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

Reverse Level Order Traversal of a Binary Tree using Recursion

Problem Statement

Given a binary tree, return the reverse level order traversal of its nodes’ values. In reverse level order traversal, we start from the bottom-most level and go up level by level, and within each level, nodes are visited from left to right. The traversal should be done using recursion only.

Examples

Input Tree Reverse Level Order Output Description
[1, 2, 3, 4, 5, null, 6]
[[4, 5, 6], [2, 3], [1]] Standard tree with three levels and both left-right children
[1]
[[1]] Edge case: Tree with a single node (root only)
[] [] Edge case: Empty tree (no nodes at all)
[1, 2, null, 3, null, null, null, 4]
[[4], [3], [2], [1]] Left-skewed tree with increasing depth
[1, null, 2, null, null, null, 3]
[[3], [2], [1]] Right-skewed tree with increasing depth
[7, 4, 9, 2, 5, 8, 10]
[[2, 5, 8, 10], [4, 9], [7]] Complete binary tree with balanced left and right subtrees

Visualization Player

Solution

Case 1: Normal Tree with Multiple Levels

In this case, we have a binary tree with multiple levels. To solve this, we recursively gather nodes level by level starting from the root and store each level in a separate list. Once we finish all levels, we reverse the list of levels. This way, the bottom-most level comes first, followed by the level above it, and so on, until we reach the root level. Finally, we flatten this list to get a single array representing the reverse level order traversal.

Case 2: Tree with Single Node

If the binary tree has only one node (i.e., just the root), then there is only one level. In reverse level order, this is still the only node present. The output will be a list containing just that root value.

Case 3: Empty Tree

In this case, the binary tree is null or empty. Since there are no nodes to traverse, the output should be an empty list. It’s important to handle this case explicitly in code to avoid errors such as null reference exceptions.

Summary

Reverse level order traversal is the process of visiting nodes from bottom to top and left to right within each level. Using recursion, we collect values for each level, then reverse the collection of levels, and finally flatten the result. This approach ensures that we maintain both vertical (levels) and horizontal (left-to-right) orderings as per the traversal’s definition.

Algorithm Steps

  1. Traverse the binary tree recursively level by level starting from the root.
  2. For each level, record the nodes’ values in an auxiliary structure (e.g., an array or list).
  3. After the traversal, reverse the order of the recorded levels.
  4. Concatenate the values from the reversed levels to obtain the reverse level order traversal.

Code

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

def reverseLevelOrder(root):
    levels = []
    def helper(node, level):
        if not node:
            return
        if len(levels) == level:
            levels.append([])
        levels[level].append(node.val)
        helper(node.left, level + 1)
        helper(node.right, level + 1)
    helper(root, 0)
    result = []
    for level in reversed(levels):
        result.extend(level)
    return result

# Example usage:
if __name__ == '__main__':
    # Construct binary tree:
    #         1
    #       /   \
    #      2     3
    #     / \   / \
    #    4   5 6   7
    root = TreeNode(1, TreeNode(2, TreeNode(4), TreeNode(5)), TreeNode(3, TreeNode(6), TreeNode(7)))
    print(reverseLevelOrder(root))