Recent research on domain-specific languages propose to embed them into existing general-purpose languages. Typed higher-order languages have proven especially useful as meta languages because they provide a rich infrastructure of higher-order functions, types, and modules. Furthermore, it has been observed that embedded programs can be restricted to those having simple types using a technique called ``phantom types''. We prove, using an idealized higher-order language, that such an embedding is sound (i.e., when all object-language terms that can be embedded into the meta language are simply typed) and that it is complete (i.e., when all simply typed object-language terms can be embedded into the meta language). The soundness proof is shown by induction over meta-language terms using a Kripke logical relation. The completeness proof is shown by induction over object-language terms. Furthermore, we address the use of Haskell and Standard ML as meta-languages.
Normalization functions, as embodied in type-directed partial evaluation, map a simply-typed higher-order value into a representation of its long beta-eta normal form. However, being dynamically typed, the original Scheme implementation of type-directed partial evaluation does not restrict input values to be typed at all. Furthermore, neither the original Scheme implementation nor the original Haskell implementation guarantee that type-directed partial evaluation preserves types. We present three implementations of type-directed partial evaluation in Haskell culminating with a version that restricts the input to typed values and for which the proofs of type-preservation and normalization are automated.
Partial evaluation provides a solution to the disproportion between general programs that can be executed in several contexts and their specialized counterparts that can be executed efficiently. However, stand-alone partial evaluation is usually too costly when a program must be specialized at run time. We introduce a collection of byte-code combinators for OCaml, a dialect of ML, that provides run-time code generation for OCaml programs. We apply these byte-code combinators in semantics-directed compilation for an imperative language and in run-time specialization using type-directed partial evaluation.
Finally, we present an approach to compiling goal-directed programs, i.e., programs that backtrack and generate successive results: We first specify the semantics of a goal-directed language using a monadic semantics and a spectrum of monads. We then compile goal-directed programs by specializing their interpreter (i.e., by using the first Futamura projection), using type-directed partial evaluation. Through various back ends, including a run-time code generator, we generate ML code, C code, and OCaml byte code
Available as PostScript,