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

机译:基于Actor的并发的May-Happen-in-Parallel分析

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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 alpha(2) from a task executing on actor alpha(1), statements of the current task in alpha(1) may run in parallel with those of the (asynchronous) call on alpha(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.
机译:本文介绍了基于参与者基于并发的语言的May-happen-in-parallel(MHP)分析。在此并发模型中,参与者是并发单元,因此,当从在参与者alpha(1)上执行的任务在参与者alpha(2)上调用方法时,alpha(1)中当前任务的语句可以并行运行与对alpha(2)的(异步)调用的方法以及与传递调用方法的方法的方法。 MHP分析的目标是识别程序中可以在任何执行中并行运行的语句对。我们的MHP分析形式化为方法级别(本地)分析,其信息可以模块化地组合以获得应用程序级别(全局)信息。 MHP分析产生的信息对于推断基于actor的并发程序的更复杂属性至关重要,例如,数据竞争检测,死锁释放,终止和资源消耗分析可以从MHP关系中大大受益,以提高其准确性。我们在MayPar上进行报告,MayPar是针对分布式异步语言的MHP静态分析器的原型实现。

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