How Do You Optimize Backtesting Parameters to Account for Real-World Spread Spikes?

Standard backtests on raw price charts often calculate hypothetical profits without factoring in variable spreads and execution slippage. What buffer rules or spread adjustments do you program into your automated backtesting models to ensure realistic historical metrics?