Types for Flexible Objects

Palmer, Zachary; Menon, Pottayil Harisanker; Rozenshteyn, Alexander; Smith, Scott F.

doi:10.1007/978-3-319-12736-1_6

Cited by 3 publications

(1 citation statement)

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“…This problem has been already studied elsewhere: some authors define a dedicated form of implication, e.g. by extending the grammar of types, defining conditional types [2,8] and others extend the grammar of constraints, defining conditional constraints [11]. Despite the fact that it is more intuitive to extend the grammar of types with expressions saying that "if the argument is of type X then the result is of type Y", this technique fails to link the type of an argument with arbitrary other types, i.e.…”

Section: A Finer Typing Of Pattern Matching On Variantsmentioning

confidence: 99%

A Type Inference System Based on Saturation of Subtyping Constraints

Vaugon

Mauny

2019

Lecture Notes in Computer Science

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This paper 3 presents a powerful and flexible technique for defining type inference algorithms, on an ML-like language, that involve subtyping and whose soundness can be proved. We define a typing algorithm as a set of inference rules of three distinct forms: typing rules collect subtyping constraints to be satisfied, instantiation rules instantiate type schemes, and saturation rules specify how to check the validity and consistency of collected constraints. Essentially, type inference then proceeds in two intertwined phases: one that extracts constraints and the other that saturates the sets of constraints. Our technique extends easily to the treatment of high-level features such as polymorphism, overloading, variants and pattern-matching, or generalized algebraic data types (GADTs).

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Section: A Finer Typing Of Pattern Matching On Variantsmentioning

confidence: 99%