FreezeML:为一级多态性提供完整和简单的类型推断

Frank Emrich, S. Lindley, Jan Stolarek, J. Cheney, Jonathan Coates
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引用次数: 6

摘要

ML在提供静态类型多态性方面非常出色,程序员无需编写任何类型注释。这种简约的代价是程序员被限制在一种形式的多态性中,在这种形式中,量词只能出现在类型的最外层,类型变量只能用单态类型实例化。一般来说,不受限制的System F-style多态性的类型推断是不可确定的。然而,文献中有大量的建议来弥合ML和System f之间的差距。我们提出了一个新的建议,FreezeML,一个ML的保守扩展,有两个新特性。首先,let和lambda绑定器可以用任意System F类型注释。其次,变量的出现可能会被冻结,显式地禁用实例化。FreezeML配备了系统F之间的类型保持转换,并允许类型推断算法,这是算法W的扩展,它是健全和完整的,并且产生主要类型。
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FreezeML: complete and easy type inference for first-class polymorphism
ML is remarkable in providing statically typed polymorphism without the programmer ever having to write any type annotations. The cost of this parsimony is that the programmer is limited to a form of polymorphism in which quantifiers can occur only at the outermost level of a type and type variables can be instantiated only with monomorphic types. Type inference for unrestricted System F-style polymorphism is undecidable in general. Nevertheless, the literature abounds with a range of proposals to bridge the gap between ML and System F. We put forth a new proposal, FreezeML, a conservative extension of ML with two new features. First, let- and lambda-binders may be annotated with arbitrary System F types. Second, variable occurrences may be frozen, explicitly disabling instantiation. FreezeML is equipped with type-preserving translations back and forth between System F and admits a type inference algorithm, an extension of algorithm W, that is sound and complete and which yields principal types.
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