The use of monads to structure functional programs is described. Monads provide a convenient framework for simulating e ects found in other languages, such as global state, exception handling, output, or non-determinism. Three case studies are looked at in detail: how monads ease the modi cation of a simple evaluator; how monads act as the basis of a datatype of arrays subject to in-place update; and how monads can be used to build parsers.

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.

The type and effect discipline is a new framework for reconstructing the principal type and the minimal effect of expressions in implicitly typed polymorphic functional languages that support imperative constructs. The type and effect discipline outperforms other polymorphic type systems. Just as types abstract collections of concrete values, effects denote imperative operations on regions. Regions abstract sets of possibly aliased memory locations. Effects are used to control type generalization in the presence of imperative constructs while regions delimit observable side-effects. The observable effects of an expression range over the regions that are free in its type environment and its type; effects related to local data structures can be discarded during type reconstruction. The type of an expression can be generalized with respect to the variables that are not free in the type environment or in the observable effect. 1 Introduction Type inference [12] is the process that automa...

We present a new static system that reconstructs the types, regions and effects of expressions in an implicitly typed functional language that supports imperative operations on reference values. Just as types structurally abstract collections of concrete values, regions represent sets of possibly aliased reference values and effects represent approximations of the imperative behavior on regions. We introduce a static semantics for inferring types, regions and effects and prove that it is consistent with respect to the dynamic semantics of the language. We present a reconstruction algorithm that computes the types and effects of expressions and assigns regions to reference values. We prove the correctness of the reconstruction algorithm with respect to the static semantics. Finally, we discuss potential applications of our system to automatic stack allocation and parallel code generation.

Abstract not found

Standard ML is an excellent language for many kinds of programming. It is safe, efficient, suitably abstract, and concise. There are many aspects of the language that work well. However, nothing is perfect: Standard ML has a few shortcomings. In some cases there are obvious solutions, and in other cases further research is required.

Functional programming may be beautiful, but to write real applications we must grapple with awkward real-world issues: input/output, robustness, concurrency, and interfacing to programs written in other languages. These lecture notes give an overview of the techniques that have been developed by the Haskell community to address these problems. I introduce various proposed extensions to Haskell along the way, and I offer an operational semantics that explains what these extensions mean. This tutorial was given at the Marktoberdorf Summer School 2000. It will appears in the book “Engineering theories of software construction, Marktoberdorf Summer School 2000”, ed CAR Hoare, M Broy, and R Steinbrueggen, NATO ASI Series, IOS Press, 2001, pp47-96. This version has a few errors corrected compared with the published version. Change summary: Apr 2005: some examples added to Section 5.2.2, to clarifyevaluate. March 2002: substantial revision 1

Region Inference is a technique for implementing programming languages that are based on typed call-by-value lambda calculus, such as Standard ML. The mathematical runtime model of region inference uses a stack of regions, each of which can contain an unbounded number of values. This paper is concerned with mapping the mathematical model onto real machines. This is done by composing region inference with Region Representation Inference, which gradually refines region information till it is directly implementable on conventional von Neumann machines. The performance of a new region-based ML compiler is compared to the performance of Standard ML of New Jersey, a state-of-the-art ML compiler. 1 Introduction It has been suggested that programming languages which are based on typed call-by-value lambda calculus can be implemented using regions for memory management[17]. At runtime, the store consists of a stack of regions. All values, including function closures, are put into regions. Reg...

A number of useful optimisations are enabled if we can determine when a value is accessed at most once. We extend the Hindley-Milner type system with uses, yielding a typeinference based program analysis which determines when values are accessed at most once. Our analysis can handle higher-order functions and data structures, and admits principal types for terms. Unlike previous analyses, we prove our analysis sound with respect to call-by-need reduction. Call-by-name reduction does not provide an accurate model of how often a value is used during lazy evaluation, since it duplicates work which would actually be shared in a real implementation. Our type system can easily be modified to analyse usage in a call-by-value language. 1 Introduction This paper describes a method for determining when a value is used at most once. Our method is based on a simple modification of the Hindley-Milner type system. Each type is labelled to indicate whether the corresponding value is used at most onc...

Let S be some type system. A typing in S for a typable term M is the collection of all of the information other than M which appears in the final judgement of a proof derivation showing that M is typable. For example, suppose there is a derivation in S ending with the judgement A M : # meaning that M has result type # when assuming the types of free variables are given by A. Then (A, #) is a typing for M .