šŸ‘Øā€šŸ’»
Coding Interview Patterns
  • Coding Interview Patterns
  • 1. Pattern: Sliding Window
    • 1.0 Introduction
    • 1.1 Maximum Sum Subarray of Size K (easy)
    • 1.2 Smallest Subarray with a given sum (easy)
    • 1.3 Longest Substring with K Distinct Characters (medium)
    • 1.4 Fruits into Baskets (medium)
    • 1.5 No-repeat Substring (hard)
    • 1.6 Longest Substring with Same Letters after Replacement (hard)
    • 1.7 Longest Subarray with Ones after Replacement (hard)
    • 1.8 - Permutation in a String (hard)
    • 1.9 String Anagrams (hard)
    • 1.10 Smallest Window containing Substring (hard)
    • 1.11 Words Concatenation (hard)
  • 2. Pattern: Two Pointers
    • 2.0 Introduction
    • 2.1 Pair with Target Sum (easy)
    • 2.2 Remove Duplicates (easy)
    • 2.3 Squaring a Sorted Array (easy)
    • 2.4 Triplet Sum to Zero (medium)
    • 2.5 Triplet Sum Close to Target (medium)
    • 2.6 Triplets with Smaller Sum (medium)
    • 2.7 Subarrays with Product Less than a Target (medium)
    • 2.8 Dutch National Flag Problem (medium)
    • 2.9 Comparing Strings containing Backspaces (medium)
    • 2.10 Minimum Window Sort (medium)
  • 7. Pattern: Tree Breadth First Search
    • 7.0 Introduction
    • 7.1 Binary Tree Level Order Traversal (easy)
    • 7.2 Reverse Level Order Traversal (easy)
    • 7.3 Zigzag Traversal (medium)
    • 7.4 Level Averages in a Binary Tree (easy)
    • 7.5 Minimum Depth of a Binary Tree (easy)
    • 7.6 Maximum Depth of Binary Tree (easy)
    • 7.7 Level Order Successor (easy)
    • 7.8 Connect Level Order Siblings (medium)
    • 7.9 Problem Challenge 1 - Connect All Level Order Siblings (medium)
    • 7.10 Problem Challenge 2 - Right View of a Binary Tree (easy)
  • 11. Pattern: Modified Binary Search
    • 11.1 Introduction
    • 11.2 Order-agnostic Binary Search (easy)
    • 11.3
  • 16. Pattern: Topological Sort (Graph)
    • 16.1 Introduction
    • 16.2 Topological Sort (medium)
    • 16.3 Tasks Scheduling (medium)
    • 16.4 Tasks Scheduling Order (medium)
  • Contributor Covenant Code of Conduct
  • Page 1
Powered by GitBook
On this page

Was this helpful?

  1. 7. Pattern: Tree Breadth First Search

7.9 Problem Challenge 1 - Connect All Level Order Siblings (medium)

Previous7.8 Connect Level Order Siblings (medium)Next7.10 Problem Challenge 2 - Right View of a Binary Tree (easy)

Last updated 3 years ago

Was this helpful?

Given a binary tree, connect each node with its level order successor. The last node of each level should point to the first node of the next level.

Example 1:

Example 2:

import java.util.*;

class TreeNode {
  int val;
  TreeNode left;
  TreeNode right;
  TreeNode next;

  TreeNode(int x) {
    val = x;
    left = right = next = null;
  }
};

class Main {
  public static void connect(TreeNode root) {
    if(root == null) return;

    Queue<TreeNode> queue = new LinkedList<>();
    queue.offer(root);
    TreeNode prev = null;
    while(!queue.isEmpty()) {
      int levelSize = queue.size();
      for(int i = 0; i < levelSize; i++) {
        TreeNode curr = queue.poll();
        if(prev != null)
          prev.next = curr;
        prev = curr;

        if(curr.left != null) queue.offer(curr.left);
        if(curr.right != null) queue.offer(curr.right);
      }
    }
  }

  public static void main(String[] args) {
    TreeNode root = new TreeNode(12);
    root.left = new TreeNode(7);
    root.right = new TreeNode(1);
    root.left.left = new TreeNode(9);
    root.right.left = new TreeNode(10);
    root.right.right = new TreeNode(5);
    Main.connect(root);

    // level order traversal using 'next' pointer
    TreeNode current = root;
    System.out.println("Traversal using 'next' pointer: ");
    while (current != null) {
      System.out.print(current.val + " ");
      current = current.next;
    }
  }
}

The time complexity of the above algorithm is O(N), where ā€˜N’ is the total number of nodes in the tree. This is due to the fact that we traverse each node once.

The space complexity of the above algorithm will be O(N), which is required for the queue. Since we can have a maximum of N/2 nodes at any level (this could happen only at the lowest level), therefore we will need O(N) space to store them in the queue.

Time complexity

Space complexity

#
#