Vertical width of Binary tree | Set 1
Last Updated :
11 Jul, 2025
Given a Binary tree, the task is to find the vertical width of the Binary tree. The width of a binary tree is the number of vertical paths in the Binary tree.
Examples:
Input:

Output: 6
Explanation: In this image, the tree contains 6 vertical lines which are the required width of the tree.
Input :
7
/ \
6 5
/ \ / \
4 3 2 1
Output : 5
Input:
1
/ \
2 3
/ \ / \
4 5 6 7
\ \
8 9
Output : 6
Approach:
Take inorder traversal and then take a temp variable to keep the track of unique vertical paths. when moving to left of the node then temp decreases by one and if goes to right then temp value increases by one. If the minimum is greater than temp, then update minimum = temp and if maximum less than temp then update maximum = temp. The vertical width of the tree will be equal to abs(minimum ) + maximum.
Follow the below steps to Implement the idea:
- Initialize a minimum and maximum variable to track the left-most and right-most index.
- Run Depth-first search traversal and maintain the current horizontal index curr, for root curr = 0.
- Traverse left subtree with curr = curr-1
- Update maximum with curr if curr > maximum.
- Update minimum with curr if curr < minimum.
- Traverse right subtree with curr = curr + 1.
- Print the vertical width of the tree i.e. abs(minimum ) + maximum.
Below is the Implementation of the above approach:
C++
// CPP program to print vertical width
// of a tree
#include <bits/stdc++.h>
using namespace std;
// A Binary Tree Node
struct Node {
int data;
struct Node *left, *right;
};
// get vertical width
void lengthUtil(Node* root, int& maximum, int& minimum,
int curr = 0)
{
if (root == NULL)
return;
// traverse left
lengthUtil(root->left, maximum, minimum, curr - 1);
// if curr is decrease then get
// value in minimum
if (minimum > curr)
minimum = curr;
// if curr is increase then get
// value in maximum
if (maximum < curr)
maximum = curr;
// traverse right
lengthUtil(root->right, maximum, minimum, curr + 1);
}
int getLength(Node* root)
{
int maximum = 0, minimum = 0;
lengthUtil(root, maximum, minimum, 0);
// 1 is added to include root in the width
return (abs(minimum) + maximum) + 1;
}
// Utility function to create a new tree node
Node* newNode(int data)
{
Node* curr = new Node;
curr->data = data;
curr->left = curr->right = NULL;
return curr;
}
// Driver program to test above functions
int main()
{
Node* root = newNode(7);
root->left = newNode(6);
root->right = newNode(5);
root->left->left = newNode(4);
root->left->right = newNode(3);
root->right->left = newNode(2);
root->right->right = newNode(1);
cout << getLength(root) << "\n";
return 0;
}
Java
// Java program to print vertical width
// of a tree
import java.util.*;
class GFG {
// A Binary Tree Node
static class Node {
int data;
Node left, right;
};
static int maximum = 0, minimum = 0;
// get vertical width
static void lengthUtil(Node root, int curr)
{
if (root == null)
return;
// traverse left
lengthUtil(root.left, curr - 1);
// if curr is decrease then get
// value in minimum
if (minimum > curr)
minimum = curr;
// if curr is increase then get
// value in maximum
if (maximum < curr)
maximum = curr;
// traverse right
lengthUtil(root.right, curr + 1);
}
static int getLength(Node root)
{
maximum = 0;
minimum = 0;
lengthUtil(root, 0);
// 1 is added to include root in the width
return (Math.abs(minimum) + maximum) + 1;
}
// Utility function to create a new tree node
static Node newNode(int data)
{
Node curr = new Node();
curr.data = data;
curr.left = curr.right = null;
return curr;
}
// Driver Code
public static void main(String[] args)
{
Node root = newNode(7);
root.left = newNode(6);
root.right = newNode(5);
root.left.left = newNode(4);
root.left.right = newNode(3);
root.right.left = newNode(2);
root.right.right = newNode(1);
System.out.println(getLength(root));
}
}
// This code is contributed by Rajput-Ji
Python3
# Python3 program to print vertical width
# of a tree
# class to create a new tree node
class newNode:
def __init__(self, data):
