LeetCode #762 — EASY

Prime Number of Set Bits in Binary Representation

Build confidence with an intuition-first walkthrough focused on math fundamentals.

The Problem

Problem Statement

Given two integers left and right, return the count of numbers in the inclusive range [left, right] having a prime number of set bits in their binary representation.

Recall that the number of set bits an integer has is the number of 1's present when written in binary.

For example, 21 written in binary is 10101, which has 3 set bits.

Example 1:

Input: left = 6, right = 10
Output: 4
Explanation:
6  -> 110 (2 set bits, 2 is prime)
7  -> 111 (3 set bits, 3 is prime)
8  -> 1000 (1 set bit, 1 is not prime)
9  -> 1001 (2 set bits, 2 is prime)
10 -> 1010 (2 set bits, 2 is prime)
4 numbers have a prime number of set bits.

Example 2:

Input: left = 10, right = 15
Output: 5
Explanation:
10 -> 1010 (2 set bits, 2 is prime)
11 -> 1011 (3 set bits, 3 is prime)
12 -> 1100 (2 set bits, 2 is prime)
13 -> 1101 (3 set bits, 3 is prime)
14 -> 1110 (3 set bits, 3 is prime)
15 -> 1111 (4 set bits, 4 is not prime)
5 numbers have a prime number of set bits.

Constraints:

1 <= left <= right <= 10⁶
0 <= right - left <= 10⁴

Step 01

Brute Force Baseline

Problem summary: Given two integers left and right, return the count of numbers in the inclusive range [left, right] having a prime number of set bits in their binary representation. Recall that the number of set bits an integer has is the number of 1's present when written in binary. For example, 21 written in binary is 10101, which has 3 set bits.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Math · Bit Manipulation

Example 1

6
10

Example 2

10
15

Core Insight

What unlocks the optimal approach

Write a helper function to count the number of set bits in a number, then check whether the number of set bits is 2, 3, 5, 7, 11, 13, 17 or 19.

Interview move: turn each hint into an invariant you can check after every iteration/recursion step.

Step 03

Algorithm Walkthrough

Iteration Checklist

Define state (indices, window, stack, map, DP cell, or recursion frame).
Apply one transition step and update the invariant.
Record answer candidate when condition is met.
Continue until all input is consumed.

Use the first example testcase as your mental trace to verify each transition.

Step 04

Edge Cases

Minimum Input

Single element / shortest valid input

Validate boundary behavior before entering the main loop or recursion.

Duplicates & Repeats

Repeated values / repeated states

Decide whether duplicates should be merged, skipped, or counted explicitly.

Extreme Constraints

Upper-end input sizes

Re-check complexity target against constraints to avoid time-limit issues.

Invalid / Corner Shape

Empty collections, zeros, or disconnected structures

Handle special-case structure before the core algorithm path.

Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #762: Prime Number of Set Bits in Binary Representation
class Solution {
    private static Set<Integer> primes = Set.of(2, 3, 5, 7, 11, 13, 17, 19);

    public int countPrimeSetBits(int left, int right) {
        int ans = 0;
        for (int i = left; i <= right; ++i) {
            if (primes.contains(Integer.bitCount(i))) {
                ++ans;
            }
        }
        return ans;
    }
}

// Accepted solution for LeetCode #762: Prime Number of Set Bits in Binary Representation
func countPrimeSetBits(left int, right int) (ans int) {
	primes := map[int]int{}
	for _, v := range []int{2, 3, 5, 7, 11, 13, 17, 19} {
		primes[v] = 1
	}
	for i := left; i <= right; i++ {
		ans += primes[bits.OnesCount(uint(i))]
	}
	return
}

# Accepted solution for LeetCode #762: Prime Number of Set Bits in Binary Representation
class Solution:
    def countPrimeSetBits(self, left: int, right: int) -> int:
        primes = {2, 3, 5, 7, 11, 13, 17, 19}
        return sum(i.bit_count() in primes for i in range(left, right + 1))

// Accepted solution for LeetCode #762: Prime Number of Set Bits in Binary Representation
impl Solution {
    pub fn count_prime_set_bits(left: i32, right: i32) -> i32 {
        let primes = [2, 3, 5, 7, 11, 13, 17, 19];
        let mut ans = 0;

        for i in left..=right {
            let bits = i.count_ones() as i32;
            if primes.contains(&bits) {
                ans += 1;
            }
        }

        ans
    }
}

// Accepted solution for LeetCode #762: Prime Number of Set Bits in Binary Representation
function countPrimeSetBits(left: number, right: number): number {
    const primes = new Set<number>([2, 3, 5, 7, 11, 13, 17, 19]);
    let ans = 0;

    for (let i = left; i <= right; i++) {
        const bits = bitCount(i);
        if (primes.has(bits)) {
            ans++;
        }
    }

    return ans;
}

function bitCount(i: number): number {
    i = i - ((i >>> 1) & 0x55555555);
    i = (i & 0x33333333) + ((i >>> 2) & 0x33333333);
    i = (i + (i >>> 4)) & 0x0f0f0f0f;
    i = i + (i >>> 8);
    i = i + (i >>> 16);
    return i & 0x3f;
}

Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Custom checkpoints (one per line)

Press Step or Run All to begin.

Step 07

Complexity Analysis

Time

O(n)

Space

O(1)

Approach Breakdown

SORT + SCAN

O(n log n) time

O(n) space

Sort the array in O(n log n), then scan for the missing or unique element by comparing adjacent pairs. Sorting requires O(n) auxiliary space (or O(1) with in-place sort but O(n log n) time remains). The sort step dominates.

BIT MANIPULATION

O(n) time

O(1) space

Bitwise operations (AND, OR, XOR, shifts) are O(1) per operation on fixed-width integers. A single pass through the input with bit operations gives O(n) time. The key insight: XOR of a number with itself is 0, which eliminates duplicates without extra space.

Shortcut: Bit operations are O(1). XOR cancels duplicates. Single pass → O(n) time, O(1) space.

Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Overflow in intermediate arithmetic

Wrong move: Temporary multiplications exceed integer bounds.

Usually fails on: Large inputs wrap around unexpectedly.

Fix: Use wider types, modular arithmetic, or rearranged operations.