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In this approach, we utilize a stack to achieve depth-first traversal of the multilevel doubly linked list. We push nodes into the stack starting from the head, along with managing the child nodes as higher priority over next nodes. This ensures that we process all child nodes before moving on to the next nodes.
Time Complexity: O(n) where n is the number of nodes. Each node is visited once.
Space Complexity: O(n) for the stack in the worst case scenario.
1using System.Collections.Generic;
2
3public class Solution {
4 public Node Flatten(Node head) {
5 if (head == null) return head;
6
7 Stack<Node> stack = new Stack<Node>();
8 Node curr = head;
9
10 while (curr != null) {
11 if (curr.child != null) {
12 if (curr.next != null) stack.Push(curr.next);
13 curr.next = curr.child;
14 curr.child.prev = curr;
15 curr.child = null;
16 }
17
18 if (curr.next == null && stack.Count > 0) {
19 curr.next = stack.Pop();
20 if (curr.next != null) curr.next.prev = curr;
21 }
22
23 curr = curr.next;
24 }
25
26 return head;
27 }
28}The C# version sticks to the iteration pattern via a stack and maintains the list flattening quite effectively using Language Integrated Query (LINQ) for stack operations.
This approach utilizes recursion to handle the traversing and flattening of lists. By inherently using the function call stack, it efficiently manages shifts between the parent and child lists, automatically flattening the entire structure as it recursively resolves each node and its children.
Time Complexity: O(n) due to the necessity to visit each node once.
Space Complexity: O(d) where d is the maximum depth of the children, necessitating stack space for recursion.
The Java solution uses a recursive helper function range `flattenDFS` that inlines child lists by redirecting next pointers and nullifying child pointers, managing node positions effectively.