Abstract nonsense

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Abstract

The notion of effect in programming languages has evolved significantly since the works of Lucassen and Gifford – where an effect system tracks memory regions and enables the improvement of parallel execution – to the point where an algebraic characterisation of effects is proposed. In this work, our interest lies in an algebraic investigation of effects and how optimisable they are. Therefore, we propose a calculus, lambda genArt, that targets the development of generative art, which inherently demands effectful computations. We provide the semantics and type system of lambda genArt, alongside an effect algebra and a new parallel constructor. We implemented the calculus as a DSL for the Haskell programming language and introduced optimisations based on the effect information. This work is the first step towards the specification and implementation of a declarative functional language for generative art based on algebraic effects and handlers.
Original languageEnglish
Title of host publicationFARM 2018 - Proceedings of the 6th ACM SIGPLAN International Workshop on Functional Art, Music, Modeling, and Design : Co-located with ICFP 2018
EditorsBrent Yorgey, Donya Quick
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Publication date2018
Pages26-37
DOIs
Publication statusPublished - 2018
EventThe 6th ACM SIGPLAN International Workshop on Functional Art, Music, Modeling, and Design - St. Louis, Missouri, United States
Duration: 29 Sep 201829 Sep 2018
https://icfp18.sigplan.org/track/farm-2018-papers#About
https://functional-art.org/2018/

Workshop

WorkshopThe 6th ACM SIGPLAN International Workshop on Functional Art, Music, Modeling, and Design
CountryUnited States
CitySt. Louis, Missouri
Period29/09/201829/09/2018
Internet address

Cite this

Gonçalves, J. (2018). Abstract nonsense. In B. Yorgey, & D. Quick (Eds.), FARM 2018 - Proceedings of the 6th ACM SIGPLAN International Workshop on Functional Art, Music, Modeling, and Design: Co-located with ICFP 2018 (pp. 26-37). Association for Computing Machinery. https://doi.org/10.1145/3242903.3242908