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Journal Articles The Computer Journal Year : 2023

SASA : a SimulAtor of Self-stabilizing Algorithms

Karine Altisen
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Erwan Jahier
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In this paper, we present sasa, an open-source SimulAtor of Self-stabilizing Algorithms. Self-stabilization defines the ability of a distributed algorithm to recover after transient failures. sasa is implemented as a faithful representation of the atomic-state model (also called the locally shared memory model with composite atomicity). This model is the most commonly used one in the self-stabilizing area to prove both the correct operation of self-stabilizing algorithms and complexity bounds on them. sasa encompasses all features necessary to debug, test and analyze self-stabilizing algorithms. All these facilities are programmable to enable users to accommodate to their particular needs. For example, asynchrony is modeled by programmable stochastic daemons playing the role of input sequence generators. Properties of algorithms can be checked using formal test oracles. The sasa distribution also provides several facilities to easily achieve (batch-mode) simulation campaigns. We show that the lightweight design of sasa allows to efficiently perform huge such campaigns. Following a modular approach, we have aimed at relying as much as possible the design of sasa on existing tools, including ocaml, dot and several tools developed in the Synchrone Group of the VERIMAG laboratory.
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hal-03603835 , version 1 (06-04-2022)



Karine Altisen, Stéphane Devismes, Erwan Jahier. SASA : a SimulAtor of Self-stabilizing Algorithms. The Computer Journal, 2023, 66 (4), pp.796-814. ⟨10.1093/comjnl/bxab196⟩. ⟨hal-03603835⟩
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