We introduce a new transformation method to eliminate intermediate data structures occurring in functional programs due to repeated list concatenations and other data manipulations (additionally exemplified with list reversal and mapping of functions over lists). The general idea is to uniformly abstract from data constructors and manipulating operations by means of rank-2 polymorphic combinators that exploit algebraic properties of these operations to provide an optimized implementation. The correctness of transformations is proved by using the free theorems derivable from parametric polymorphic types.

Many functional programs with accumulating parameters are contained in the class of macro tree transducers. We present a program transformation technique that can be used to solve the efficiency problems due to creation and consumption of intermediate data structures in compositions of such functions, where classical deforestation techniques fail. In order to do so, given two macro tree transducers under appropriate restrictions, we construct a single macro tree transducer that implements the composition of the two original ones. The imposed restrictions are more liberal than those in the literature on macro tree transducer composition, thus generalising previous results.

Abstract programming supports the separation of logical concerns from issues of control in program construction. While this separation of concerns leads to reduced code size and increased reusability of code, its main disadvantage is the computational overhead it incurs. Fusion techniques can be used to combine the reusability of abstract programs with the e#ciency of specialized programs.