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

Check if Two Binary Trees are Mirror Images - Algorithm, Visualization, Examples

Problem Statement

Given two binary trees, your task is to determine whether they are mirror images of each other. Two trees are said to be mirrors if the structure of one tree is the reverse of the other and their corresponding node values are the same. This check must be done recursively for all corresponding nodes.

Examples

Tree 1 Tree 2 Are Mirror? Description
[1, 2, 3, 4, 5]
[1, 3, 2, null, null, 5, 4]
true Tree 2 is the mirror image of Tree 1: left and right children are swapped at every node.
[10, 20, 30]
[10, 30, 20]
true Left and right subtrees are perfectly mirrored.
[1, 2, 3]
[1, 2, 3]
false Both trees have the same structure, but are not mirrors (no left-right reversal).
[] [] true Two empty trees are trivially mirrors of each other.
[1]
[1]
true Single-node trees with the same value are mirrors.
[1, 2]
[1, null, 2]
true Tree 1 has a left child; Tree 2 has a right child. Structures mirror each other.

Solution

Case 1: Both Trees Are Empty

If both trees are completely empty (null), they are considered mirror images by definition. This is the simplest and most direct case. There's nothing to compare, and yet they reflect each other perfectly in absence.

Case 2: One Tree is Empty, the Other is Not

In this case, the trees cannot be mirrors. A mirror image implies that both trees must at least have the same number of levels and nodes (albeit in mirrored structure). If one is null and the other is not, the symmetry breaks immediately.

Case 3: Root Nodes Have Different Values

If the values at the root nodes of the two trees are different, they cannot be mirrors. The concept of a mirror requires that not only the structure but the data in corresponding mirrored positions must match.

Case 4: Root Values Match — Compare Subtrees

If the root values are the same, we recursively compare the left subtree of the first tree with the right subtree of the second tree, and the right subtree of the first with the left subtree of the second. Both comparisons must succeed for the trees to be considered mirrors.

Case 5: Trees Have Partial Mirror Structure

Sometimes, the trees may start as mirrors but differ deeper down in structure or values. For instance, if the root and immediate children match in a mirrored way but the grandchildren do not reflect each other, then the trees are not mirrors. Every level of the tree must satisfy the mirror property.

Case 6: Single Node Trees

Two single-node trees with the same value are mirrors of each other, since there's no child to compare. But if one has children and the other doesn't, they are not mirrors. Even having a child on different sides breaks the mirror property.

Algorithm Steps

  1. Given two binary trees, if both trees are empty, they are mirrors; if one is empty and the other is not, they are not mirrors.
  2. Compare the root nodes of both trees. If the values are not equal, the trees are not mirrors.
  3. Recursively check if the left subtree of the first tree is a mirror of the right subtree of the second tree, and if the right subtree of the first tree is a mirror of the left subtree of the second tree.
  4. If both recursive checks return true, then the two trees are mirror images of each other.

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 isMirror(t1, t2):
    if not t1 and not t2:
        return True
    if not t1 or not t2:
        return False
    return (t1.val == t2.val) and isMirror(t1.left, t2.right) and isMirror(t1.right, t2.left)

# Example usage:
if __name__ == '__main__':
    # Tree 1:
    #      1
    #     / \
    #    2   3
    #
    # Tree 2 (mirror of Tree 1):
    #      1
    #     / \
    #    3   2
    tree1 = TreeNode(1, TreeNode(2), TreeNode(3))
    tree2 = TreeNode(1, TreeNode(3), TreeNode(2))
    print(isMirror(tree1, tree2))