Abstract not found

The design of a module system for constructing and main- taining large programs is a difficult task that raises a number of theoretical and practical issues. A fundamental issue is the management of the flow of information between program units at compile time via the notion of an interface. Experience has shown that fully opaque interfaces are awkward to use in practice since too much information is hidden, and that fully transparent interfaces lead to excessive interdependencies, creating problems for maintenance and separate compilation. The "sharing" specifications of Standard ML address this issue by allowing the programmer to specify equational relationships between types in separate modules, but are not expressive enough to allow the programmer com- plete control over the propagation of type information be- tween modules.

We describe a new compiler for Standard ML called TIL, that is based on four technologies: intensional polymorphism, tag-free garbage collection, conventional functional language optimization, and loop optimization. We use intensional polymorphism and tag-free garbage collection to provide specialized representations, even though SML is a polymorphic language. We use conventional functional language optimization to reduce the cost of intensional polymorphism, and loop optimization to generate good code for recursive functions. We present an example of TIL compiling an SML function to machine code, and compare the performance of TIL code against that of a widely used compiler, Standard ML of New Jersey.

Region-based memory management is an alternative to standard tracing garbage collection that makes potentially dangerous operations such as memory deallocation explicit but verifiably safe. In this article, we present a new compiler intermediate language, called the Capability Calculus, that supports region-based memory management and enjoys a provably safe type system. Unlike previous region-based type systems, region lifetimes need not be lexically scoped and yet the language may be checked for safety without complex analyses. Therefore, our type system may be deployed in settings such as extensible operating systems where both the performance and safety of untrusted code is important.

Standard ML is one of a number of new programming languages developed in the 1980s that are seen as suitable vehicles for serious systems and applications programming. It offers an excellent ratio of expressiveness to language complexity, and provides competitive efficiency. Because of its type and module system, Standard ML manages to combine safety, security, and robustness with much of the flexibility of dynamically typed languages like Lisp. It is also has the most well-developed scientific foundation of any major language. Here I review the strengths and weaknesses of Standard ML and describe some of what we have learned through the design, implementation, and use of the language.

The views and conclusions contained in this document are those of the authors and should not be interpreted as representing o cial policies, either expressed or implied, of the Advanced Research Projects Agency or the U.S. Government. Any opinions, ndings, and conclusions or recommendations expressed in this material are those of the We study the typing properties of closure conversion for simply-typed and polymorphic-calculi. Unlike most accounts of closure conversion, which only treat the untyped-calculus, we translate well-typed source programs to well-typed target programs. This allows later compiler phases to take advantage of types for representation analysis and tag-free garbage collection, and it facilitates correctness proofs. Our account of closure conversion for the simply-typed language takes advantage of a simple model of objects by mapping closures to existentials. Closure conversion for the polymorphic language requires additional type machinery, namely translucency in the style of Harper and Lillibridge's module calculus, to express the type of a closure.

Soft type systems provide the benefits of static type checking for dynamically typed languages without rejecting untypable programs. A soft type checker infers types for variables and expressions and inserts explicit run-time checks to transform untypable programs to typable form. We describe a practical soft type system for R4RS Scheme. Our type checker uses a representation for types that is expressive, easy to interpret, and supports efficient type inference. Soft Scheme supports all of R4RS Scheme, including procedures of fixed and variable arity, assignment, continuations, and top-level definitions. Our implementation is available by anonymous FTP. The first author was supported in part by the United States Department of Defense under a National Defense Science and Engineering Graduate Fellowship. y The second author was supported by NSF grant CCR-9122518 and the Texas Advanced Technology Program under grant 003604-014. 1 Introduction Dynamically typed languages like Scheme...

Compilers for monomorphic languages, such as C and Pascal, take advantage of types to determine data representations, alignment, calling conventions, and register selection. However, these languages lack important features including polymorphism, abstract datatypes, and garbage collection. In contrast, modern programming languages such as Standard ML (SML), provide all of these features, but existing implementations fail to take full advantage of types. The result is that performance of SML code is quite bad when compared to C. In this thesis, I provide a general framework, called type-directed compilation, that allows compiler writers to take advantage of types at all stages in compilation. In the framework, types are used not only to determine efficient representations and calling conventions, but also to prove the correctness of the compiler. A key property of typedirected compilation is that all but the lowest levels of the compiler use typed intermediate languages. An advantage of this approach is that it provides a means for automatically checking the integrity of the resulting code. An important

We investigate whether the π-calculus is able to serve as a good foundation for the design and implementation of a strongly-typed concurrent programming language. The first half of the dissertation examines whether the π-calculus supports a simple type system which is flexible enough to provide a suitable foundation for the type system of a concurrent programming language. The second half of the dissertation considers how to implement the π-calculus efficiently, starting with an abstract machine for π-calculus and finally presenting a compilation of π-calculus to C. We start the dissertation by presenting a simple, structural type system for π-calculus, and then, after proving the soundness of our type system, show how to infer principal types for π-terms. This simple type system can be extended to include useful type-theoretic constructions such as recursive types and higherorder polymorphism. Higher-order polymorphism is important, since it gives us the ability to implement abstract datatypes in a type-safe manner, thereby providing a greater degree of modularity for π-calculus programs. The functional computational paradigm plays an important part in many programming languages. It is well-known that the π-calculus can encode functional computation. We go further and show that the type structure of λ-terms is preserved by such encodings, in the sense that we can relate the type of a λ-term to the type of its encoding in the π-calculus. This means that a π-calculus programming language can genuinely support typed functional programming as a special case. An efficient implementation of π-calculus is necessary if we wish to consider π-calculus as an operational foundation for concurrent programming. We first give a simple abstract machine for π-calculus and prove it correct. We then show how this abstract machine inspires a simple, but efficient, compilation of π-calculus to C (which now forms the basis of the Pict programming language implementation).

. This paper describes a simple extension of the Hindley-Milner polymorphic type discipline to call-by-value languages that incorporate imperative features like references, exceptions, and continuations. This extension sacrifices the ability to type every purely functional expression that is typable in the Hindley-Milner system. In return, it assigns the same type to functional and imperative implementations of the same abstraction. Hence with a module system that separates specifications from implementations, imperative features can be freely used to implement polymorphic specifications. A study of a number of ML programs shows that the inability to type all Hindley-Milner typable expressions seldom impacts realistic programs. Furthermore, most programs that are rendered untypable by the new system can be easily repaired. Keywords: Continuations, functional programming, polymorphism, references, state 1. Polymorphism, Imperative Features, and Modules The Hindley-Milner polymorphic ty...