Model Reduction
Model reduction is a process used to reduce the size and complexity of a mathematical model while maintaining its key behaviors and outputs. In the context of protocol verification, it involves removing redundant variables or simplifying logic that does not affect the safety or liveness properties being tested.
By reducing the model, developers can perform more efficient model checking and uncover errors that would otherwise be hidden by the complexity of the full system. This is particularly useful for analyzing the interaction between different DeFi protocols, where the full state space is prohibitively large.
Effective model reduction allows for deeper analysis of protocol dynamics, such as the impact of interest rate changes or liquidation cascades. It is a fundamental technique for ensuring the scalability of formal verification efforts.