# Orderbook Deep Dive

## Overview

In traditional orderbook systems, achieving a full on-chain implementation is considered challenging due to the significant amount of data reference and updates, which can lead to high [gas costs](https://github.com/Secured-Finance/secured-finance-docs/blob/main/resources/knowledge-base/gas-cost.md). However, **Secured Finance has successfully implemented an on-chain orderbook system.**

Particularly, gas-intensive processes such as creating open orders, executing market orders, and auto-rolling result in increasing gas costs proportional to the data volume, according to Solidity's characteristics. In some cases, these processes may even approach Ethereum's block gas limit, potentially causing execution issues.

### The key points of Gas cost for On-chain orderbook:

* Creating open orders incurs increasing [gas costs](https://github.com/Secured-Finance/secured-finance-docs/blob/main/resources/knowledge-base/gas-cost.md) as the data volume on the orderbook grows.
* Executing [market orders](https://github.com/Secured-Finance/secured-finance-docs/blob/main/fixed-rate-lending/getting-started/platform-guide/trading/order-type.md) results in escalating gas costs proportional to the number of matched open orders, potentially leading to execution challenges in certain cases.
* [Auto-rolling](https://docs.secured.finance/fixed-rate-lending/advanced-topics/market-dynamics/auto-rolling) faces mounting gas costs proportional to the number of positions subject to auto-rolling, potentially leading to execution challenges in certain scenarios.

These challenges prompted Secured Finance to address them effectively and enable a practical gas cost for the full on-chain orderbook system. To achieve this, we introduced red-black trees, lazy evaluation, and the concept of Genesis Value. These solutions ensure the smooth operation of the on-chain orderbook system, optimizing gas costs and enhancing the overall efficiency and performance of the platform.

## What You'll Learn

* How the Red-Black Tree data structure enables efficient orderbook operations
* How Lazy Evaluation reduces gas costs for on-chain operations
* How Compound Factors and Genesis Values are used for price calculations
* How Orderbook Rotation works during market transitions

## Key Components

* [**Red-Black Tree**](https://docs.secured.finance/fixed-rate-lending/advanced-topics/orderbook-deep-dive/red-black-tree): The self-balancing binary search tree that powers the orderbook
* [**Lazy Evaluation**](https://docs.secured.finance/fixed-rate-lending/advanced-topics/orderbook-deep-dive/lazy-evaluation): The technique that minimizes gas costs for orderbook operations
* [**Compound Factor**](https://docs.secured.finance/fixed-rate-lending/advanced-topics/orderbook-deep-dive/compound-factor): The mechanism for calculating time-value adjustments
* [**Genesis Value**](https://docs.secured.finance/fixed-rate-lending/advanced-topics/orderbook-deep-dive/genesis-value): The initial value representation for assets and obligations
* [**Orderbook Rotation**](https://docs.secured.finance/fixed-rate-lending/advanced-topics/orderbook-deep-dive/orderbook-rotation): The process for transitioning between market periods

## Related Resources

* [Market Dynamics](https://docs.secured.finance/fixed-rate-lending/advanced-topics/market-dynamics)
* [Core Mechanics](https://docs.secured.finance/fixed-rate-lending/core-mechanics/order-book-system)
* [Safety Measures](https://docs.secured.finance/fixed-rate-lending/advanced-topics/safety-measures)