The Generalized Intensional Transformation for Implementing Lazy Functional Languages

Abstract

The intensional transformation is a promising technique for implementing lazy functional languages based on a demand-driven execution model. Despite its theoretical elegance and its simple and efficient execution model, the intensional transformation suffered, until now, from two main drawbacks: it could only be applied to programs that manipulate primitive data-types and it could only compile a simple (and rather restricted) class of higher-order functions. In this paper we remedy the above two deficiencies, obtaining a transformation algorithm that is applicable to mainstream lazy functional languages. The proposed transformation initially uses defunctionalization in order to eliminate higher-order functions from the source program. The original intensional transformation is then extended in order to apply to the target first-order language with user-defined data types that resulted from the defunctionalization. It is demonstrated that the proposed technique can be used to compile a relatively large subset of Haskell into portable C code whose performance is comparable to existing mainstream implementations.

Work partially supported by the research project “$\mathrm\Theta$A$\mathrm\Lambda$H$\mathrm\Sigma-$EM$\mathrm\Pi$: Handling uncertainty in data intensive applications on a distributed computing environment (cloud computing)” (MIS 380153), funded by the European Social Fund and the Greek national funds through the Operational Program “Education and Lifelong Learning”.