Parameterized synthesis of self-stabilizing protocols in symmetric networks

Mirzaie, Nahal; Faghih, Fathiyeh; Jacobs, Swen; Bonakdarpour, Borzoo

doi:10.1007/s00236-019-00361-7

Cited by 4 publications

(1 citation statement)

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“…The designer provides a set of legitimate states and the size of the template process, and the procedure yields a completed self-stabilizing template. A similar approach for more general topologies is presented in [28]. Bertrand et al [6] target systems composed of an unbounded number of agents that are fully specified and one underspecified controller process.…”

Section: Related Workmentioning

confidence: 99%

Synthesis of Distributed Agreement-Based Systems with Efficiently-Decidable Verification

Jaber

Wagner

Jacobs

et al. 2023

Lecture Notes in Computer Science

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Distributed agreement-based (DAB) systems use common distributed agreement protocols such as leader election and consensus as building blocks for their target functionality. While automated verification for DAB systems is undecidable in general, recent work identifies a large class of DAB systems for which verification is efficiently-decidable. Unfortunately, the conditions characterizing such a class can be opaque and non-intuitive, and can pose a significant challenge to system designers trying to model their systems in this class.In this paper, we present a synthesis-driven tool, Cinnabar, to help system designers building DAB systems ensure that their intended designs belong to an efficiently-decidable class. In particular, starting from an initial sketch provided by the designer, Cinnabar generates sketch completions using a counterexample-guided procedure. The core technique relies on compactly encoding root-causes of counterexamples to varied properties such as efficient-decidability and safety. We demonstrate Cinnabar ’s effectiveness by successfully and efficiently synthesizing completions for a variety of interesting DAB systems including a distributed key-value store and a distributed consortium system.

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Section: Related Workmentioning

confidence: 99%