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The Art Science and Engineering of Programming
Article . 2019 . Peer-reviewed
Data sources: Crossref
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https://dx.doi.org/10.48550/ar...
Article . 2019
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2019
Data sources: DBLP
DBLP
Article . 2019
Data sources: DBLP
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Distributed Reactive Programming for Reactive Distributed Systems

Authors: Florian Myter; Christophe Scholliers; Wolfgang De Meuter;

Distributed Reactive Programming for Reactive Distributed Systems

Abstract

Context: The term reactivity is popular in two areas of research: programming languages and distributed systems. On one hand, reactive programming is a paradigm which provides programmers with the means to declaratively write event-driven applications. On the other hand, reactive distributed systems handle client requests in a timely fashion regardless of load or failures. Inquiry: Reactive programming languages and frameworks tailored to the implementation of distributed systems have previously been proposed. However, we argue that these approaches are ill fit to implement reactive distributed systems. Approach: We analyse state of the art runtimes for distributed reactive programming and identify two key issues with regards to reactive distributed systems. They rely on single, central points of coordination and/or assume a lack of partial failures in the systems they support. Knowledge: Based on our analysis we propose a novel runtime for distributed reactive programming languages and frameworks. This runtime supports reactive distributed systems by design. Grounding: We implement a proof of concept framework for reactive distributed systems in JavaScript which builds atop our runtime. Using this framework we implement a case study application which highlights the applicability of our approach. Moreover, we benchmark our runtime against a similar approach in order to showcase its runtime properties and we prove its correctness. Importance: This work aims to bridge the gap between two kinds of reactivity: reactive distributed systems and distributed reactive programming. Current distributed reactive programming approaches do not support reactive distributed systems. Our runtime is the first to bridge this reactivity gap: it allows for reactive distributed systems to be implemented using distributed reactive programming.

Country
Belgium
Keywords

FOS: Computer and information sciences, Technology and Engineering, Mathematics and Statistics, Computer Science - Programming Languages, Programming Languages (cs.PL)

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    popularity
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    Top 10%
    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!
13
Top 10%
Top 10%
Top 10%
Green
gold