Optimizing Lazy Functional Programs Using Flow Inference

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Optimizing Lazy Functional Programs Using Flow Inference (1995)

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by Karl-Filip Faxen

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@MISC{Faxen95optimizinglazy,
    author = {Karl-Filip Faxen},
    title = {Optimizing Lazy Functional Programs Using Flow Inference},
    year = {1995}
}

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Abstract

. Nonstrict higher order functional programming languages are notorious for their low run time efficiency. Optimizations based on flow analysis, which determines for each variable x in a program which expressions could have originated the value of x, can improve the situation by removing redundant eval and thunk operations, avoiding thunk updates, and allowing the use of unboxed representations of some data. We formulate flow analysis as an inference problem in a type system built using type inclusion constraints and an algorithm for solving these constraints is also given. 1 Introduction Polymorphically typed nonstrict higher order functional programming languages are a boon to the programmer because they provide powerful mechanisms for abstraction [11]. Equally, and for the same reasons, they are very difficult to compile to efficient code. Among the main obstacles are the frequent need to build thunks (representations for unevaluated expressions), test whether objects are thunks o...

Keyphrases

flow analysis order functional programming language thunk operation unboxed representation inference problem type inclusion constraint low run time efficiency powerful mechanism thunk update efficient code main obstacle unevaluated expression introduction polymorphically type system redundant eval frequent need

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