uncurrying optimization in terms of the dataflow algorithm, as well as a complete implementation of the optimization using HOOPL.
Bailey, Justin George, "Using Dataflow Optimization Techniques with a Monadic Intermediate Language" (2012). Dissertations and Theses. Paper 508.