What does the Brian Kernighan algorithm do in the context of bits?
It counts the number of set bits (1s) in the binary representation of a number by repeatedly turning off the rightmost set bit until the number becomes zero.
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intermediate
Explain the key operation n = n & (n - 1) in Brian Kernighan's algorithm.
This operation removes the rightmost set bit from n. It works because subtracting 1 flips all bits after the rightmost set bit, and ANDing with n clears that set bit.
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intermediate
Why is Brian Kernighan's algorithm more efficient than checking each bit one by one?
Because it only loops as many times as there are set bits, not the total number of bits, making it faster especially for numbers with few set bits.
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beginner
Write the base case condition for the Brian Kernighan algorithm loop.
The loop continues while n is not zero. When n becomes zero, all set bits have been counted and removed.
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intermediate
What is the time complexity of Brian Kernighan's algorithm?
O(k), where k is the number of set bits in the number. This is usually faster than O(log n) for checking all bits.
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What does the expression n & (n - 1) do in Brian Kernighan's algorithm?
AAdds 1 to n
BFlips all bits of n
CRemoves the rightmost set bit from n
DChecks if n is even
✗ Incorrect
The expression clears the rightmost set bit, helping count set bits efficiently.
How many times does the loop run in Brian Kernighan's algorithm?
AAlways fixed 32 times
BTotal number of bits in n
CNumber of unset bits in n
DNumber of set bits in n
✗ Incorrect
The loop runs once for each set bit, making it efficient.
What is the initial value of the count variable in the algorithm?
A0
B1
Cn
DUndefined
✗ Incorrect
Count starts at zero and increments each time a set bit is removed.
When does the Brian Kernighan algorithm stop running?
AWhen n becomes negative
BWhen n becomes zero
CWhen count reaches n
DAfter 32 iterations
✗ Incorrect
The loop stops when all set bits are removed and n is zero.
Which of these is a benefit of Brian Kernighan's algorithm?
ARuns faster for numbers with few set bits
BUses more memory
CChecks every bit regardless
DOnly works for even numbers
✗ Incorrect
It loops only as many times as set bits, so it is faster for sparse bit patterns.
Describe how Brian Kernighan's algorithm counts set bits in a number.
Think about how the algorithm removes one set bit at a time.
You got /5 concepts.
Explain why Brian Kernighan's algorithm is more efficient than checking each bit individually.
Focus on how the number of iterations relates to set bits.
You got /4 concepts.
Practice
(1/5)
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
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).
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.
Final Answer:
It repeatedly clears the least significant set bit until the number becomes zero. -> Option A
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
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.
Step 2: Verify other options
OR, XOR, and addition do not clear the least significant set bit correctly.
Final Answer:
n = n & (n - 1); -> Option B
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
Step 1: Convert 13 to binary and count set bits
13 in binary is 1101, which has three set bits (1,1,0,1).
Step 2: Apply Brian Kernighan algorithm steps
Each iteration clears one set bit, so count increments 3 times until n becomes 0.
Final Answer:
3 -> Option A
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
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.
Step 2: Correct expression
It should be n = n & (n - 1) to correctly clear the least significant set bit.
Final Answer:
Missing parentheses around (n - 1) in the expression. -> Option D
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
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
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.
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.
Final Answer:
const counts = arr.map(n => {
let count = 0;
while (n > 0) {
n = n & (n - 1);
count++;
}
return count;
}); -> Option C
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
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