self.data = data
self.left = self.right = None
# get vertical width
def lengthUtil(root, maximum, minimum, curr=0):
if (root == None):
return
# traverse left
lengthUtil(root.left, maximum,
minimum, curr - 1)
# if curr is decrease then get
# value in minimum
if (minimum[0] > curr):
minimum[0] = curr
# if curr is increase then get
# value in maximum
if (maximum[0] < curr):
maximum[0] = curr
# traverse right
lengthUtil(root.right, maximum,
minimum, curr + 1)
def getLength(root):
maximum = [0]
minimum = [0]
lengthUtil(root, maximum, minimum, 0)
# 1 is added to include root in the width
return (abs(minimum[0]) + maximum[0]) + 1
# Driver Code
if __name__ == '__main__':
root = newNode(7)
root.left = newNode(6)
root.right = newNode(5)
root.left.left = newNode(4)
root.left.right = newNode(3)
root.right.left = newNode(2)
root.right.right = newNode(1)
print(getLength(root))
# This code is contributed by PranchalK
C#
// C# program to print vertical width
// of a tree
using System;
class GFG {
// A Binary Tree Node
public class Node {
public int data;
public Node left, right;
};
static int maximum = 0, minimum = 0;
// get vertical width
static void lengthUtil(Node root, int curr)
{
if (root == null)
return;
// traverse left
lengthUtil(root.left, curr - 1);
// if curr is decrease then get
// value in minimum
if (minimum > curr)
minimum = curr;
// if curr is increase then get
// value in maximum
if (maximum < curr)
maximum = curr;
// traverse right
lengthUtil(root.right, curr + 1);
}
static int getLength(Node root)
{
maximum = 0;
minimum = 0;
lengthUtil(root, 0);
// 1 is added to include root in the width
return (Math.Abs(minimum) + maximum) + 1;
}
// Utility function to create a new tree node
static Node newNode(int data)
{
Node curr = new Node();
curr.data = data;
curr.left = curr.right = null;
return curr;
}
// Driver Code
public static void Main(String[] args)
{
Node root = newNode(7);
root.left = newNode(6);
root.right = newNode(5);
root.left.left = newNode(4);
root.left.right = newNode(3);
root.right.left = newNode(2);
root.right.right = newNode(1);
Console.WriteLine(getLength(root));
}
}
// This code is contributed by PrinciRaj1992
JavaScript
<script>
// JavaScript program to prvertical width
// of a tree
// class to create a new tree node
class newNode{
constructor(data){
this.data = data
this.left = this.right = null
}
}
// get vertical width
function lengthUtil(root, maximum, minimum, curr = 0){
if (root == null)
return
// traverse left
lengthUtil(root.left, maximum,
minimum, curr - 1)
// if curr is decrease then get
// value in minimum
if (minimum[0] > curr)
minimum[0] = curr
// if curr is increase then get
// value in maximum
if (maximum[0] <curr)
maximum[0] = curr
// traverse right
lengthUtil(root.right, maximum,
minimum, curr + 1)
}
function getLength(root)
{
let maximum = [0]
let minimum = [0]
lengthUtil(root, maximum, minimum, 0)
// 1 is added to include root in the width
return (Math.abs(minimum[0]) + maximum[0]) + 1
}
// Driver Code
root = new newNode(7)
root.left = new newNode(6)
root.right = new newNode(5)
root.left.left = new newNode(4)
root.left.right = new newNode(3)
root.right.left = new newNode(2)
root.right.right = new newNode(1)
document.write(getLength(root),"</br>")
// This code is contributed by shinjanpatra.
</script>
Time Complexity: O(n)
Auxiliary Space: O(h) where h is the height of the binary tree. This much space is needed for recursive calls.
Below is the idea to solve the problem:
Create a class to store the node and the horizontal level of the node. The horizontal level of left node will be 1 less than its parent, and horizontal level of the right node will be 1 more than its parent. We create a minLevel variable to store the minimum horizontal level or the leftmost node in the tree, and a maxLevel variable to store the maximum horizontal level or the rightmost node in the tree. Traverse the tree in level order and store the minLevel and maxLevel. In the end, print sum of maxLevel and absolute value of minLevel which is the vertical width of the tree.
