Binary TreesBinary Trees36
  1. 1Preorder Traversal of a Binary Tree using Recursion
  2. 2Preorder Traversal of a Binary Tree using Iteration
  3. 3Inorder Traversal of a Binary Tree using Recursion
  4. 4Inorder Traversal of a Binary Tree using Iteration
  5. 5Postorder Traversal of a Binary Tree Using Recursion
  6. 6Postorder Traversal of a Binary Tree using Iteration
  7. 7Level Order Traversal of a Binary Tree using Recursion
  8. 8Level Order Traversal of a Binary Tree using Iteration
  9. 9Reverse Level Order Traversal of a Binary Tree using Iteration
  10. 10Reverse Level Order Traversal of a Binary Tree using Recursion
  11. 11Find Height of a Binary Tree
  12. 12Find Diameter of a Binary Tree
  13. 13Find Mirror of a Binary Tree
  14. 14Left View of a Binary Tree
  15. 15Right View of a Binary Tree
  16. 16Top View of a Binary Tree
  17. 17Bottom View of a Binary Tree
  18. 18Zigzag Traversal of a Binary Tree
  19. 19Check if a Binary Tree is Balanced
  20. 20Diagonal Traversal of a Binary Tree
  21. 21Boundary Traversal of a Binary Tree
  22. 22Construct a Binary Tree from a String with Bracket Representation
  23. 23Convert a Binary Tree into a Doubly Linked List
  24. 24Convert a Binary Tree into a Sum Tree
  25. 25Find Minimum Swaps Required to Convert a Binary Tree into a BST
  26. 26Check if a Binary Tree is a Sum Tree
  27. 27Check if All Leaf Nodes are at the Same Level in a Binary Tree
  28. 28Lowest Common Ancestor (LCA) in a Binary Tree
  29. 29Solve the Tree Isomorphism Problem
  30. 30Check if a Binary Tree Contains Duplicate Subtrees of Size 2 or More
  31. 31Check if Two Binary Trees are Mirror Images
  32. 32Calculate the Sum of Nodes on the Longest Path from Root to Leaf in a Binary Tree
  33. 33Print All Paths in a Binary Tree with a Given Sum
  34. 34Find the Distance Between Two Nodes in a Binary Tree
  35. 35Find the kth Ancestor of a Node in a Binary Tree
  36. 36Find All Duplicate Subtrees in a Binary Tree
GraphsGraphs46
  1. 1Breadth-First Search in Graphs
  2. 2Depth-First Search in Graphs
  3. 3Number of Provinces in an Undirected Graph
  4. 4Connected Components in a Matrix
  5. 5Rotten Oranges Problem - BFS in Matrix
  6. 6Flood Fill Algorithm - Graph Based
  7. 7Detect Cycle in an Undirected Graph using DFS
  8. 8Detect Cycle in an Undirected Graph using BFS
  9. 9Distance of Nearest Cell Having 1 - Grid BFS
  10. 10Surrounded Regions in Matrix using Graph Traversal
  11. 11Number of Enclaves in Grid
  12. 12Word Ladder - Shortest Transformation using Graph
  13. 13Word Ladder II - All Shortest Transformation Sequences
  14. 14Number of Distinct Islands using DFS
  15. 15Check if a Graph is Bipartite using DFS
  16. 16Topological Sort Using DFS
  17. 17Topological Sort using Kahn's Algorithm
  18. 18Cycle Detection in Directed Graph using BFS
  19. 19Course Schedule - Task Ordering with Prerequisites
  20. 20Course Schedule 2 - Task Ordering Using Topological Sort
  21. 21Find Eventual Safe States in a Directed Graph
  22. 22Alien Dictionary Character Order
  23. 23Shortest Path in Undirected Graph with Unit Distance
  24. 24Shortest Path in DAG using Topological Sort
  25. 25Dijkstra's Algorithm Using Set - Shortest Path in Graph
  26. 26Dijkstra’s Algorithm Using Priority Queue
  27. 27Shortest Distance in a Binary Maze using BFS
  28. 28Path With Minimum Effort in Grid using Graphs
  29. 29Cheapest Flights Within K Stops - Graph Problem
  30. 30Number of Ways to Reach Destination in Shortest Time - Graph Problem
  31. 31Minimum Multiplications to Reach End - Graph BFS
  32. 32Bellman-Ford Algorithm for Shortest Paths
  33. 33Floyd Warshall Algorithm for All-Pairs Shortest Path
  34. 34Find the City With the Fewest Reachable Neighbours
  35. 35Minimum Spanning Tree in Graphs
  36. 36Prim's Algorithm for Minimum Spanning Tree
  37. 37Disjoint Set (Union-Find) with Union by Rank and Path Compression
  38. 38Kruskal's Algorithm - Minimum Spanning Tree
  39. 39Minimum Operations to Make Network Connected
  40. 40Most Stones Removed with Same Row or Column
  41. 41Accounts Merge Problem using Disjoint Set Union
  42. 42Number of Islands II - Online Queries using DSU
  43. 43Making a Large Island Using DSU
  44. 44Bridges in Graph using Tarjan's Algorithm
  45. 45Articulation Points in Graphs
  46. 46Strongly Connected Components using Kosaraju's Algorithm

