We introduce a new compile-time notion of type subsumption based on type simulation. We show how to apply this static subsumption relation to support a more intuitive, object oriented approach to generic programming of reusable, high performance container types. As a first step towards an efficient implementation of the resulting type system in a compiler we present a novel algorithm for bidirectional type inference over arbitrary syntax graphs. The algorithm uses the new static type subsumption relation to compress the data that has to be stored for each node in the typeflow graph. During typeflow analysis this means that the set of types for a given node can be symbolically represented using antichains instead of using bitvectors or some other explicit set representation. This results in a typing algorithm that is both flexible and precise and shows good performance on representative instances.
It was found independently by Hindley @cite_9 and Milner @cite_12 that polymorphic types were useful for structuring programs. Since the early contributions of Hindley and Milner many alternatives and extensions to their approach have been suggested in the literature @cite_5 @cite_16 @cite_18 @cite_1 @cite_6 @cite_15 .
@cite_18 @cite_9 @cite_1 @cite_6 @cite_5 @cite_15 @cite_16 @cite_12
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Dealing with polymorphism in the presence of imperative features is a long-standing open problem for Hindley-Milner type systems. A widely adopted approach is the value restriction, which inhibits polymorphic generalisation and unfairly rejects various programs that cannot go wrong. We consider abstract interpretation as a tool for constructing safe and precise type systems, and investigate how to derive store-based types by abstract interpretation. We propose store-based types as a type discipline that holds potential for interesting and flexible alternatives to the value restriction. Starting from a denotational semantics of the eager untyped lambda-calculus with explicit runtime errors, the standard collecting semantics is defined as specifying the strongest program properties. By a first abstraction, a new sound type collecting semantics is derived in compositional fix-point form. Then by successive (semi-dual) Galois connection based abstractions, type systems and or type inference algorithms are designed as abstract semantics or abstract interpreters approximating the type collecting semantics. This leads to a hierarchy of type systems, which is part of the lattice of abstract interpretations of the untyped lambda-calculus. This hierarchy includes two new � la Church Curry polytype systems. Abstractions of this polytype semantics lead to classical Milner Mycroft and Damas Milner polymorphic type schemes, Church Curry monotypes and Hindley principal typing algorithm. This shows that types are abstract interpretations. Many type inference and program analysis systems include notions of subtyping and parametric polymorphism. When used together, these two features induce equivalences that allow types to be simplified by eliminating quantified variables. Eliminating variables both improves the readability of types and the performance of algorithms whose complexity depends on the number of type variables. We present an algorithm for simplifying quantified types in the presence of subtyping and prove it is sound and complete for non-recursive and recursive types. We also show that an extension of the algorithm is sound but not complete for a type language with intersection and union types, as well as for a language of constrained types. A polymorphic, constraint-based type inference algorithm for an object-oriented language is defined. A generalized form of type, polymorphic recursively constrained types, are inferred. These types are expressive enough for typing objects, since they generalize recursive types and F-bounded polymorphism. The well-known tradeoff between inheritance and subtyping is mitigated by the type inference mechanism. Soundness and completeness of type inference are established.