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This approach utilizes recursion to traverse the N-ary tree in a postorder fashion. For each node, we recursively visit all its children first before processing the node itself.
Time Complexity: O(n), where n is the number of nodes, as each node is visited once.
Space Complexity: O(n) for the recursion stack in the worst case (maximum tree height).
1function Node(val, children) {
2 this.val = val;
3 this.children = children || [];
4}
5
6var postorder = function(root) {
7 const result = [];
8 function traverse(node) {
9 if (node === null) return;
10 for (let child of node.children) {
11 traverse(child);
12 }
13 result.push(node.val);
14 }
15 traverse(root);
16 return result;
17};
18
JavaScript follows a similar recursive approach. The function traverse
handles node traversal and updates the result array with node values after processing all child nodes. The main function postorder
executes the traversal, starting from root, and returns the final result.
This approach uses an iterative method to perform postorder traversal with the help of a stack to simulate recursion. Nodes are pushed onto the stack in such a way that their children are processed before the node itself.
Time Complexity: O(n)
Space Complexity: O(n)
1class
Python's iterative solution relies on a stack. Nodes are processed using a stack then prepended to the result list for postorder. A final reversal of result
after processing gives the correct postorder traversal.