We present λ CIL , a typed λ-calculus which serves as the foundation for a typed intermediate language for optimizing compilers for higher-order polymorphic programming languages. The key innovation of λ CIL is a novel formulation of intersection and union types and flow labels on both terms and types. These flow types can encode polyvariant control and data flow information within a polymorphically typed program representation. Flow types can guide a compiler in generating customized data representations in a strongly typed setting. Since λ CIL enjoys confluence, standardization, and subject reduction properties, it is a valuable tool for reasoning about programs and program transformations.

The CIL compiler for core Standard ML compiles whole ML programs using a novel typed intermediate language that supports the generation of type-safe customized data representations. In this paper, we present empirical data comparing the relative efficacy of several different flow-based customization strategies for function representations. We develop a cost model to interpret dynamic counts of operations required for each strategy. In this cost model, customizing the representation of closed functions gives a 12-17% improvement on average over uniform closure representations, depending on the layout of the closure. We also present data on the relative effectiveness of various strategies for reducing representation pollution, i.e., situations where flow constraints require the representation of a value to be less efficient than it would be in ideal circumstances. For the benchmarks tested and the types of representation pollution detected by our compiler, the pollution removal strategies we consider often cost more in overhead than they gain via enabled customizations. Notable exceptions are selective defunctionalization, a function representation strategy that often achieves significant customization benefits via aggressive pollution removal, and a simple form of flow-directed inlining, in which pollution removal allows multiple functions to be inlined at the same call site.

We present a new framework for transforming data representations in a strongly typed intermediate language. Our method allows both value producers (sources) and value consumers (sinks) to support multiple representations, automatically inserting any required code. Specialized representations can be easily chosen for particular source/sink pairs.The framework is based on these techniques:1. Flow annotated types encode the "flows-from" (source) and "flows-to" (sink) information of a flow graph.2. Intersection and union types support (a) encoding precise flow information, (b) separating flow information so that transformations can be well typed, (c) automatically reorganizing flow paths to enable multiple representations.As an instance of our framework, we provide a function representation transformation that encompasses both closure conversion and inlining. Our framework is adaptable to data other than functions.

Over the last several years, much interesting work has been done in modelling object-oriented programming languages in terms of extensions of the bounded second-order lambda calculus, F . Unfortunately, it has recently been shown by Pierce ([Pie92]) that type checking F is undecidable. Moreover, he showed that the undecidability arises in the seemingly simpler problem of determining whether one type is a subtype of another. In [Bru93a, Bru93b], the first author introduced a statically-typed, functional, object-oriented programming language, TOOPL, which supports classes, objects, methods, instance variables, subtypes, and inheritance. The semantics of TOOPL is based on F , so the question arises whether type checking in this language is decidable. In this paper we show that type checking for TOOPLE, a minor variant of TOOPL (Typed Object-Oriented Programming Language), is decidable. The proof proceeds by showing that subtyping is decidable, that all terms of TOOPLE have minimum types...