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| /** | |
| * @param {number[]} nums | |
| * @return {number} | |
| */ | |
| var minimumOperations = function(nums) { | |
| // Initialize a counter to keep track of total operations | |
| let operations = 0; | |
| // Loop through each number in the array | |
| for (let num of nums) { |
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| /** | |
| * Finds the minimum number of integers needed so that | |
| * each interval contains at least two chosen numbers. | |
| * | |
| * @param {number[][]} intervals - Array of [start, end] intervals | |
| * @return {number} - Minimum number of integers chosen | |
| */ | |
| var intersectionSizeTwo = function(intervals) { | |
| // Step 1: Sort intervals | |
| // - Primary: by end ascending (smaller right boundary first) |
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| /** | |
| * @param {number[]} nums | |
| * @param {number} original | |
| * @return {number} | |
| */ | |
| var findFinalValue = function(nums, original) { | |
| // Step 1: Convert nums into a Set for faster lookups. | |
| // Why? Searching in an array is O(n), but in a Set it's O(1). | |
| let numSet = new Set(nums); |
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| /** | |
| * @param {number[]} bits | |
| * @return {boolean} | |
| */ | |
| var isOneBitCharacter = function(bits) { | |
| // Start from the first bit | |
| let i = 0; | |
| // Traverse until the second-to-last bit | |
| // (because the last bit is always 0, we want to see if it's consumed or not) |
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| /** | |
| * @param {number[]} nums | |
| * @param {number} k | |
| * @return {boolean} | |
| */ | |
| var kLengthApart = function(nums, k) { | |
| // Keep track of the index of the last '1' we saw | |
| let lastOneIndex = -1; | |
| // Loop through the array |
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| /** | |
| * @param {string} s | |
| * @return {number} | |
| */ | |
| var numSub = function(s) { | |
| const MOD = 1_000_000_007; // Large prime for modulo operations | |
| let ans = 0; // Final answer accumulator | |
| let run = 0; // Current streak length of consecutive '1's | |
| for (let i = 0; i < s.length; i++) { |
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| /** | |
| * @param {string} s | |
| * @return {number} | |
| */ | |
| let numberOfSubstrings = function (s) { | |
| const n = s.length; | |
| // dp[i] stores the nearest index <= i where a '0' occurs | |
| // (or -1 if none). This helps us quickly jump backwards | |
| // to substrings that include more zeros. |
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| /** | |
| * @param {number} n | |
| * @param {number[][]} queries | |
| * @return {number[][]} | |
| */ | |
| var rangeAddQueries = function(n, queries) { | |
| // Step 1: Initialize an n x n matrix filled with 0s | |
| let mat = Array.from({ length: n }, () => Array(n).fill(0)); | |
| // Step 2: Process each query |
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| /** | |
| * Calculates the maximum number of operations that can be performed | |
| * on a binary string `s`. An operation is defined as pairing a '1' | |
| * with the end of a block of consecutive '0's. | |
| * | |
| * @param {string} s - Input binary string consisting of '0' and '1' | |
| * @return {number} - Maximum number of operations possible | |
| */ | |
| var maxOperations = function (s) { | |
| const n = s.length; // Length of the string |
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| /** | |
| * @param {number[]} nums | |
| * @return {number} | |
| */ | |
| var minOperations = function(nums) { | |
| // Step 1: Quick checks for trivial cases | |
| // If the array already contains a 1, spreading it is possible. | |
| // If the gcd of the entire array > 1, it's impossible to ever reach 1. | |
| const gcd = (a, b) => { |