Merge pull request DaleStudy#85 from sounmind/main

Evan, Week 4

Author: leokim0922

counting-bits/evan.js

@@ -0,0 +1,25 @@
+/**
+ * @param {number} n
+ * @return {number[]}
+ */
+var countBits = function (n) {
+  const result = new Array(n + 1).fill(0);
+
+  for (let i = 1; i <= n; i++) {
+    /** The number of 1's in i divided by 2, except last bit of i */
+    const totalOnes = result[i >> 1];
+    const lastBit = i & 1;
+
+    result[i] = totalOnes + lastBit;
+  }
+
+  return result;
+};
+
+/**
+ * Time Complexity: O(n), where n is number input
+ * Reason: The algorithm processes each number from 1 to n exactly once.
+ *
+ * Space Complexity: O(n), where n is number input
+ * Reason: The algorithm uses an array of size n + 1
+ */

group-anagrams/evan.js

@@ -0,0 +1,35 @@
+/**
+ * @param {string[]} strList
+ * @return {string[][]}
+ */
+var groupAnagrams = function (strList) {
+  const map = new Map();
+
+  for (const str of strList) {
+    const sortedStr = str.split("").sort().join("");
+
+    if (!map.has(sortedStr)) {
+      map.set(sortedStr, []);
+    }
+
+    map.get(sortedStr).push(str);
+  }
+
+  return Array.from(map.values());
+};
+
+/**
+ * Time Complexity: O(n * k log k)
+ * Reason:
+ * - n is the number of strings in the input array.
+ * - k is the maximum length of a string in the input array.
+ * - Sorting each string takes O(k log k) time.
+ * - Thus, sorting all n strings takes O(n * k log k) time.
+ *
+ * Space Complexity: O(n * k)
+ * Reason:
+ * - We use a map to store the grouped anagrams.
+ * - In the worst case, we might store all n strings in the map.
+ * - Each string has a maximum length of k.
+ * - Thus, the space complexity is O(n * k).
+ */

missing-number/evan.js

@@ -0,0 +1,26 @@
+/**
+ * @param {number[]} nums
+ * @return {number}
+ */
+var missingNumber = function (nums) {
+  const expectedSum = (nums.length * (nums.length + 1)) / 2;
+  const actualSum = nums.reduce((prev, curr) => prev + curr);
+
+  return expectedSum - actualSum;
+};
+
+/**
+ * Time Complexity: O(n)
+ * Reason:
+ * - Finding the maximum number in the array takes O(n) time.
+ * - Calculating the target sum takes O(1) time.
+ * - Iterating through the array to update the target number takes O(n) time.
+ * - Checking the condition and returning the result takes O(1) time.
+ * - Therefore, the overall time complexity is O(n).
+ *
+ * Space Complexity: O(1)
+ * Reason:
+ * - The algorithm uses a constant amount of extra space (variables like maxNumber, hasZero, targetNumber).
+ * - No additional space proportional to the input size is used.
+ * - Therefore, the overall space complexity is O(1).
+ */

number-of-1-bits/evan.js

@@ -0,0 +1,23 @@
+/**
+ * @param {number} n, maximum 32 bit number
+ * @return {number}
+ */
+var hammingWeight = function (n) {
+  return n.toString(2).replace(/0/g, "").length;
+};
+
+/**
+ * Time Complexity: O(1)
+ * Reason:
+ * - n.toString(2): Converts the number to a binary string, which has a fixed length of up to 32 bits. This is O(1) because the length is constant.
+ * - replace(/0/g, ''): Removes all '0's from the binary string. The operation is O(1) since the string length is at most 32 characters.
+ * - .length: Getting the length of the resulting string is O(1).
+ * Therefore, the overall time complexity is O(1).
+ *
+ * Space Complexity: O(1)
+ * Reason:
+ * - n.toString(2): The binary string representation has a fixed maximum length of 32 characters, which requires O(1) space.
+ * - replace(/0/g, ''): The resulting string after removing '0's has a length of at most 32 characters, so it also requires O(1) space.
+ * - .length: Retrieving the length of a string does not require additional space.
+ * Therefore, the overall space complexity is O(1).
+ */

reverse-bits/evan.js

@@ -0,0 +1,22 @@
+/**
+ * @param {number} n - a positive integer
+ * @return {number} - a positive integer
+ */
+var reverseBits = function (n) {
+  const binary = n.toString(2).padStart(32, "0");
+  const reversedBinary = binary.split("").reverse().join("");
+
+  return parseInt(reversedBinary, 2);
+};
+
+/**
+ * Time Complexity: O(1)
+ * Reason:
+ * - Each step involves operations on fixed-length strings or arrays (maximum length of 32).
+ * - Thus, the time complexity for each operation is constant, resulting in an overall time complexity of O(1).
+ *
+ * Space Complexity: O(1)
+ * Reason:
+ * - The algorithm uses a constant amount of space for the binary string, reversed binary string, and intermediate arrays.
+ * - Each of these has a fixed length of 32, so the overall space complexity is O(1).
+ */