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EPF Week 3

Gm everyone! I will be working on improving the testing and doing the comparative tests of the verkle trees library.

Description

Once the Verkle implementation is done we'll want to run various tests to compare it to other implementations. I noticed the rust library did a nice fuzzing test, using a deterministic RNG. We could do the same (in Nim) using the same RNG and compare our results to theirs. The fuzzing test is currently a bit basic, it just generates key/values and adds them to the tree. We will enhance it to generate sparse/dense/deep trees to better test edge cases. Also, we could enhance it to perform additional actions on the tree, like deleting and fetching keys, or computing commitments and verifying proofs for random keys (i.e. each node down from the root) or batches of keys.

This would test for caching issues (we'll be caching commitments), and could also serve for benchmarking. It would also be nice to contribute back the extended test suite to the Rust and Go implementations, so we can compare the implmentations, and to help them debug their own.

RnD

Also there is the usual weekly meeting with the Nimbus and the OnlyDust team.

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Naman Garg
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Bullshark

BullShark is a protocol that achieves Byzantine Atomic Broadcast (BAB) in a distributed system using a DAG. It lies in the DAG-Rider paradigm, optimized for the common synchronous case, and entails several main enhancements to ensure practical deployability. The core idea is to use the DAG to order transactions in a distributed Byzantine setting, and it gives a sound solution toward distributed consensus for deploying blockchain technologies. BullShark runs on a peer-to-peer message-passing model, where each message is a vertex in the DAG. The key primitive assumes a computationally bounded adversary who is allowed to corrupt at most a third of the parties. The notion of reliable link between honest parties means that all messages eventually arrive, which is what supports the operation of the protocol both in synchronous and asynchronous periods. The work adopts a GST model to be able to reason about synchronous network conditions. BullShark Core: DAG Constructions The protocol has a DAG construction at its core. Each party posts transaction proposals through messages into a DAG. In the DAG, vertices represent messages, and edges represent causal relationships. The parties make a new vertex through combining blocks of transactions and with references to messages which it has previously received. These references are either strong, hence link to vertices in the previous round, or weak, hence link to vertices in rounds which are earlier to ensure their eventual inclusion in the total order. BullShark relies on reliable broadcast mechanisms to give firm guarantees of message integrity, agreement, and validity among parties with the fact that all honest parties will eventually receive the same messages and have a consistent view of the DAG. The protocol further makes use of a global perfect coin for leader election and is charged with leaders who possess fairness and unpredictability in terms of leadership selections for message proposals. Advancing rounds in BullShark The protocol is built itself around certain conditions that drive the process of advancement. By feeding a round with enough vertices, specifically 2 f + 1, parties ensure advancement into the next. Advancing is guaranteed even when messages in the middle of the process of reaching another party are delayed. During synchronous periods, BullShark introduces timeouts to bound the round advancement protocol, and this dual approach gives the best of both worlds: very low latency and high throughput yet with liveness guarantee under worst-case asynchronous conditions

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