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

Find the kth Ancestor of a Node in a Binary Tree - Algorithm & Code Examples

Binary Trees

Contents

ProblemExamplesSolutionAlgorithmCode

Problem Statement❯

Given a binary tree, a target node value, and an integer k, your task is to find the kth ancestor of the target node. If the node doesn't exist or there are fewer than k ancestors, return null or indicate the absence of such an ancestor.

The tree is not guaranteed to be a Binary Search Tree. The nodes contain unique integer values.

Examples❯

Input Tree Node k k-th Ancestor Description
[1, 2, 3, 4, 5, 6, 7]
7 2 1 7 → parent 3 → parent 1 → 2nd ancestor = 1
[1, 2, 3, null, 4, null, 5]
4 1 2 4 → parent 2 → 1st ancestor = 2
[10, 20, 30, 40, 50, 60, 70]
70 3 10 70 → 30 → 10 → 3rd ancestor = 10
[1, 2, 3, 4, null, null, 5]
5 1 3 5 → parent 3 → 1st ancestor = 3
[1, 2, 3]
3 2 1 3 → 1st ancestor = 1 → 2nd ancestor = root (no further ancestor) = 1
[1, 2, 3, 4, 5, 6, 7]
4 3 -1 4 → 2 → 1 → no ancestor at distance 3 → return -1

Solution❯

Understanding the Problem

We are given a binary tree and a target node. The goal is to find the kth ancestor of this node. An ancestor of a node is any node in the path from the node to the root (excluding the node itself). The 1st ancestor is the parent, the 2nd is the grandparent, and so on.

For example, in the following binary tree: 

    1
   /   2   3
 / 4   5

If the target node is 5 and k = 2, we trace upward: 5 → 2 → 1. So the 2nd ancestor is 1.

Step-by-Step Solution with Example

Step 1: Build a parent map

We first traverse the tree and store each node’s parent in a map. This helps us move upwards from any node without recursion.

Step 2: Start from the target node

Using the parent map, we begin at the target node and move to its parent. We repeat this process k times.

Step 3: Count each jump

Each move upward reduces k by 1. If at any point the parent is null, it means we’ve reached the root or an ancestor doesn’t exist.

Step 4: Return the current node

If after k jumps we’re at a valid node, that’s our answer. Otherwise, return null.

Example Walkthrough

Tree:

    1
   /   2   3
 / 4   5

Target node = 5, k = 2:

  • Start at 5 → parent is 2 → k becomes 1
  • Move to 2 → parent is 1 → k becomes 0

Since k = 0 and we’re at node 1, the answer is 1.

Edge Cases

Case 1: Target node has fewer than k ancestors

Tree: 

    1
   /   2   3
     /
    4
Target node = 4, k = 3
Path: 4 → 3 → 1 → null → k = 0?
Since we ran out of ancestors before reaching k steps, the output is null.

Case 2: Target node is the root

Tree: 

    1
Target node = 1, k ≥ 1
The root has no parent, so any kth ancestor is null.

Case 3: Deep ancestor in a skewed tree

Tree: 

    1
   /
  2
 /
3
Target node = 3, k = 2
Path: 3 → 2 → 1 → Done → Answer is 1.

Case 4: Empty tree

If the tree is empty (i.e., root is null), we cannot find any ancestor. Output is always null.

Finally

This problem teaches us how to think in terms of upward traversal in a tree using parent mapping. It’s essential to handle edge cases like reaching the root too early or when the tree is empty.

A good solution avoids recursion for upward traversal and uses simple loops with a parent map, making it efficient and easy to follow.

Algorithm Steps❯

  1. Given a binary tree, a target node value, and an integer k.
  2. Traverse the tree recursively to find the target node.
  3. While backtracking, decrement k each time an ancestor is visited.
  4. When k reaches 0, the current node is the kth ancestor.
  5. If the target is not found or there is no kth ancestor, return an indication (e.g. null).

Code

C
C++
Python
Java
JS
Go
Rust
Kotlin
Swift
TS
#include <stdio.h>
#include <stdlib.h>
#include <stdbool.h>

typedef struct TreeNode {
    int val;
    struct TreeNode *left;
    struct TreeNode *right;
} TreeNode;

TreeNode* kthAncestor = NULL;

bool findHelper(TreeNode* root, int target, int* k) {
    if (root == NULL) return false;
    if (root->val == target) return true;
    if (findHelper(root->left, target, k) || findHelper(root->right, target, k)) {
        (*k)--;
        if (*k == 0) {
            kthAncestor = root;
        }
        return true;
    }
    return false;
}

TreeNode* findKthAncestor(TreeNode* root, int target, int k) {
    kthAncestor = NULL;
    findHelper(root, target, &k);
    return kthAncestor;
}

TreeNode* newNode(int val) {
    TreeNode* node = (TreeNode*)malloc(sizeof(TreeNode));
    node->val = val;
    node->left = node->right = NULL;
    return node;
}

int main() {
    TreeNode* root = newNode(1);
    root->left = newNode(2);
    root->right = newNode(3);
    root->left->left = newNode(4);
    root->left->right = newNode(5);

    TreeNode* ancestor = findKthAncestor(root, 5, 2);
    if (ancestor)
        printf("The kth ancestor is: %d\n", ancestor->val);
    else
        printf("No kth ancestor found.\n");
    return 0;
}

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