Abstract.Restricting polymorphism to values is now the standard way to obtain soundness in ML-like programming languages with imperative features. While this solution has undeniable advantages over previous approaches, it forbids polymorphism in many cases where it would be sound. We use a subtyping based approach to recover part of this lost polymorphism, without changing the type algebra itself, and this has significant applications.

We propose a modest conservative extension to ML that allows semiexplicit first-class polymorphism while preserving the essential properties of type inference. In our proposal, the introduction of polymorphic types is fully explicit, that is, both introduction points and exact polymorphic types are to be specified. However, the elimination of polymorphic types is semiimplicit: only elimination points are to be specified as polymorphic types themselves are inferred. This extension is particularly useful in Objective ML where polymorphism replaces subtyping.

Abstract. We propose a modest conservative extension to ML that allows semi-explicit higher-order polymorphism while preserving the essential properties of ML.

Abstract. GADTs, short for Generalized Algebraic DataTypes, which allow constructors of algebraic datatypes to be non-surjective, have many useful applications. However, pattern matching on GADTs introduces local type equality assumptions, which are a source of ambiguities that may destroy principal typesand must be resolved by type annotations. We introduce ambivalent types to tighten the definition of ambiguities and better confine them, so that type inference has principal types, remains monotonic, and requires fewer type annotations.

The type system of Objective Caml has many unique features, which make ensuring the correctness of its implementation difficult. One of these features is structurally polymorphic types, such as polymorphic object and variant types, which have the extra specificity of allowing recursion. We implemented in Coq a certified interpreter for Core ML extended with structural polymorphism and recursion. Along with type soundness of evaluation, soundness and principality of type inference, and correctness of a stack-based interpreter, are also proved.†