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.

We present two complementary improvements for abstract-interpretation-based flow analysis of higher-order languages: (1) abstract garbage collection and (2) abstract counting. Abstract garbage collection is an analog to its concrete counterpart: the analysis determines when an abstract resource has become unreachable, and then, re-allocates it as fresh. This prevents flow sets from joining during abstract interpretation, which has two immediate effects: (1) the precision of the interpretation increases and (2) its running time often falls. In abstract counting, the analysis tracks how many times an abstract resource has been allocated. A count of one implies that the abstract resource momentarily represents only one concrete resource. This knowledge, in turn, drives environment analysis, expanding the kind (rather than just the degree) of optimization available to the compiler.

We consider the problem of reconciling a dependently typed functional language with imperative features such as mutable higher-order state, pointer aliasing, and nontermination. We propose Hoare type theory (HTT), which incorporates Hoare-style specifications into types, making it possible to statically track and enforce correct use of side effects.

The main feature of HTT is the Hoare type {P}x:A{Q} specifying computations with precondition P and postcondition Q that return a result of type A. Hoare types can be nested, combined with other types, and abstracted, leading to a smooth integration with higher-order functions and type polymorphism.

We further show that in the presence of type polymorphism, it becomes possible to interpret the Hoare types in the “small footprint” manner, as advocated by separation logic, whereby specifications tightly describe the state required by the computation.

We establish that HTT is sound and compositional, in the sense that separate verifications of individual program components suffice to ensure the correctness of the composite program.