Simulate a sandwich with a specified attacker size `a`. Returns the full outcome, including a `reverted` flag when the victim's slippage check would f

Swap `dx` units of X into the pool, receiving Y out. Returns the Y amount out.

Maximize attacker profit over `a` via golden-section search on the feasible interval. Returns the best outcome seen.

Pure preview of `swap_x_for_y` without mutating the pool.

Mid-price of Y in units of X: `x / y`.

Swap `dy` units of Y into the pool, receiving X out.

Small defense comparison table used for live presentation. The private route row is modeled as no public pre-trade visibility, so no attack is attempt

Sweep fixed attacker sizes around the reference scenario. This is meant for classroom visualization: it shows where profit peaks and where the victim

Sweep base fee to show where gross MEV remains positive but rational net profit disappears after fixed bundle gas cost.

Sweep pool depth, keeping price at 1 X = 1 Y and all other params fixed.

Sweep slippage tolerance from `s_min` to `s_max` linearly.

Find the largest attacker size `a` such that the victim's slippage check still passes. This is a monotonic bisection: larger `a` always hurts the vict

Sweep fee over a list of values.

Sweep victim trade size from `v_min` to `v_max` with `n` log-spaced points.