Position of rightmost different bit (original) (raw)
Last Updated : 3 Oct, 2025
Given two numbers **m and **n. Find the position of the rightmost different bit in the binary representation of numbers. It is guaranteed that such a bit exists
**Examples:
**Input: m = 11, n = 9
Output: 2
Explanation: (11) 10 = (1011)2, (9) 10 = (1001)2
It can be seen that **2nd bit from the right is differentInput: m = 52, n = 4
Output: 5
Explanation: (52) 10 = (110100)2,(4) 10 = (100)2, can also be written as = (000100)2
It can be seen that **5th bit from the right is different
Table of Content
- Position of rightmost different bit using XOR:
- Position of rightmost different bit using ffs() function:
Position of rightmost different bit using XOR:
Get the bitwise xor of **m and **n. Let it be **xor_value = m ^ n. Now, find the position of rightmost set bit in **xor_value. As 0 XOR 1 and 1 XOR 0 equals 1, so if a bit is set in the XOR value then it means that the bits at that position were different in the given numbers
An efficient way to find the rightmost set bit:
For n = 10, which is 00001010 in binary, we can find the position of its rightmost set bit using the expression log2(n & -n) + 1. First, we calculate -n using two's complement by inverting the bits of 10 to get 11110101 and adding 1 to obtain 11110110. Performing (n & -n) gives 00000010, which is 2 in decimal. Taking log2(2) results in 1, and adding 1 gives us 2, indicating that the rightmost set bit of 10 is at position 2 from the right. This method efficiently isolates the rightmost set bit and calculates its position using bitwise operations and logarithms.
C++ `
#include <bits/stdc++.h> using namespace std;
// Function to find the position of // rightmost set bit in 'n' // returns 0 if there is no set bit. int getRightMostSetBit(int n) { // to handle edge case when n = 0. if (n == 0) return 0;
return log2(n & -n) + 1;}
// Function to find the position of // rightmost different bit in the // binary representations of 'm' and 'n' // returns 0 if there is no // rightmost different bit. int posOfRightMostDiffBit(int m, int n) { // position of rightmost different // bit
return getRightMostSetBit(m ^ n);}
int main() { int m = 52, n = 4;
cout << posOfRightMostDiffBit(m, n) << endl;
return 0;}
Java
class GFG {
// Function to find the position of
// rightmost set bit in 'n'
// return 0 if there is no set bit.
static int getRightMostSetBit(int n)
{
if (n == 0)
return 0;
return (int)((Math.log10(n & -n)) / Math.log10(2))
+ 1;
}
// Function to find the position of
// rightmost different bit in the
// binary representations of 'm' and 'n'
static int posOfRightMostDiffBit(int m, int n)
{
// position of rightmost different bit
return getRightMostSetBit(m ^ n);
}
public static void main(String arg[])
{
int m = 52, n = 4;
System.out.print( + posOfRightMostDiffBit(m, n));
}}
Python
import math
Function to find the position of
rightmost set bit in 'n'
def getRightMostSetBit(n): if (n == 0): return 0
return math.log2(n & -n) + 1Function to find the position of
rightmost different bit in the
binary representations of 'm' and 'n'
def posOfRightMostDiffBit(m, n):
# position of rightmost different
# bit
return getRightMostSetBit(m ^ n)if name == "main": m = 52 n = 4 print(int(posOfRightMostDiffBit(m, n)))
C#
using System;
class GFG {
// Function to find the position of
// rightmost set bit in 'n'
static int getRightMostSetBit(int n)
{
if (n == 0)
return 0;
return (int)((Math.Log10(n & -n)) / Math.Log10(2))
+ 1;
}
// Function to find the position of
// rightmost different bit in the
// binary representations of 'm' and 'n'
static int posOfRightMostDiffBit(int m, int n)
{
// position of rightmost different bit
return getRightMostSetBit(m ^ n);
}
// Driver code
public static void Main()
{
int m = 52, n = 4;
// Function call
Console.Write( posOfRightMostDiffBit(m, n));
}}
JavaScript
// Function to find the position // of rightmost set bit in 'n' function getRightMostSetBit(n) { if (n === 0) return 0;
return Math.log2(n & -n) + 1;}
// Function to find the position // of rightmost different bit function posOfRightMostDiffBit(m, n) { return getRightMostSetBit(m ^ n); }
// Driver code let m = 52, n = 4;
console.log(posOfRightMostDiffBit(m, n));
PHP
`
**Time Complexity: O(log2 N), this time complexity is equal to O(1) as one has to check for at most 31 bits only
**Auxiliary Space: O(1)
Position of rightmost different bit using ffs() function:
ffs() function searches the first set bit from the right side and then returns the index of that bit (1-based indexing). So we can use this function on the XOR of both the values to get the index of the rightmost different bit
C++ `
#include <bits/stdc++.h> using namespace std;
// function to find rightmost different // bit in two numbers. int posOfRightMostDiffBit(int m, int n) { return ffs(m ^ n); }
int main() { int m = 52, n = 4;
// Function call
cout << posOfRightMostDiffBit(m, n);
return 0;}
Java
import java.util.*; class GFG {
// function to find rightmost
// different bit in two numbers.
static int posOfRightMostDiffBit(int m, int n)
{
return (int)Math.floor(
Math.log10(Math.pow(m ^ n, 2)))
+ 2;
}
public static void main(String[] args)
{
int m = 52, n = 4;
// Function call
System.out.println(posOfRightMostDiffBit(m, n));
}}
Python
from math import floor, log10
Function to find rightmost different
bit in two numbers.
def posOfRightMostDiffBit(m, n):
return floor(log10(pow(m ^ n, 2))) + 2if name == 'main':
m, n = 52, 4
print(
posOfRightMostDiffBit(m, n))C#
using System; class GFG {
// function to find rightmost
// different bit in two numbers.
static int posOfRightMostDiffBit(int m, int n)
{
return (int)Math.Floor(
Math.Log10(Math.Pow(m ^ n, 2)))
+ 2;
}
public static void Main(String[] args)
{
int m = 52, n = 4;
Console.Write( posOfRightMostDiffBit(m, n));
}}
// This code is contributed by shivanisinghss2110
JavaScript
// Function to find the position of rightmost different bit function posOfRightMostDiffBit(m, n) { let x = m ^ n; if (x === 0) return 0;
return Math.log2(x & -x) + 1;}
// Driver code let m = 52, n = 4; console.log(posOfRightMostDiffBit(m, n));
PHP
`
**Time Complexity: O(log2 N), this time complexity is equal to O(1) as one has to check for at most 31 bits only
**Auxiliary Space: O(1)