Läufer and Odersky - Type Inference For Abstract Polymorphic Data Types

I was reading MacQueen, Plotkin and Sethi's An Ideal Model for Recursive Polymorphic Types and the ACM web site came up with a great recommendation: Polymorphic Type Inference and Abstract Data Types by Läufer and Odersky. The former paper was written in 1983 and the latter in 1993. I wish someone had told me about this after I wrote this tutorial on Hindley-Milner type inference https://prooftoys.org/ian-grant/hm/,  see Lattices Everywhere. In particular it made me think about the way I handled recursive data types in that, simply as assumptions about the types of the constructors like nil and cons, deconstructors like hd and tl and predicates like null. I suppose that's not handling them, it's simply ignoring the issues? But what are the issues? I am going to try and do the same trick with some of the examples Läufer and Odersky give. MacQueen discusses existential types in his Using Dependent Types to Express Modular Structure, published in 1986. See also Jeremy Gibbons' really excellent Unfolding Abstract Datatypes (2008). 

Another recent discovery of mine is this project called Successor ML which is "the web page for discussion and documentation of designs for a successor to Standard ML." [Italics mine]. It doesn't mention Python, ...


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