About: Threshold guards are a basic primitive of many fault-tolerant algorithms that solve classical problems of distributed computing, such as reliable broadcast, two-phase commit, and consensus. Moreover, threshold guards can be found in recent blockchain algorithms such as Tendermint consensus. In this tutorial, we give an overview of the techniques implemented in Byzantine Model Checker (ByMC). ByMC implements several techniques for automatic verification of threshold-guarded distributed algorithms. These algorithms have the following features: (1) up to t of processes may crash or behave Byzantine; (2) the correct processes count messages and make progress when they receive sufficiently many messages, e.g., at least [Formula: see text]; (3) the number n of processes in the system is a parameter, as well as t; (4) and the parameters are restricted by a resilience condition, e.g., [Formula: see text]. Traditionally, these algorithms were implemented in distributed systems with up to ten participating processes. Nowadays, they are implemented in distributed systems that involve hundreds or thousands of processes. To make sure that these algorithms are still correct for that scale, it is imperative to verify them for all possible values of the parameters.   Goto Sponge  NotDistinct  Permalink

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  • Threshold guards are a basic primitive of many fault-tolerant algorithms that solve classical problems of distributed computing, such as reliable broadcast, two-phase commit, and consensus. Moreover, threshold guards can be found in recent blockchain algorithms such as Tendermint consensus. In this tutorial, we give an overview of the techniques implemented in Byzantine Model Checker (ByMC). ByMC implements several techniques for automatic verification of threshold-guarded distributed algorithms. These algorithms have the following features: (1) up to t of processes may crash or behave Byzantine; (2) the correct processes count messages and make progress when they receive sufficiently many messages, e.g., at least [Formula: see text]; (3) the number n of processes in the system is a parameter, as well as t; (4) and the parameters are restricted by a resilience condition, e.g., [Formula: see text]. Traditionally, these algorithms were implemented in distributed systems with up to ten participating processes. Nowadays, they are implemented in distributed systems that involve hundreds or thousands of processes. To make sure that these algorithms are still correct for that scale, it is imperative to verify them for all possible values of the parameters.
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  • Decentralization
  • Distributed computing problems
  • Nami Tamaki albums
  • Distributed computing
  • Blockchains
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