To solve the problem of finding the longest binary gap in a given positive integer ( N ), we can follow these steps:
-
Convert the integer ( N ) into its binary representation. In JavaScript, you can do this using
toString(2)
method. -
Traverse through the binary representation to identify sequences of consecutive zeros (‘0’). Keep track of the length of each sequence.
-
As we identify these sequences, keep track of the maximum length encountered.
-
Finally, return the length of the longest binary gap found. If no binary gaps are found, return 0.
Here’s the JavaScript implementation based on the described approach:
function solution(N) {
const binaryString = N.toString(2); // Convert N to binary string
let maxGapLength = 0;
let currentGapLength = 0;
let inGap = false;
for (let i = 0; i < binaryString.length; i++) {
if (binaryString[i] === '1') {
if (inGap) {
// We've encountered the end of a gap
if (currentGapLength > maxGapLength) {
maxGapLength = currentGapLength;
}
currentGapLength = 0;
}
inGap = true;
} else {
if (inGap) {
// We are inside a gap
currentGapLength++;
}
}
}
return maxGapLength;
}
N.toString(2)
converts ( N ) to its binary string representation.
Then we ierate through each character of the binary string
When encountering ‘1’, check if we were already in a gap (i.e., inGap
is true). If so, this signifies the end of a gap, so update maxGapLength
if the current gap is longer than previously recorded.
When encountering ‘0’, if we are in a gap (inGap
is true), increment currentGapLength
.
After the loop, ensure to check if the last recorded gap (if any) is the longest.
This algorithm is efficient with a time complexity of ( O(log N) ), where ( N ) is the integer input, due to the conversion to binary and subsequent traversal of its digits. This ensures it can handle the maximum input size within reasonable time constraints.