The tree-to-tree correction problem involves determining the minimum cost sequence of edit operations needed to transform one labeled ordered tree into another. The edit operations include changing a node, deleting a node, or inserting a node. The paper presents an algorithm that computes the distance between two trees in time O(V·V'·L²·L'²), where V and V' are the number of nodes in the trees, and L and L' are their maximum depths. The algorithm is based on the concept of mappings, which describe how edit operations transform one tree into another. The paper also discusses possible applications of the tree-to-tree correction problem, including measuring tree similarity, error recovery in programming languages, and finding the largest common substructure between two trees. The algorithm is shown to be efficient and applicable to various tree-related problems.The tree-to-tree correction problem involves determining the minimum cost sequence of edit operations needed to transform one labeled ordered tree into another. The edit operations include changing a node, deleting a node, or inserting a node. The paper presents an algorithm that computes the distance between two trees in time O(V·V'·L²·L'²), where V and V' are the number of nodes in the trees, and L and L' are their maximum depths. The algorithm is based on the concept of mappings, which describe how edit operations transform one tree into another. The paper also discusses possible applications of the tree-to-tree correction problem, including measuring tree similarity, error recovery in programming languages, and finding the largest common substructure between two trees. The algorithm is shown to be efficient and applicable to various tree-related problems.