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

Convert a Binary Tree into a Doubly Linked List - Algorithm & Code Examples

Problem Statement

Given a binary tree, convert it into a doubly linked list (DLL) in-place. The nodes should be arranged in the same order as an in-order traversal of the binary tree. Each node's left pointer should point to the previous node in the DLL, and the right pointer should point to the next node.

Examples

Input Tree Level Order Output Description
[10, 12, 15, 25, 30, 36]
[[10], [12, 15], [25, 30, 36]] Standard binary tree; in-order traversal yields DLL: 25 ⇄ 12 ⇄ 30 ⇄ 10 ⇄ 36 ⇄ 15
[1]
[[1]] Single-node tree; DLL is just: 1
[] [] Empty tree; DLL does not exist
[4, 3, null, 2, null, 1]
[[4], [3], [2], [1]] Left-skewed tree; DLL follows in-order: 1 ⇄ 2 ⇄ 3 ⇄ 4
[5, null, 6, null, 7, null, 8]
[[5], [6], [7], [8]] Right-skewed tree; DLL is 5 ⇄ 6 ⇄ 7 ⇄ 8

Solution

Understanding the Problem

We are given a binary tree and our task is to convert it into a doubly linked list (DLL). The conversion must follow the in-order traversal sequence of the binary tree — that is, we must visit the left subtree, then the root, and finally the right subtree.

Each node in the tree contains a value, a left pointer, and a right pointer. In the DLL, the left pointer will act as the "previous" pointer, and the right pointer will act as the "next" pointer.

This transformation is done *in-place*, meaning we won't use extra data structures for creating new nodes — we'll just adjust the pointers of existing nodes to form the DLL.

Step-by-Step Solution with Example

Step 1: Understand In-Order Traversal

In in-order traversal, we recursively visit the left subtree, then the current node, and finally the right subtree. This ensures nodes are visited in ascending order for a Binary Search Tree (BST).

Step 2: Use a Previous Pointer

While traversing the tree in-order, we maintain a pointer to the previously visited node. We connect the previous node's right pointer to the current node, and the current node's left pointer to the previous node.

Step 3: Maintain Head of DLL

The first node visited in in-order becomes the head of the resulting DLL. This node has no left pointer (i.e., left = null).

Step 4: Apply It on an Example

Let's say our binary tree is:

        10
       /        5    15

In-order traversal of this tree gives: 5 → 10 → 15

During traversal:

  • Visit 5: it becomes the head of DLL.
  • Visit 10: link 5.right = 10 and 10.left = 5.
  • Visit 15: link 10.right = 15 and 15.left = 10.

The final doubly linked list: 5 <-> 10 <-> 15

Edge Cases

Case 1: Empty Tree

If the input tree is null, there's nothing to convert. The output should also be null.

Case 2: Single Node Tree

For a tree with one node like [10], that node itself becomes the doubly linked list. Both its left and right pointers will remain null.

Result: 10

Case 3: Right Skewed Tree

Each node has only a right child: [10, null, 20, null, 30]

In-order traversal: 10 → 20 → 30

DLL: 10 <-> 20 <-> 30

Case 4: Left Skewed Tree

Each node has only a left child: [30, 20, null, 10, null]

In-order traversal: 10 → 20 → 30

DLL: 10 <-> 20 <-> 30

Case 5: Tree with Mixed Structure

Even in trees with a mix of left and right children, the same logic applies — we traverse in in-order and link accordingly. The DLL will reflect the in-order sequence.

Finally

This problem is a classic example of using in-order traversal with pointer adjustments to transform a tree structure into a linear one (DLL). For beginners, it reinforces the importance of traversal techniques, pointer manipulation, and understanding recursive logic.

Always remember to handle edge cases like empty trees or single-node trees gracefully, and ensure your recursive base case is well-defined to prevent stack overflow.

Algorithm Steps

  1. If the binary tree is empty, return null.
  2. Recursively convert the left subtree into a doubly linked list.
  3. Recursively convert the right subtree into a doubly linked list.
  4. Make the root node a standalone doubly linked list node by setting its left and right pointers to null.
  5. If a left list exists, find its rightmost (tail) node and link it with the root: set tail.right = root and root.left = tail.
  6. If a right list exists, link the root with the head of the right list: set root.right = rightList and rightList.left = root.
  7. Return the head of the combined doubly linked list (the head of the left list if it exists, otherwise the root).

Code

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

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

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

TreeNode* treeToDLL(TreeNode* root) {
    if (root == NULL) return NULL;
    TreeNode* leftList = treeToDLL(root->left);
    TreeNode* rightList = treeToDLL(root->right);
    root->left = root->right = NULL;
    TreeNode* head;
    if (leftList) {
        head = leftList;
        TreeNode* tail = leftList;
        while (tail->right) {
            tail = tail->right;
        }
        tail->right = root;
        root->left = tail;
    } else {
        head = root;
    }
    if (rightList) {
        root->right = rightList;
        rightList->left = root;
    }
    return head;
}

int main() {
    TreeNode* root = createNode(1);
    root->left = createNode(2);
    root->right = createNode(3);
    root->left->left = createNode(4);
    root->right->left = createNode(5);
    root->right->right = createNode(6);

    TreeNode* dllHead = treeToDLL(root);
    TreeNode* curr = dllHead;
    while (curr) {
        printf("%d", curr->val);
        if (curr->right) printf(" <-> ");
        curr = curr->right;
    }
    printf("\n");
    return 0;
}

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