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zbMATH Open
Article . 2016
Data sources: zbMATH Open
DBLP
Article . 2016
Data sources: DBLP
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May-Happen-in-Parallel Analysis for Actor-Based Concurrency

May-happen-in-parallel analysis for actor-based concurrency
Authors: Elvira Albert; Antonio Flores-Montoya; Samir Genaim; Enrique Martin-Martin;

May-Happen-in-Parallel Analysis for Actor-Based Concurrency

Abstract

This article presents a may-happen-in-parallel (MHP) analysis for languages with actor-based concurrency . In this concurrency model, actors are the concurrency units such that, when a method is invoked on an actor a 2 from a task executing on actor a 1 , statements of the current task in a 1 may run in parallel with those of the (asynchronous) call on a 2 , and with those of transitively invoked methods. The goal of the MHP analysis is to identify pairs of statements in the program that may run in parallel in any execution. Our MHP analysis is formalized as a method-level ( local ) analysis whose information can be modularly composed to obtain application-level ( global ) information. The information yielded by the MHP analysis is essential to infer more complex properties of actor-based concurrent programs, for example, data race detection, deadlock freeness, termination, and resource consumption analyses can greatly benefit from the MHP relations to increase their accuracy. We report on MayPar, a prototypical implementation of an MHP static analyzer for a distributed asynchronous language.

Related Organizations
Keywords

Other programming paradigms (object-oriented, sequential, concurrent, automatic, etc.), actors, analysis, Theory of programming languages, concurrency, may-happen-in-parallel

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    popularity
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    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!
15
Top 10%
Top 10%
Top 10%
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