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 a Binary Tree is a Sum Tree - Algorithm and Code Examples

Problem Statement

Given a binary tree, check whether it is a **Sum Tree**. A Sum Tree is a binary tree in which the value of each non-leaf node is equal to the sum of the values present in its left and right subtrees. Leaf nodes are considered Sum Trees by default. You need to return whether the entire tree satisfies the Sum Tree property.

Examples

Input Tree Is Sum Tree? Description
[26, 10, 3, 4, 6, null, 3]
true Every node equals the sum of its left and right children: 26 = 10 + 3, 10 = 4 + 6, etc.
[10, 8, 2, 3, 5]
false The root node 10 ≠ 8 + 2. Violates the sum tree property.
[0]
true Single node is trivially a sum tree by definition.
[] true An empty tree is considered a valid sum tree (base case).
[20, 8, 12, 3, 5, 6, 6]
false Some internal nodes do not match the sum of their children: e.g., 12 ≠ 6 + 6.
[44, 9, 13, 4, 5, 6, 7]
true All internal nodes follow the rule: 9 = 4 + 5, 13 = 6 + 7, 44 = 9 + 13 + (leaf nodes sum).
[18, 8, 10, 3, 5, 6, 4]
false Although child nodes satisfy sum tree rule, root 18 ≠ 8 + 10, so the whole tree fails.

Solution

Case 1: The Tree is Empty

An empty tree (null or None) is trivially considered a Sum Tree because there's nothing to violate the sum condition. So, in this case, the answer is true.

Case 2: The Tree Has a Single Node

If the tree has only one node, it's a leaf. Leaf nodes are always considered Sum Trees by definition, as there are no child nodes to sum. Hence, the answer is true.

Case 3: The Tree Has Internal Nodes and Satisfies the Sum Property

For a non-leaf node, if its value is equal to the sum of values in its left and right subtrees, and both subtrees themselves are Sum Trees, then the entire subtree rooted at this node is a Sum Tree. For example, in the tree:

    26
   /  \
 10    3
/  \     \
4    6     3
Each non-leaf node follows the rule:
  • 4 and 6 are leaves → valid
  • 10 = 4 + 6 → valid
  • 3 is a leaf → valid
  • 26 = 10 + 3 + 3 → valid
So, the output is true.

Case 4: The Tree Has Internal Nodes but Violates the Sum Rule

If any node (other than a leaf) violates the condition — meaning its value doesn't equal the sum of its left and right subtrees — then the tree is not a Sum Tree. For example:

    18
   /  \
  9    8
The root node 18 ≠ 9 + 8 (which is 17), so it fails the check. Therefore, the answer is false.

Case 5: The Tree Contains Mixed Nodes with One Invalid Subtree

Even if most of the tree follows the Sum Tree rule, a single violation anywhere in the tree (in a subtree) makes the entire tree invalid. So, we must recursively validate every node.

Algorithm Steps

  1. If the tree is empty, return true with sum = 0.
  2. If the node is a leaf, return true with sum equal to the node's value.
  3. Recursively check the left and right subtrees to obtain their sums and whether they are sum trees.
  4. For the current node, verify that it is a sum tree by checking if its value equals the sum of the left and right subtree sums.
  5. Return true for the current node if both subtrees are sum trees and the node's value equals the left sum plus the right sum; also, return the total sum (node's value + left sum + right sum).
  6. If the condition fails, return false.

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 isSumTree(root):
    # Returns a tuple (isSumTree, sum)
    if root is None:
        return (True, 0)
    if root.left is None and root.right is None:
        return (True, root.val)
    leftIsSum, leftSum = isSumTree(root.left)
    rightIsSum, rightSum = isSumTree(root.right)
    total = leftSum + rightSum
    if leftIsSum and rightIsSum and root.val == total:
        return (True, root.val + total)
    else:
        return (False, 0)

# Example usage:
if __name__ == '__main__':
    # Construct binary tree:
    #         26
    #        /  \
    #      10    3
    #     /  \    \
    #    4    6    3
    root = TreeNode(26, TreeNode(10, TreeNode(4), TreeNode(6)), TreeNode(3, None, TreeNode(3)))
    print(isSumTree(root)[0])