Right View of a Binary Tree - Iterative Approach

Problem Statement

Given a binary tree, return the right view of the tree using an iterative level-order traversal approach. The right view of a binary tree includes the last node at each level when the tree is viewed from the right side.

Examples

Input Tree Right View Output Description
[1, 2, 3, 4, 5, null, 6]
[1, 3, 6] Standard case: Nodes visible from the right at each level
[1]
[1] Single-node tree: root is the only visible node
[] [] Empty tree: no nodes to view from any side
[1, 2, null, 3, null, null, null, 4]
[1, 2, 3, 4] Left-skewed tree: right view includes one node per level
[1, null, 2, null, null, null, 3]
[1, 2, 3] Right-skewed tree: all nodes are visible in the right view
[10, 20, 30, null, 25, null, 35]
[10, 30, 35] Balanced tree with both left and right children

Visualization Player

Solution

Case 1: Tree is empty

If the binary tree has no nodes, the right view is simply an empty list. There are no levels to process, so nothing can be seen from the right side.

Case 2: Tree has only one node

In this scenario, there is just the root node and no children. Hence, the right view consists of that single root node, since it's both the top and the rightmost node.

Case 3: Tree has multiple levels with both left and right children

To find the right view, we use a level-order traversal, where we visit each level from left to right. At each level, we track the last node — this is the node visible from the right side. For example, in the tree [1, 2, 3, null, 5, null, 4], we process level by level and pick the last node at each level: 1 from level 1, 3 from level 2, and 4 from level 3.

Case 4: Tree is right skewed

If the tree has only right children at each level, then all the nodes form the right view because each node is the only one in its level and also the rightmost. For example, [1, null, 2, null, 3] yields [1, 2, 3] as the right view.

Case 5: Tree is left skewed

When the tree contains only left children at each level, even then, the last (and only) node of each level becomes part of the right view. For instance, [1, 2, null, 3] will result in [1, 2, 3] as each level still has one node, and it's considered the rightmost by default.

Algorithm Steps

  1. Given a binary tree, if the tree is empty, return an empty result.
  2. Initialize a queue and enqueue the root node.
  3. While the queue is not empty, determine the number of nodes at the current level (levelSize).
  4. For each node in the current level, dequeue a node.
  5. If the node is the last one in the level (i.e. for index i == levelSize - 1), record its value as part of the right view.
  6. Enqueue the left and then right child of the node (if they exist) for processing in the next level.
  7. Repeat until all levels are processed; the recorded values form the right view of the binary tree.

Code

Python
Java
JavaScript
C
C++
C#
Kotlin
Swift
Go
Php
class TreeNode:
    def __init__(self, val=0, left=None, right=None):
        self.val = val
        self.left = left
        self.right = right

def rightView(root):
    if not root:
        return []
    result = []
    queue = [root]
    while queue:
        levelSize = len(queue)
        for i in range(levelSize):
            node = queue.pop(0)
            if i == levelSize - 1:
                result.append(node.val)
            if node.left:
                queue.append(node.left)
            if node.right:
                queue.append(node.right)
    return result

if __name__ == '__main__':
    # Construct binary tree:
    #         1
    #        / \
    #       2   3
    #        \    \
    #         5    4
    root = TreeNode(1, TreeNode(2, None, TreeNode(5)), TreeNode(3, None, TreeNode(4)))
    print(rightView(root))