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Proceedings of the ACM on Programming Languages
Article . 2020 . Peer-reviewed
License: CC BY ND
Data sources: Crossref
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DBLP
Article . 2020
Data sources: DBLP
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Effects as capabilities: effect handlers and lightweight effect polymorphism

Authors: Jonathan Immanuel Brachthäuser; Philipp Schuster; Klaus Ostermann;

Effects as capabilities: effect handlers and lightweight effect polymorphism

Abstract

Effect handlers have recently gained popularity amongst programming language researchers. Existing type- and effect systems for effect handlers are often complicated and potentially hinder a wide-spread adoption. We present the language Effekt with the goal to close the gap between research languages with effect handlers and languages for working programmers. The design of Effekt revolves around a different view of effects and effect types. Traditionally, effect types express which side effects a computation might have. In Effekt, effect types express which capabilities a computation requires from its context. While this new point in the design space of effect systems impedes reasoning about purity, we demonstrate that it simplifies the treatment of effect polymorphism and the related issues of effect parametricity and effect encapsulation. To guarantee effect safety, we separate functions from values and treat all functions as second-class. We define the semantics of Effekt as a translation to System Xi, a calculus in explicit capability-passing style.

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    55
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
55
Top 1%
Top 10%
Top 10%
Published in a Diamond OA journal