Savings in the last iteration. Possibly one path to a goal explored only - essentially eliminating the last iteration. Some parts of the tree with no solution because of deadlock are removed. Tunnel Macros Tunnel Macros essentially treat long tunnels as one square. Tunnels consisting of articulation points can be handled more aggressively.
Tree depth is cut.
Goal macros push stones directly to the correct goal square. This method can potentially cut solutions. The tree depth is further reduced. The branching factor of the search tree is reduced. These subsets of stones are stored as patterns and reused throughout the rest of the search to improve the lower bound.