Follow the below steps to Implement the idea:
- Initialize two variables maxLevel = 0 and minLevel = 0 and queue Q of pair of the type (Node*, Integer).
- Push (root, 0) in Q.
- Run while loop till Q is not empty
- Store the front node of the Queue in cur and the current horizontal level in count.
- If curr->left is not null then push (root->left, count-1) and update minLevel with min(minLevel, count-1).
- If curr->right is not null then push (root->right, count+1) and update maxLevel with max(maxLevel, count+1).
- Print maxLevel + abs(minLevel) + 1.
Below is the Implementation of the above approach:
C++
// C++ program to find Vertical Height of a tree
#include <bits/stdc++.h>
#include <iostream>
using namespace std;
struct Node {
int data;
struct Node* left;
struct Node* right;
Node(int x)
{
data = x;
left = right = NULL;
}
};
int verticalWidth(Node* root)
{
// Code here
if (root == NULL)
return 0;
int maxLevel = 0, minLevel = 0;
queue<pair<Node*, int> > q;
q.push({ root, 0 }); // we take root as 0
// Level order traversal code
while (q.empty() != true) {
Node* cur = q.front().first;
int count = q.front().second;
q.pop();
if (cur->left) {
minLevel = min(minLevel,
count - 1); // as we go left,
// level is decreased
q.push({ cur->left, count - 1 });
}
if (cur->right) {
maxLevel = max(maxLevel,
count + 1); // as we go right,
// level is increased
q.push({ cur->right, count + 1 });
}
}
return maxLevel + abs(minLevel)
+ 1; // +1 for the root node, we gave it a value
// of zero
}
int main()
{
// making the tree
Node* root = new Node(7);
root->left = new Node(6);
root->right = new Node(5);
root->left->left = new Node(4);
root->left->right = new Node(3);
root->right->left = new Node(2);
root->right->right = new Node(1);
cout << "Vertical width is : " << verticalWidth(root)
<< endl;
return 0;
}
// code contributed by Anshit Bansal
Java
// Java program to print vertical width
// of a tree
import java.util.*;
class GFG {
// A Binary Tree Node
static class Node {
int data;
Node left, right;
};
static class Pair {
Node node;
int level; // Horizontal Level
Pair(Node node, int level)
{
this.node = node;
this.level = level;
}
}
static int maxLevel = 0, minLevel = 0;
// get vertical width
static void lengthUtil(Node root)
{
Queue<Pair> q = new ArrayDeque<>();
// Adding the root node initially with level as 0;
q.add(new Pair(root, 0));
while (q.size() > 0) {
// removing the node at the peek of queue;
Pair rem = q.remove();
// If the left child of removed node exists
if (rem.node.left != null) {
// level of the left child will be 1 less
// than its parent
q.add(
new Pair(rem.node.left, rem.level - 1));
// updating the minLevel
minLevel
= Math.min(minLevel, rem.level - 1);
}
// If the right child of removed node exists
if (rem.node.right != null) {
// level of the right child will be 1 more
// than its parent
q.add(new Pair(rem.node.right,
rem.level + 1));
// updating the minLevel
maxLevel
= Math.max(minLevel, rem.level + 1);
}
}
}
static int getLength(Node root)
{
maxLevel = 0;
minLevel = 0;
lengthUtil(root);
// 1 is added to include root in the width
return (Math.abs(minLevel) + maxLevel) + 1;
}
// Utility function to create a new tree node
static Node newNode(int data)
{
Node curr = new Node();
curr.data = data;
curr.left = curr.right = null;
return curr;
}
// Driver Code
public static void main(String[] args)
{
Node root = newNode(7);
root.left = newNode(6);
root.right = newNode(5);
root.left.left = newNode(4);
root.left.right = newNode(3);
root.right.left = newNode(2);
root.right.right = newNode(1);
System.out.println(getLength(root));
}
}
// This code is contributed by Archit Sharma
Python3
# Python code for the above approach
class Node:
# A Binary Tree Node
def __init__(self, data):
self.data = data
self.left = None
self.right = None
# get vertical width
def verticalWidth(root):
