The problem Swap-Trade solves

Traditional on-chain order matching faces significant challenges due to state bloating and the sequential nature of smart contract execution. This not only slows down the process but also leads to inefficiencies and increased costs. The growing state of the blockchain and the inherent limitations of sequential smart contract operations exacerbate these issues.

Solution:

Eigen AVS addresses these problems by keeping orders off-chain while utilizing a unique matching engine. This engine allows for parallel order matching, significantly improving efficiency and speed. The off-chain matching engine enables tasks that would traditionally bloat the blockchain to be executed more efficiently, while on-chain validation ensures transparency and security. In the event of any malicious activity, ETH is slashed as a penalty, maintaining the integrity of the system. This hybrid approach combines the best of both worlds: off-chain efficiency with on-chain security and accountability.

Challenges we ran into

During the development of our decentralized on-chain order matching DEX, we encountered several hurdles:

Creating Custom Transactions:

Problem: We faced difficulties in creating custom transactions due to the complexity of the process.
Solution: To overcome this, we extensively utilized available documentation, participated in Telegram and Discord groups, and sought advice from developers who were already building on BASE. Their insights and support were invaluable in helping us resolve the issues and successfully implement custom transactions.
Running the Eigen AVS System:

Problem: Implementing the Eigen AVS system presented challenges related to ensuring parallel processing of order matching without compromising on-chain validation integrity. We encountered issues with synchronization and data consistency.
Solution: We addressed these challenges by optimizing our code for better parallel processing and implementing robust error-handling mechanisms. We also conducted thorough testing to ensure synchronization and data consistency. Collaboration with experts in the field and iterative refinements helped us fine-tune the system, ensuring efficient and reliable operation