Skip to main content
Kent Academic Repository

Unifying graded and parameterised monads

Orchard, Dominic, Wadler, Philip, Eades, Harley (2020) Unifying graded and parameterised monads. Proceedings Eighth Workshop on Mathematically Structured Functiona Programming, MSFP@ETAPS 2020, Dublin, Ireland, 25th April 2020, . (KAR id:84635)

Abstract

Monads are a useful tool for structuring effectful features of computation such as state, non-determinism, and continuations. In the last decade, several generalisations of monads have been suggested which provide a more fine-grained model of effects by replacing the single type constructor of a monad with an indexed family of constructors. Most notably, graded monads (indexed by a monoid) model effect systems and parameterised monads (indexed by pairs of pre- and post-conditions) model program logics. This paper studies the relationship between these two generalisations of monads via a third generalisation. This third generalisation, which we call category-graded monads, arises by generalising a view of monads as a particular special case of lax functors. A category-graded monad provides a family of functors T f indexed by morphisms f of some other category. This allows certain compositions of effects to be ruled out (in the style of a program logic) as well as an abstract description of effects (in the style of an effect system). Using this as a basis, we show how graded and parameterised monads can be unified, studying their similarities and differences along the way.

Item Type: Article
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Dominic Orchard
Date Deposited: 30 Nov 2020 11:00 UTC
Last Modified: 25 Nov 2021 11:51 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/84635 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.