if root == None:
return 0
maxLevel = 0
minLevel = 0
q = []
# Adding the root node initially with level as 0;
q.append([root, 0]) # we take root as 0
# Level order traversal code
while len(q) != 0:
# removing the node at the peek of queue;
cur, count = q.pop(0)
# If the left child of removed node exists
if cur.left:
# updating the minLevel
minLevel = min(minLevel, count - 1)
# level of the left child will be 1 less than its parent
q.append([cur.left, count - 1])
# If the right child of removed node exists
if cur.right:
# updating the maxLevel
maxLevel = max(maxLevel, count + 1)
# level of the right child will be 1 more
# than its parent
q.append([cur.right, count + 1])
return maxLevel + abs(minLevel) + 1
# making the tree
root = Node(7)
root.left = Node(6)
root.right = Node(5)
root.left.left = Node(4)
root.left.right = Node(3)
root.right.left = Node(2)
root.right.right = Node(1)
print("Vertical width is : ", verticalWidth(root))
# This code is contributed by Potta Lokesh
C#
// C# program to print vertical width of a tree
using System;
using System.Collections;
public class GFG {
// A Binary Tree Node
class Node {
public int data;
public Node left, right;
};
class Pair {
public Node node;
public int level; // Horizontal Level
public Pair(Node node, int level)
{
this.node = node;
this.level = level;
}
}
static int maxLevel = 0, minLevel = 0;
// get vertical width
static void lengthUtil(Node root)
{
Queue q = new Queue();
// Adding the root node initially with level as 0;
q.Enqueue(new Pair(root, 0));
while (q.Count > 0) {
// removing the node at the peek of queue;
Pair rem = (Pair)q.Dequeue();
// If the left child of removed node exists
if (rem.node.left != null) {
// level of the left child will be 1 less
// than its parent
q.Enqueue(
new Pair(rem.node.left, rem.level - 1));
// updating the minLevel
minLevel
= Math.Min(minLevel, rem.level - 1);
}
// If the right child of removed node exists
if (rem.node.right != null) {
// level of the right child will be 1 more
// than its parent
q.Enqueue(new Pair(rem.node.right,
rem.level + 1));
// updating the minLevel
maxLevel
= Math.Max(minLevel, rem.level + 1);
}
}
}
static int getLength(Node root)
{
maxLevel = 0;
minLevel = 0;
lengthUtil(root);
// 1 is added to include root in the width
return (Math.Abs(minLevel) + maxLevel) + 1;
}
// Utility function to create a new tree node
static Node newNode(int data)
{
Node curr = new Node();
curr.data = data;
curr.left = curr.right = null;
return curr;
}
static public void Main()
{
// Code
Node root = newNode(7);
root.left = newNode(6);
root.right = newNode(5);
root.left.left = newNode(4);
root.left.right = newNode(3);
root.right.left = newNode(2);
root.right.right = newNode(1);
Console.WriteLine(getLength(root));
}
}
// This code is contributed by lokeshmvs21.
JavaScript
class Node {
constructor(x) {
this.data = x;
this.left = null;
this.right = null;
}
}
function verticalWidth(root) {
if (!root) {
return 0;
}
let maxLevel = 0;
let minLevel = 0;
const q = [];
q.push([root, 0]); // we take root as 0
// Level order traversal code
while (q.length !== 0) {
const [cur, count] = q.shift();
if (cur.left) {
minLevel = Math.min(minLevel, count - 1); // as we go left, level is decreased
q.push([cur.left, count - 1]);
}
if (cur.right) {
maxLevel = Math.max(maxLevel, count + 1); // as we go right, level is increased
q.push([cur.right, count + 1]);
}
}
return maxLevel + Math.abs(minLevel) + 1; // +1 for the root node, we gave it a value of zero
}
// making the tree
const root = new Node(7);
root.left = new Node(6);
root.right = new Node(5);
root.left.left = new Node(4);
root.left.right = new Node(3);
root.right.left = new Node(2);
root.right.right = new Node(1);
console.log("Vertical width is: ", verticalWidth(root));
Time Complexity: O(n). This much time is needed to traverse the tree.
