Introduction

In this blog post, we'll share the most commonly asked coding interview questions at Otter.ai. If you don't have months to study for your interviews, you can use AI tools like Chatmagic to generate solutions quickly and efficiently - helping you pass the interviews and get the job offer!

Problem #1: Trapping Rain Water II

Given an m x n integer matrix heightMap representing the height of each unit cell in a 2D elevation map, return the volume of water it can trap after raining. Example 1: Input: heightMap = [[1,4,3,1,3,2],[3,2,1,3,2,4],[2,3,3,2,3,1]] Output: 4 Explanation: After the rain, water is trapped between the blocks. We have two small ponds 1 and 3 units trapped. The total volume of water trapped is 4. Example 2: Input: heightMap = [[3,3,3,3,3],[3,2,2,2,3],[3,2,1,2,3],[3,2,2,2,3],[3,3,3,3,3]] Output: 10 Constraints: m == heightMap.length n == heightMap[i].length 1 <= m, n <= 200 0 <= heightMap[i][j] <= 2 * 104

Topics: Array, Breadth-First Search, Heap (Priority Queue), Matrix

Problem #2: Word Break

Given a string s and a dictionary of strings wordDict, return true if s can be segmented into a space-separated sequence of one or more dictionary words. Note that the same word in the dictionary may be reused multiple times in the segmentation. Example 1: Input: s = "leetcode", wordDict = ["leet","code"] Output: true Explanation: Return true because "leetcode" can be segmented as "leet code". Example 2: Input: s = "applepenapple", wordDict = ["apple","pen"] Output: true Explanation: Return true because "applepenapple" can be segmented as "apple pen apple". Note that you are allowed to reuse a dictionary word. Example 3: Input: s = "catsandog", wordDict = ["cats","dog","sand","and","cat"] Output: false Constraints: 1 <= s.length <= 300 1 <= wordDict.length <= 1000 1 <= wordDict[i].length <= 20 s and wordDict[i] consist of only lowercase English letters. All the strings of wordDict are unique.

Topics: Array, Hash Table, String, Dynamic Programming, Trie, Memoization

Problem #3: Flatten Deeply Nested Array

Given a multi-dimensional array arr and a depth n, return a flattened version of that array. A multi-dimensional array is a recursive data structure that contains integers or other multi-dimensional arrays. A flattened array is a version of that array with some or all of the sub-arrays removed and replaced with the actual elements in that sub-array. This flattening operation should only be done if the current depth of nesting is less than n. The depth of the elements in the first array are considered to be 0. Please solve it without the built-in Array.flat method. Example 1: Input arr = [1, 2, 3, [4, 5, 6], [7, 8, [9, 10, 11], 12], [13, 14, 15]] n = 0 Output [1, 2, 3, [4, 5, 6], [7, 8, [9, 10, 11], 12], [13, 14, 15]] Explanation Passing a depth of n=0 will always result in the original array. This is because the smallest possible depth of a subarray (0) is not less than n=0. Thus, no subarray should be flattened. Example 2: Input arr = [1, 2, 3, [4, 5, 6], [7, 8, [9, 10, 11], 12], [13, 14, 15]] n = 1 Output [1, 2, 3, 4, 5, 6, 7, 8, [9, 10, 11], 12, 13, 14, 15] Explanation The subarrays starting with 4, 7, and 13 are all flattened. This is because their depth of 0 is less than 1. However [9, 10, 11] remains unflattened because its depth is 1. Example 3: Input arr = [[1, 2, 3], [4, 5, 6], [7, 8, [9, 10, 11], 12], [13, 14, 15]] n = 2 Output [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] Explanation The maximum depth of any subarray is 1. Thus, all of them are flattened. Constraints: 0 <= count of numbers in arr <= 105 0 <= count of subarrays in arr <= 105 maxDepth <= 1000 -1000 <= each number <= 1000 0 <= n <= 1000

Topics: nan