Algebraic fusion of functions with an accumulating parameter and its improvement

• Authors: Shin-ya Katsumata;Susumu Nishimura
• Venue: Journal of Functional Programming
• Year: 2008

This paper develops a new framework for fusion that is designed for eliminating the intermediate data structures involved in the composition of functions that have one accumulating parameter. The new fusion framework comprises two steps: algebraic fusion and its subsequent improvement process. The key idea in our development is to regard functions with an accumulating parameter as functions that operate over the monoid of data contexts. Algebraic fusion composes each such function with a monoid homomorphism that is derived from the definition of the consumer function to obtain a higher-order function that computes over the monoid of endofunctions. The transformation result may be further refined by an improvement process, which replaces the operation over the monoid of endofunctions (i.e., function closures) with another monoid operation over a monoid structure other than function closures. Using our framework, one can formulate a particular solution to the fusion problem by devising appropriate monoids and monoid homomorphisms. This provides a unified exposition of a variety of fusion methods that have been developed so far in different formalisms. Furthermore, the cleaner formulation makes it possible to argue about some delicate issues on a firm mathematical basis. We demonstrate that algebraic fusion and improvement in the world of complete pointed partial orders (CPOs) and continuous functions can correctly fuse functions that operate on partial and infinite data structures. We also show that subtle differences in termination behaviours of transformed programmes caused by certain different fusion methods can be cleanly explained by corresponding improvement processes that have different underlying monoid structures.