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Merge pull request #812 from Jeehay28/main
[Jeehay28] Week 4
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/** | ||
* @param {number[]} coins | ||
* @param {number} amount | ||
* @return {number} | ||
*/ | ||
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// TC : O(c*a), where c is the number of coins, and a is amount | ||
// SC : O(a) // dp array requires O(a) space | ||
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var coinChange = function (coins, amount) { | ||
// dynamic programming approach | ||
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// dp[amount] : the minimum number of coins | ||
// as a default, dp[0] = 0, for other amounts, dp[amount] = amount + 1 () | ||
// [0, amount+1, amount+1, ...] | ||
const dp = [0, ...new Array(amount).fill(amount + 1)]; | ||
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// start from coin because i - coin >= 0 | ||
for (const coin of coins) { | ||
for (let i = coin; i <= amount; i++) { | ||
// dp[i] : not using the current coin | ||
// dp[i - coin] + 1 : using the current coin | ||
dp[i] = Math.min(dp[i - coin] + 1, dp[i]); | ||
} | ||
} | ||
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// dp[amount] === amount + 1 : that amount of money cannot be made up by any combination of the coins | ||
return dp[amount] < amount + 1 ? dp[amount] : -1; | ||
}; | ||
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/** | ||
* Definition for singly-linked list. | ||
* function ListNode(val, next) { | ||
* this.val = (val===undefined ? 0 : val) | ||
* this.next = (next===undefined ? null : next) | ||
* } | ||
*/ | ||
/** | ||
* @param {ListNode} list1 | ||
* @param {ListNode} list2 | ||
* @return {ListNode} | ||
*/ | ||
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// Time Complexity: O(m + n) | ||
// Space Complexity: O(m + n) | ||
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var mergeTwoLists = function(list1, list2) { | ||
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if(!(list1 && list2)) { | ||
return list1 || list2; | ||
} | ||
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if(list1.val < list2.val) { | ||
list1.next = mergeTwoLists(list1.next, list2); | ||
return list1; | ||
} else { | ||
list2.next = mergeTwoLists(list1, list2.next); | ||
return list2; | ||
} | ||
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}; | ||
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/** | ||
* @param {number[]} nums | ||
* @return {number} | ||
*/ | ||
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// *** Guided approach 2: bitwise operations and avoids potential overflow issues with very large sums | ||
// XOR method | ||
// Time complexity: O(n)(two loops: one for numbers 0 to n and one for array elements) | ||
// Space complexity: O(1) | ||
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var missingNumber = function (nums) { | ||
// XOR with itself results in 0 : a xor a = 0 | ||
// XOR with 0 results in the number itself : a xor 0 = a | ||
// XOR is commutative and associative | ||
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const n = nums.length; | ||
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let xor = 0; | ||
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for (let i = 0; i <= n; i++) { | ||
xor ^= i; | ||
} | ||
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for (any of nums) { | ||
xor ^= any; | ||
} | ||
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return xor; | ||
}; | ||
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// *** Guided approach 1: simplicity and clarity | ||
// Gauss' Formula (Sum of First n Numbers): n*(n+1) / 2 | ||
// Time complexity: O(n) | ||
// Space complexity: O(1) | ||
// var missingNumber = function (nums) { | ||
// const n = nums.length; | ||
// const expectedSum = (n * (n + 1)) / 2; | ||
// const actualSum = nums.reduce((acc, cur) => acc + cur, 0); // O(n) | ||
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// const missingNum = expectedSum - actualSum; | ||
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// return missingNum; | ||
// }; | ||
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// *** My own approach | ||
// Time complexity: O(n^2) | ||
// Space complexity: O(n) | ||
// var missingNumber = function (nums) { | ||
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// let distinctNums = new Set([]); | ||
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// for (any of nums) { | ||
// if (distinctNums.has(any)) { | ||
// return | ||
// } else { | ||
// distinctNums.add(any) | ||
// } | ||
// } | ||
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// const n = distinctNums.size; | ||
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// for (let i = 0; i <= n; i++) { | ||
// if (!nums.includes(i)) { | ||
// return i; | ||
// } | ||
// } | ||
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// }; |
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/** | ||
* @param {string} s | ||
* @return {number} | ||
*/ | ||
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// TC : O(n^2) | ||
// SC : O(1) | ||
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var countSubstrings = function (s) { | ||
// For each character in the string, treat it as the center of a potential palindrome. | ||
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// 'Count Palindromic Substrings' helper function | ||
const countPS = (left, right) => { | ||
let cnt = 0; | ||
while (left >= 0 && right < s.length && s[left] === s[right]) { | ||
cnt += 1; | ||
left -= 1; | ||
right += 1; | ||
} | ||
return cnt; | ||
}; | ||
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let totCnt = 0; | ||
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for (let i = 0; i < s.length; i++) { | ||
// left === right : 1 center point, odd-length palindromic | ||
totCnt += countPS(i, i); | ||
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// left !== right : 2 center points, even-length palindromic | ||
totCnt += countPS(i, i + 1); | ||
} | ||
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return totCnt; | ||
}; | ||
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/** | ||
* @param {character[][]} board | ||
* @param {string} word | ||
* @return {boolean} | ||
*/ | ||
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// board(N * M), where N is the number of row and M is the number of columns | ||
// L, the length of the word | ||
// TC : O(N * M * 4^L) | ||
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// recursion depth : the length of the word (L) | ||
// each recursion call requires constant space. | ||
// SC : O(L) | ||
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var exist = function (board, word) { | ||
let row = board.length; | ||
let col = board[0].length; | ||
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const dfs = (r, c, idx) => { | ||
// search done | ||
if (idx === word.length) { | ||
return true; | ||
} | ||
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// row and column are out of range | ||
if (r < 0 || r >= row || c < 0 || c >= col) { | ||
return false; | ||
} | ||
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if (board[r][c] !== word[idx]) { | ||
return false; | ||
} | ||
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// word[idx] === board[r][c] | ||
// continue searching for word[idx + 1] in adjacent cells on the board | ||
const temp = board[r][c]; | ||
board[r][c] = "visited"; | ||
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const arr = [ | ||
[1, 0], // Move down | ||
[-1, 0], // Move up | ||
[0, 1], // Move right | ||
[0, -1], // Move left | ||
]; | ||
for (const [up, right] of arr) { | ||
if (dfs(r + up, c + right, idx + 1)) { | ||
return true; | ||
} | ||
} | ||
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board[r][c] = temp; | ||
return false; | ||
}; | ||
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for (let i = 0; i < row; i++) { | ||
for (let j = 0; j < col; j++) { | ||
if (dfs(i, j, 0)) { | ||
return true; | ||
} | ||
} | ||
} | ||
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return false; | ||
}; | ||
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