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EPF Final Update

The cohort 4 of EPF has finally ended and I can say I had the best experience during these months!

Verkle Implementation in Nim

For detailed update check out this blog by fellow contributor Advaita.

Verkle Implementation in Java

Thanks to Dragan for helping with onboarding to the project. Check his final update for detailed update

Future Steps

I am very excited and happy to see Verkle to be pushed more and more with time (inevitable).

I can see lots optimizations, changes, views, additions coming to Verkle in the future as we progress closer to the Verge.

I am also actively looking at the Prague/Electra upgrade updates and also plan to contribute to that.

Nimbus

Next steps are -

  • Integration of constantine with verkle trie impl.
  • Integrating in the nimbus client
  • Join the testnet
  • Optimizations

Besu

Next steps are -

  • Integration in the client (Ongoing with the help of Karim from Besu)
  • Join the testnet
  • Optimizations

Self Evaluation

I started this cohort with minimal knowledge about core blockchain and I am happy with what I am leaving with.

What went well:

  • Kick-started by core journey. I started this cohort with minimal knowledge and I am happy with what I am leaving with.
  • Got the chance to collaborate with awesome people be it fellows, mentors, core devs (ofc hr).
  • Got the chance to make meaningful connections
  • Devconnect was WOW! Nothing beats collaborating in-person.

What didn't go well:

  • Faced knowledge gaps at many places therefore I wasn't able to contribute to full potential
  • Due to many people contributing to this project, there were collisions.
  • Communication problem/gap between fellow contributors.
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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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