Count Set Bits Brian Kernighan Algorithm in DSA Typescript - Time & Space Complexity

Time Complexity: Count Set Bits Brian Kernighan Algorithm

O(k)

Understanding Time Complexity

We want to understand how fast the Brian Kernighan algorithm counts the number of 1s in a binary number.

How does the time taken grow as the number gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function countSetBits(n: number): number {
  let count = 0;
  while (n !== 0) {
    n = n & (n - 1);
    count++;
  }
  return count;
}
    

This code counts how many bits are set to 1 in the binary form of the number n by repeatedly turning off the rightmost set bit.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The while loop that clears the rightmost set bit each time.
• How many times: The loop runs once for each set bit (1) in the number.

How Execution Grows With Input

Execution depends on how many 1s are in the number, not its size in bits.

Input Size (n)	Approx. Operations (loop runs)
10 (binary 1010)	2
15 (binary 1111)	4
1023 (binary 1111111111)	10

Pattern observation: The number of operations equals the count of 1 bits, which can be much less than total bits.

Final Time Complexity

Time Complexity: O(k)

This means the time grows with the number of set bits (k), not the total bits in the number.

Common Mistake

[X] Wrong: "The loop runs once for every bit in the number (total bits)."

[OK] Correct: The loop only runs for each 1 bit, skipping zeros, so it can be much faster.

Interview Connect

Knowing this algorithm shows you understand bit manipulation and efficient counting, a useful skill in many coding problems.

Self-Check

What if we changed the input to always have only one set bit? How would the time complexity change?

Practice

1. What does the Brian Kernighan algorithm do when counting set bits in a number?

easy

A. It repeatedly clears the least significant set bit until the number becomes zero.

B. It counts the total number of digits in the number.

C. It shifts the number to the right until it becomes zero without checking bits.

D. It adds all bits of the number without any bitwise operation.

Solution

1. Step 1: Understand the algorithm's main operation

   The Brian Kernighan algorithm clears the least significant set bit in each iteration by doing n = n & (n-1).

2. Step 2: Effect of clearing bits

   Each clearing reduces the number of set bits by one until the number becomes zero, counting how many set bits were present.

3. Final Answer:

   It repeatedly clears the least significant set bit until the number becomes zero. -> Option A

4. Quick Check:

   Clearing bits one by one counts set bits [OK]

Hint: Clear least set bit repeatedly to count set bits [OK]

Common Mistakes:

• Confusing bit count with digit count
• Using simple right shifts without bit checks
• Ignoring bitwise AND operation

2. Which of the following is the correct TypeScript syntax to clear the least significant set bit of a number n?

easy

A. n = n | (n - 1);

B. n = n & (n - 1);

C. n = n ^ (n - 1);

D. n = n + (n - 1);

Solution

1. Step 1: Identify the bitwise operation to clear least set bit

   The operation n = n & (n - 1) clears the least significant set bit in n.

2. Step 2: Verify other options

   OR, XOR, and addition do not clear the least significant set bit correctly.

3. Final Answer:

   n = n & (n - 1); -> Option B

4. Quick Check:

   AND with (n-1) clears least set bit [OK]

Hint: Use AND with (n-1) to clear least set bit [OK]

Common Mistakes:

• Using OR or XOR instead of AND
• Adding numbers instead of bitwise operations
• Missing parentheses around (n - 1)

3. What is the output of the following TypeScript code?

function countSetBits(n: number): number {
  let count = 0;
  while (n > 0) {
    n = n & (n - 1);
    count++;
  }
  return count;
}

console.log(countSetBits(13));

medium

A. 3

B. 4

C. 2

D. 5

Solution

1. Step 1: Convert 13 to binary and count set bits

   13 in binary is 1101, which has three set bits (1,1,0,1).

2. Step 2: Apply Brian Kernighan algorithm steps

   Each iteration clears one set bit, so count increments 3 times until n becomes 0.

3. Final Answer:

   3 -> Option A

4. Quick Check:

   Number of 1s in 1101 = 3 [OK]

Hint: Count 1s in binary using n & (n-1) loop [OK]

Common Mistakes:

• Counting total bits instead of set bits
• Misunderstanding binary representation
• Off-by-one errors in loop count

4. Identify the error in this TypeScript function that tries to count set bits using Brian Kernighan's algorithm:

function countSetBits(n: number): number {
  let count = 0;
  while (n != 0) {
    n = n & n - 1;
    count++;
  }
  return count;
}

medium

A. Return statement is missing.

B. Using != instead of > in the while condition.

C. Incorrect initialization of count variable.

D. Missing parentheses around (n - 1) in the expression.

Solution

1. Step 1: Analyze the expression inside the loop

   The expression n = n & n - 1 lacks parentheses, so it is evaluated as (n & n) - 1, which is incorrect.

2. Step 2: Correct expression

   It should be n = n & (n - 1) to correctly clear the least significant set bit.

3. Final Answer:

   Missing parentheses around (n - 1) in the expression. -> Option D

4. Quick Check:

   Parentheses ensure correct order of operations [OK]

Hint: Use parentheses: n = n & (n - 1) [OK]

Common Mistakes:

• Using != 0 causing potential infinite loop for negatives
• Assuming both conditions always equivalent
• Operator precedence confusion causing wrong calculation

5. Given an array of numbers [5, 7, 10], which TypeScript code correctly uses Brian Kernighan's algorithm to return an array of their set bit counts?

hard

A. const counts = arr.map(n => {
let count = 0;
while (n > 0) {
n = n >> 1;
count++;
}
return count;
});

B. const counts = arr.map(n => n.toString(2).length);

C. const counts = arr.map(n => {
let count = 0;
while (n > 0) {
n = n & (n - 1);
count++;
}
return count;
});

D. const counts = arr.map(n => {
let count = 0;
for (let i = 0; i < 32; i++) {
if ((n & (1 << i)) !== 0) count++;
}
return count;
});

Solution

1. Step 1: Understand Brian Kernighan's algorithm usage

   const counts = arr.map(n => { let count = 0; while (n > 0) { n = n & (n - 1); count++; } return count; }); uses the correct loop with n = n & (n - 1) to count set bits for each number.

2. Step 2: Check other options for correctness

   const counts = arr.map(n => n.toString(2).length); counts total binary digits, not set bits. const counts = arr.map(n => { let count = 0; while (n > 0) { n = n >> 1; count++; } return count; }); counts total bits by shifting, not set bits. const counts = arr.map(n => { let count = 0; for (let i = 0; i < 32; i++) { if ((n & (1 << i)) !== 0) count++; } return count; }); uses a loop checking each bit, which works but is not Brian Kernighan's algorithm.

3. Final Answer:

   const counts = arr.map(n => { let count = 0; while (n > 0) { n = n & (n - 1); count++; } return count; }); -> Option C

4. Quick Check:

   Use n & (n-1) loop inside map for set bits [OK]

Hint: Use map with n & (n-1) loop for each number [OK]

Common Mistakes:

• Counting binary string length instead of set bits
• Using right shift without bit check
• Confusing bitwise loop with simple iteration