Crate finality_grandpa

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Finality gadget for blockchains.

https://github.com/w3f/consensus/blob/master/pdf/grandpa.pdf

Consensus proceeds in rounds. Each round, voters will cast a prevote and precommit message.

Votes on blocks are then applied to the blockchain, being recursively applied to blocks before them. A DAG is superimposed over the blockchain with the vote_graph logic.

Equivocation detection and vote-set management is done in the round module. The work for actually casting votes is done in the voter module.

Modules

  • Logic for a single round of GRANDPA.
  • Maintains the vote-graph of the blockchain.
  • A voter in GRANDPA. This transitions between rounds and casts votes.
  • Implementation of a VoterSet, representing the complete set of voters and their weights in the context of a round of the protocol.

Structs

  • A catch-up message, which is an aggregate of prevotes and precommits necessary to complete a round.
  • A commit message which is an aggregate of precommits.
  • Struct returned from validate_commit function with information about the validation result.
  • A commit message with compact representation of authentication data.
  • An equivocation (double-vote) in a given round.
  • Historical votes seen in a round.
  • A precommit for a block and its ancestors.
  • A prevote for a block and its ancestors.
  • A primary proposed block, this is a broadcast of the last round’s estimate.
  • A signed message.
  • A signed precommit message.
  • A signed prevote message.

Enums

  • Top-level error type used by this crate.
  • A protocol message or vote.

Traits

  • Arithmetic necessary for a block number.
  • Chain context necessary for implementation of the finality gadget.

Functions

  • Runs the callback with the appropriate CommitProcessingOutcome based on the given CommitValidationResult. Outcome is bad if ghost is undefined, good otherwise.
  • Validates a GRANDPA commit message.

Type Definitions

  • Authentication data for a set of many messages, currently a set of precommit signatures but in the future could be optimized with BLS signature aggregation.