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This approach uses post-order traversal to traverse each subtree and decide if it should be pruned. Starting from the leaf nodes, it recursively checks if a subtree contains a 1. If a subtree doesn't contain any 1s, it returns null. This way, when the recursion unwinds, only relevant subtrees are kept.
Time Complexity: O(N), where N is the number of nodes, since each node is visited once.
Space Complexity: O(H), where H is the height of the tree, due to the recursive stack space.
1function TreeNode(val, left, right) {
2 this.val = (val===undefined ? 0 : val)
3 this.left = (left===undefined ? null : left)
4 this.right = (right===undefined ? null : right)
5}
6
7var pruneTree = function(root) {
8 if (!root) return null;
9 root.left = pruneTree(root.left);
10 root.right = pruneTree(root.right);
11 if (root.val === 0 && !root.left && !root.right) return null;
12 return root;
13};This JavaScript implementation handles a binary tree pruning through post-order recursion. Each subtree gets evaluated recursively; if no 1 exists in a subtree, or if part of the subtree contains just nodes with a value of 0, such nodes get pruned by setting their references to null. This tidy approach ensures efficient maintenance of necessary nodes.
By utilizing an iterative traversal using a stack, the tree can be pruned without recursion. This approach mimics the recursion stack by using an explicit stack to manage nodes that need to be processed. Once the subtree rooted at a node is evaluated, decisions are made to prune or retain nodes based on whether a 1 is found.
Time Complexity: O(N), as we are ensuring every node is visited.
Space Complexity: O(H), attributed to the height of the tree in terms of stack use.
This JavaScript solution uses an iterative method involving a stack to simulate post-order traversal. By deeply inspecting children before retracting visited nodes, the solution determines the pruning status, enabling iterative execution without inherent recursive constraints.