Why Count Set Bits Brian Kernighan Algorithm in DSA Python?

The Big Idea

Discover how a simple trick can make counting bits lightning fast!

The Scenario

Imagine you have a long list of numbers, and you want to know how many bits are set to 1 in each number. Doing this by checking every bit one by one feels like counting every grain of sand on a beach by hand.

The Problem

Checking each bit manually is slow and boring. It wastes time because you look at bits that are zero and don't add to the count. This makes the process long and error-prone, especially for big numbers.

The Solution

The Brian Kernighan Algorithm smartly skips all the zero bits and jumps directly from one set bit to the next. It uses a simple trick to remove the rightmost set bit in each step, making counting very fast and neat.

Before vs After

✗ Before

def count_set_bits(number):
    count = 0
    while number > 0:
        count += number & 1
        number >>= 1
    return count

✓ After

def count_set_bits(number):
    count = 0
    while number > 0:
        number &= number - 1
        count += 1
    return count

What It Enables

This algorithm lets you count set bits quickly and efficiently, even in very large numbers, saving time and effort.

Real Life Example

In networking, counting set bits helps find how many devices are active in a network mask or how many features are enabled in a settings flag.

Key Takeaways

Manual bit counting checks every bit, which is slow.

Brian Kernighan's method removes one set bit at a time, speeding up counting.

This makes bit counting efficient and practical for big numbers.

Practice

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

easy

A. It shifts the number to the right until it becomes zero without counting bits.

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

C. It converts the number to a string and counts the characters.

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

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 bits were set.

3. Final Answer:

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

4. Quick Check:

   Clearing bits counts set bits [OK]

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

Common Mistakes:

• Thinking it counts all digits, not just set bits
• Confusing bit shifting with bit clearing
• Counting characters in string form of number

2. Which of the following is the correct syntax to clear the least significant set bit in Python using Brian Kernighan's method?

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 bit clearing operation

   The correct operation to clear the least significant set bit is n = n & (n - 1).

2. Step 2: Understand why other options are incorrect

   Using OR, XOR, or addition does not clear the least significant set bit correctly.

3. Final Answer:

   n = n & (n - 1) -> Option A

4. Quick Check:

   Bit clear uses AND with n-1 [OK]

Hint: Use AND with n minus one to clear bits [OK]

Common Mistakes:

• Using OR instead of AND
• Using XOR which toggles bits
• Adding numbers instead of bitwise operations

3. What is the output of the following Python code using Brian Kernighan's algorithm?

def count_set_bits(n):
    count = 0
    while n:
        n = n & (n - 1)
        count += 1
    return count

print(count_set_bits(13))

medium

A. 3

B. 5

C. 4

D. 2

Solution

1. Step 1: Convert 13 to binary

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

2. Step 2: Count set bits using the algorithm

   Each iteration clears one set bit: 1101 -> 1100 -> 1000 -> 0000, total 3 times.

3. Final Answer:

   3 -> Option A

4. Quick Check:

   Binary 1101 has 3 set bits [OK]

Hint: Count 1s in binary of number [OK]

Common Mistakes:

• Counting total bits instead of set bits
• Miscounting binary digits
• Confusing decimal with binary

4. Find the error in the following code that tries to count set bits using Brian Kernighan's algorithm:

def count_set_bits(n):
    count = 0
    while n > 0:
        n = n & (n + 1)
        count += 1
    return count

print(count_set_bits(7))

medium

A. Loop condition should be n != 0

B. Missing initialization of count variable

C. Using n & (n + 1) instead of n & (n - 1)

D. Using addition instead of bitwise AND

Solution

1. Step 1: Identify the bit clearing operation

   The code uses n & (n + 1), which does not clear the least significant set bit correctly.

2. Step 2: Correct operation for clearing bits

   The correct operation is n = n & (n - 1) to clear the rightmost set bit.

3. Final Answer:

   Using n & (n + 1) instead of n & (n - 1) -> Option C

4. Quick Check:

   Use n & (n - 1) to clear bits [OK]

Hint: Use n & (n - 1), not n & (n + 1) [OK]

Common Mistakes:

• Using n & (n + 1) which is incorrect
• Confusing loop condition syntax
• Forgetting to initialize count

5. Given a list of integers, which code snippet correctly uses Brian Kernighan's algorithm to return a list of counts of set bits for each number?

nums = [3, 5, 7]

A) def count_bits_list(nums):
       return [bin(n).count('1') for n in nums]

B) def count_bits_list(nums):
       def count_set_bits(n):
           count = 0
           while n:
               n = n & (n - 1)
               count += 1
           return count
       return [count_set_bits(n) for n in nums]

C) def count_bits_list(nums):
       return [sum(int(d) for d in str(n)) for n in nums]

D) def count_bits_list(nums):
       return [len(str(n)) for n in nums]

hard

A. Option A uses built-in count of '1's in binary string.

B. Option B uses Brian Kernighan's algorithm correctly.

C. Option C sums digits of decimal string, not bits.

D. Option D counts decimal digits, not bits.

Solution

1. Step 1: Analyze the code snippets

   The first snippet uses Python's bin(n).count('1'), which counts set bits but not Brian Kernighan's algorithm. The second snippet implements the algorithm correctly using a while loop that clears the least significant set bit with n = n & (n - 1). The third sums the decimal digits, which is incorrect for bits. The fourth counts the length of the decimal string, also incorrect.

2. Step 2: Confirm correct implementation

   The second snippet defines count_set_bits using n = n & (n - 1) in a loop and applies it to each number via list comprehension, which is the proper use of Brian Kernighan's algorithm.

3. Final Answer:

   Option B uses Brian Kernighan's algorithm correctly. -> Option B

4. Quick Check:

   Correctly uses n & (n-1) loop [OK]

Hint: Use n & (n - 1) loop inside list comprehension [OK]

Common Mistakes:

• Using string digit sums instead of bits
• Counting decimal digits instead of set bits
• Confusing built-in binary count with algorithm