Find largest subtree having identical left and right subtrees - GeeksforGeeks
Given a binary tree, find the largest subtree having identical left and right subtree. Expected complexity is O(n).
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Given a binary tree, find the largest subtree having identical left and right subtree. Expected complexity is O(n).
We can save recursive calls. The idea is to do a postorder traversal of given binary tree and for each node, we store structure of its left and right subtrees. In order to store the structure of left and right subtree, we use a string. We separate left and right subtree nodes from current node in the string by using a delimiter. For every encountered node, we update largest subtree found so far if its left and right subtree structure are similar.
/ Sets maxSize to size of largest subtree with// identical left and right. maxSize is set with// size of the maximum sized subtree. It returns// size of subtree rooted with current node. This// size is used to keep track of maximum size.int largestSubtreeUtil(Node* root, string& str, int& maxSize, Node*& maxNode){ if (root == NULL) return 0; // string to store structure of left and // right subtrees string left = "", right = ""; // traverse left subtree and finds its size int ls = largestSubtreeUtil(root->left, left, maxSize, maxNode); // traverse right subtree and finds its size int rs = largestSubtreeUtil(root->right, right, maxSize, maxNode); // if left and right subtrees are similar // update maximum subtree if needed (Note that // left subtree may have a bigger value than // right and vice versa) int size = ls + rs + 1; if (left.compare(right) == 0) { if (size > maxSize) { maxSize = size; maxNode = root; } } // append left subtree data str.append("|").append(left).append("|"); // append current node data str.append("|").append(to_string(root->data)).append("|"); // append right subtree data str.append("|").append(right).append("|"); return size;}// function to find the largest subtree// having identical left and right subtreeint largestSubtree(Node* node, Node*& maxNode){ int maxSize = 0; string str = ""; largestSubtreeUtil(node, str, maxSize, maxNode); return maxSize;}
The worst case time complexity still remains O(n2) as we need O(n) time to compare two strings.
Further Optimization:
We can optimized the space used in above program by using Succinct Encoding of Binary Tree.
We can optimized the space used in above program by using Succinct Encoding of Binary Tree.
A simple solution is to consider every node, recursively check if left and right subtrees are identical using the approach discussed here. Keep track of maximum size such node.
Two trees are identical when they have same data and arrangement of data is also same.
To identify if two trees are identical, we need to traverse both trees simultaneously, and while traversing we need to compare data and children of the trees.
static Node root1, root2; /* Given two trees, return true if they are structurally identical */ boolean identicalTrees(Node a, Node b) { /*1. both empty */ if (a == null && b == null) { return true; } /* 2. both non-empty -> compare them */ if (a != null && b != null) { return (a.data == b.data && identicalTrees(a.left, b.left) && identicalTrees(a.right, b.right)); } /* 3. one empty, one not -> false */ return false; }