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LeoParDS is a new tool for learning broadcast protocols (BPs) from a set of positive and negative example traces. It is the first tool that enables learning of a distributed computational model in a parameterized setting, i.e., with a parametric number of processes running the BP concurrently. We describe the tool along a running example, discuss some implementation details, and present experimental results on randomly generated BPs.

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Learning Broadcast Protocols with LeoParDS

  • 会议论文

  • 发表日期：

    2025年

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  • Noa Izsak,
  • Dana Fisman,
  • Swen Jacobs

摘要

LeoParDS is a new tool for learning broadcast protocols (BPs) from a set of positive and negative example traces. It is the first tool that enables learning of a distributed computational model in a parameterized setting, i.e., with a parametric number of processes running the BP concurrently. We describe the tool along a running example, discuss some implementation details, and present experimental results on randomly generated BPs.