# Subtype Polymorphism à la carte via Machine Learning on Dependent Types

Johnson, Colin G., Swan, Jerry, Edwin, Brady (2018) Subtype Polymorphism à la carte via Machine Learning on Dependent Types. In: ML4PL. 2nd International Workshop on Machine Learning Techniques for Programming Languages. . ACM ISBN ACM ISBN 123-4567-24-567/08/06. (doi:10.475/123_4)

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## Abstract

The ability to write 'closed' frameworks in terms of abstract supertypes and subsequently extend them via contractually-conforming subtypes is a ubiquitous programming paradigm (e.g. underpinning Object-Orientation). While the motivation for such abstraction is to insulate against requirements change, any change of contract requires extensive (typically manual) refactoring, potentially throughout the entire class hierarchy. As an alternative to defining such abstractions a priori, we describe the broad role that Machine Learning can play in inducing abstractions from a pre-existing codebase. Concrete examples are given in which contacts are enforced by dependent types in the Idris language.

Item Type: Conference or workshop item (Paper) 10.475/123_4 Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, Faculties > Sciences > School of Computing Colin Johnson 30 Dec 2018 17:28 UTC 30 May 2019 08:41 UTC https://kar.kent.ac.uk/id/eprint/71461 (The current URI for this page, for reference purposes) https://orcid.org/0000-0002-9236-6581 https://orcid.org/0000-0003-1944-7147 https://orcid.org/0000-0002-9734-367X