Auxiliary Space: O(n). This much space is needed to maintain the queue.
Vertical width of Binary tree | Set 1
Similar Reads
Basics & Prerequisites
Data Structures
Array Data StructureIn this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions. An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous
3 min read
String in Data StructureA string is a sequence of characters. The following facts make string an interesting data structure.Small set of elements. Unlike normal array, strings typically have smaller set of items. For example, lowercase English alphabet has only 26 characters. ASCII has only 256 characters.Strings are immut
2 min read
Hashing in Data StructureHashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. Hashing involves mapping data to a specific index in a hash table (an array of items) using a hash function. It enables fast retrieval of information based on its key. The
2 min read
Linked List Data StructureA linked list is a fundamental data structure in computer science. It mainly allows efficient insertion and deletion operations compared to arrays. Like arrays, it is also used to implement other data structures like stack, queue and deque. Hereâs the comparison of Linked List vs Arrays Linked List:
2 min read
Stack Data StructureA Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). LIFO implies that the element that is inserted last, comes out first and FILO implies that the element that is inserted first
2 min read
Queue Data StructureA Queue Data Structure is a fundamental concept in computer science used for storing and managing data in a specific order. It follows the principle of "First in, First out" (FIFO), where the first element added to the queue is the first one to be removed. It is used as a buffer in computer systems
2 min read
Tree Data StructureTree Data Structure is a non-linear data structure in which a collection of elements known as nodes are connected to each other via edges such that there exists exactly one path between any two nodes. Types of TreeBinary Tree : Every node has at most two childrenTernary Tree : Every node has at most
4 min read
Graph Data StructureGraph Data Structure is a collection of nodes connected by edges. It's used to represent relationships between different entities. If you are looking for topic-wise list of problems on different topics like DFS, BFS, Topological Sort, Shortest Path, etc., please refer to Graph Algorithms. Basics of
3 min read
Trie Data StructureThe Trie data structure is a tree-like structure used for storing a dynamic set of strings. It allows for efficient retrieval and storage of keys, making it highly effective in handling large datasets. Trie supports operations such as insertion, search, deletion of keys, and prefix searches. In this
15+ min read
Algorithms
Searching AlgorithmsSearching algorithms are essential tools in computer science used to locate specific items within a collection of data. In this tutorial, we are mainly going to focus upon searching in an array. When we search an item in an array, there are two most common algorithms used based on the type of input
2 min read
Sorting AlgorithmsA Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ
3 min read
Introduction to RecursionThe process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. A recursive algorithm takes one step toward solution and then recursively call itself to further move. The algorithm stops once we reach the solution
14 min read
Greedy AlgorithmsGreedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. At every step of the algorithm, we make a choice that looks the best at the moment. To make the choice, we sometimes sort the array so that we can always get
3 min read
Graph AlgorithmsGraph is a non-linear data structure like tree data structure. The limitation of tree is, it can only represent hierarchical data. For situations where nodes or vertices are randomly connected with each other other, we use Graph. Example situations where we use graph data structure are, a social net
3 min read
Dynamic Programming or DPDynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of
3 min read
Bitwise AlgorithmsBitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers to perform operations efficiently. These algorithms utilize bitwise operators like AND, OR, XOR, NOT, Left Shift, and Right Shift.BasicsIntroduction to Bitwise Algorit
4 min read
Advanced
Segment TreeSegment Tree is a data structure that allows efficient querying and updating of intervals or segments of an array. It is particularly useful for problems involving range queries, such as finding the sum, minimum, maximum, or any other operation over a specific range of elements in an array. The tree
3 min read
Pattern SearchingPattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Patten SearchingImportant Pattern Searching Algorithms:Naive String Matching : A Simple Algorithm that works i
2 min read
GeometryGeometry is a branch of mathematics that studies the properties, measurements, and relationships of points, lines, angles, surfaces, and solids. From basic lines and angles to complex structures, it helps us understand the world around us.Geometry for Students and BeginnersThis section covers key br
2 min read
Interview Preparation
Practice Problem