Loading...
Abstracting extensible data types: Or, rows by any other name
Morris, J. Garrett McKinna, James
Morris, J. Garrett
McKinna, James
Citations
Altmetric:
Abstract
We present a novel typed language for extensible data types, generalizing and abstracting existing systems of row types and row polymorphism. Extensible data types are a powerful addition to traditional functional programming languages, capturing ideas from OOP-like record extension and polymorphism to modular compositional interpreters. We introduce row theories, a monoidal generalization of row types, giving a general account of record concatenation and projection (dually, variant injection and branching). We realize them via qualified types, abstracting the interpretation of records and variants over different row theories. Our approach naturally types terms untypable in other systems of extensible data types, while maintaining strong metatheoretic properties, such as coherence and principal types. Evidence for type qualifiers has computational content, determining the implementation of record and variant operations; we demonstrate this in giving a modular translation from our calculus, instantiated with various row theories, to polymorphic λ-calculus.
Description
This work is licensed under a Creative Commons Attribution 4.0 International License.
Date
2019-01
Journal Title
Journal ISSN
Volume Title
Publisher
Association for Computing Machinery (ACM)
Research Projects
Organizational Units
Journal Issue
Keywords
Citation
J. Garrett Morris and James McKinna. 2019. Abstracting extensible data types: Or, rows by any other name. Proc. ACM Program. Lang. 3, POPL, Article 12 (January 2019), 28 pages. DOI:https://doi.org/10.1145/3290325