Generalized algebraic data types (GADTs), sometimes known as “guarded recursive data types ” or “first-class phantom types”, are a simple but powerful generalization of the data types of Haskell and ML. Recent works have given compelling examples of the utility of GADTs, although type inference is known to be difficult. Our contribution is to show how to exploit programmer-supplied type annotations to make the type inference task almost embarrassingly easy. Our main technical innovation is wobbly types, which express in a declarative way the uncertainty caused by the incremental nature of typical type-inference algorithms.

In almost all languages all arguments to functions are to be given explicitly. The Haskell class system however is an exception: functions can have class predicates as part of their type signature, and dictionaries are implicitly constructed and implicitly passed for such predicates, thus relieving the programmer from a lot of clerical work and removing clutter from the program text. Unfortunately Haskell maintains a very strict boundary between the implicit and the explicit world; if the implicit mechanisms fail to construct the hidden dictionaries there is no way the programmer can provide help, nor is he able to override the choices made by the implicit mechanisms. In this paper we describe, in the context of Haskell, a mechanism that allows the programmer to explicitly construct implicit arguments. This extension blends well with existing resolution mechanisms, since it only overrides the default behavior. We include a description of the use of partial type signatures, which liberates the programmer from having to choose between specifying a complete type signature or no type signature at all. Finally we show how the system can easily be extended to deal with higher-order predicates, thus enabling the elegant formulation of some forms of generic programming.

Abstract not found

Abstract. We present a uniqueness type system that is simpler than both Clean’s uniqueness system and a system we proposed previously. The new type system is straightforward to implement and add to existing compilers, and can easily be extended with advanced features such as higher rank types and impredicativity. We describe our implementation in Morrow, an experimental functional language with both these features. Finally, we prove soundness of the core type system with respect to the call-by-need lambda calculus. 1 Introduction to Uniqueness Typing An important property of pure functional programming languages is referential transparency: the same expression used twice must have the same value twice. This makes equational reasoning possible and aids program analysis, but most languages do not have this property. For example, in the following C fragment,

Dependent type systems, in which types can depend on values, admit detailed specifications of function behavior and data invariants. Programming languages based on System F do not have dependent types, and are therefore more limited in what structure or function invariants can be encoded in the type system. In this paper, we show how guarded algebraic datatypes can simulate dependent types. We formalize additions to a guarded-datatypesenhanced System F that allow types to depend on values. We discuss the resulting programming style, which is similar to theorem proving. Our technique can be applied to multiple existing programming languages, including Haskell and C#. We also introduce an idiom for eliminating any runtime costs associated with the use of simulated dependent types. We have developed a tool to automatically produce the boilerplate necessary for the simulation, and we have used it to enforce data structure invariants and to allow elision of runtime bounds checks.

Abstract. The more expressive a type system, the more type information has to be provided in a program. Having to provide a type is sometimes a pain, but lacking expressivity is often even worse. There is a continuous struggle between expressivity and (type-)verbosity. However, even very expressive type systems allow type inference for parts of a program. Generic Haskell is an extension of Haskell that supports defining generic functions. Generic Haskell assumes that the type of a generic function is explicitly specified. This is often no problem, but sometimes it is rather painful to have to specify a type – in particular for generic functions with many dependencies – and sometimes the specified type can be generalized. In this paper, we identify three type inference problems specific to generic functions, and present (partial) solutions to each of them. 1

Many predominantly lazy languages now incorporate strictness enforcing primitives, for example a strict let or sequential composition seq. Reasons for doing this include gains in time or space efficiencies, or control of parallel evaluation. This thesis studies how to prove equivalences between programs in languages with selective strictness, specifically, we use a restricted core lazy functional language with a selective strictness operator seq whose operational semantics is a variant of one considered by van Eckelen and de Mol, which itself was derived from Launchbury’s natural semantics for lazy evaluation. The main research contributions are as follows: We establish some of the first ever equivalences between programs with selective strictness. We do this by manipulating operational semantics derivations, in

Recent years have seen a revival of interest in extending ML’s predicative type inference system with impredicative quantification in the style of System F, for which type inference is undecidable. This paper suggests a modest extension of ML with System F types: the heart of the idea is to extend the language of types with unary universal and existential quantifiers. The introduction and elimination of a quantified type is never inferred but indicated explicitly by the programmer by supplying the quantified type itself. Quantified types co-exist with ordinary ML schemes, which are in turn implicitly introduced and eliminated at let-bindings and use sites, respectively. The resulting language, QML, does not impose any restriction on instantiating quantified variables with quantified types; neither let- nor λ-bound variables ever require a type annotation, even if the variable’s inferred scheme or type involves quantified types. This proposal, albeit more verbose in terms of annotations than others, is simple to specify, implement, understand, and formalize.

Abstract not found

Abstract not found