338. Counting Bits
Problem Description
Given an integer n, return an array ans of length n + 1 such that for each i (0 <= i <= n), ans[i] is the number of 1's in the binary representation of i.
Example 1:
Input: n = 2
Output: [0,1,1]
Explanation:
0 --> 0
1 --> 1
2 --> 10
Example 2:
Input: n = 5
Output: [0,1,1,2,1,2]
Explanation:
0 --> 0
1 --> 1
2 --> 10
3 --> 11
4 --> 100
5 --> 101
Constraints:
0 <= n <= 10⁵
Follow up:
- It is very easy to come up with a solution with a runtime of
O(n log n). Can you do it in linear timeO(n)and possibly in a single pass? - Can you do it without using any built-in function (i.e., like
__builtin_popcountin C++)?
Solution
Python Solution
class Solution:
def countBits(self, n: int) -> List[int]:
ans = [0] * (n + 1)
for i in range(1, n + 1):
# i >> 1 is i/2, so we can use previously calculated result
# i & 1 is checking if i is odd (1) or even (0)
ans[i] = ans[i >> 1] + (i & 1)
return ans
Time Complexity: O(n)
Single pass through the array.
Space Complexity: O(1)
Not counting the output array.
Java Solution
class Solution {
public int[] countBits(int n) {
int[] ans = new int[n + 1];
for (int i = 1; i <= n; i++) {
// i >> 1 is i/2, so we can use previously calculated result
// i & 1 is checking if i is odd (1) or even (0)
ans[i] = ans[i >> 1] + (i & 1);
}
return ans;
}
}
Time Complexity: O(n)
Single pass through the array.
Space Complexity: O(1)
Not counting the output array.
C++ Solution
class Solution {
public:
vector countBits(int n) {
vector ans(n + 1);
for (int i = 1; i <= n; i++) {
// i >> 1 is i/2, so we can use previously calculated result
// i & 1 is checking if i is odd (1) or even (0)
ans[i] = ans[i >> 1] + (i & 1);
}
return ans;
}
};
Time Complexity: O(n)
Single pass through the array.
Space Complexity: O(1)
Not counting the output array.
JavaScript Solution
/**
* @param {number} n
* @return {number[]}
*/
var countBits = function(n) {
const ans = new Array(n + 1).fill(0);
for (let i = 1; i <= n; i++) {
// i >> 1 is i/2, so we can use previously calculated result
// i & 1 is checking if i is odd (1) or even (0)
ans[i] = ans[i >> 1] + (i & 1);
}
return ans;
};
Time Complexity: O(n)
Single pass through the array.
Space Complexity: O(1)
Not counting the output array.
C# Solution
public class Solution {
public int[] CountBits(int n) {
int[] ans = new int[n + 1];
for (int i = 1; i <= n; i++) {
// i >> 1 is i/2, so we can use previously calculated result
// i & 1 is checking if i is odd (1) or even (0)
ans[i] = ans[i >> 1] + (i & 1);
}
return ans;
}
}
Time Complexity: O(n)
Single pass through the array.
Space Complexity: O(1)
Not counting the output array.
Approach Explanation
The solution uses dynamic programming with bit manipulation:
- Key Insight:
- Pattern recognition
- Bit manipulation
- Dynamic programming
- Optimal substructure
- Algorithm Steps:
- Initialize array
- Use previous results
- Bit operations
- Build solution
Example walkthrough:
- Start with 0
- Use right shift
- Check last bit
- Build answer
Optimization insights:
- Single pass
- No counting needed
- Constant operations
- Space efficient
Edge Cases:
- n = 0
- n = 1
- Powers of 2
- Large numbers