Data Structures & Algorithms Interview Questions

叶 路. - "from collections import deque def updateword(words, startword, end_word): if end_word not in words: return None # Early exit if end_word is not in the dictionary queue = deque([(start_word, 0)]) # (word, steps) visited = set([start_word]) # Keep track of visited words while queue: word, steps = queue.popleft() if word == end_word: return steps # Found the target word, return steps for i in range(len(word)): "See full answer

Yeshwanth D. - "Was this for an entry level engineer role?"See full answer

Anonymous Roadrunner - "def is_palindrome(s: str) -> bool: new = '' for a in s: if a.isalpha() or a.isdigit(): new += a.lower() return (new == new[::-1]) debug your code below print(is_palindrome('abcba')) `"See full answer

Rick E. - " O(n) - characters in the string O(n) - stack def identify_adjacent(s: str, k: int) -> str: stack = [] n = len(s) for ch in s: if stack: topch, topcnt = stack[-1] if top_ch == ch: top_cnt += 1 stack[-1] = (ch, top_cnt) else: top_cnt = 1 stack.append((ch,1)) if top_cnt == k: stack.pop() else: stack.append"See full answer

Alfred O. - "We can use dictionary to store cache items so that our read / write operations will be O(1). Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1) Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"See full answer

Warrenbuff - "#include #include #include using namespace std; vector diff(const vector& A, const vector& B) { unordered_set elements; vector result; for (const auto& element : A) { elements.insert(element); } for (const auto& element : B) { if (elements.find(element) == elements.end()) { result.push_back(element); } else { elements.erase(element); } } for"See full answer

Anonymous Prawn - "Would be better to adjust resolution in the video player directly."See full answer

Kishor J. - "we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"See full answer

Rahul M. - "Idea for solution: Reverse the complete char array Reverse the words separated by space. i.e. Find the space characters and the reverse the subarray between two space characters. vector reverseSubarray(vector& arr, int s, int e) { while (s reverseWords(vector& arr ) { int n = arr.size(); reverse(arr, 0, n - 1"See full answer

Jessica R. - "a top-down recursive solution with memoization in python: from typing import List from functools import cache def changeSigns(nums: List[int], S: int) -> int: @cache def dp(i, curr_sum): if i == len(nums): if curr_sum == S: return 1 return 0 return dp(i+1, currsum + nums[i]) + dp(i+1, currsum - nums[i]) answer = dp(0, 0) if answer == 0: return -1 return answer `"See full answer

Kofi N. - "const mergeIntervals = (intervals) => { const compare = (a, b) => { if(a[0] b[0]) return 1 else if(a[0] === b[0]) { return a[1] - b[1] } } let current = [] const result = [] const sorted = intervals.sort(compare) for(let i = 0; i = b[0]) current[1] = b[1] els"See full answer

Tiago R. - "function isValid(s) { const stack = []; for (let i=0; i < s.length; i++) { const char = s.charAt(i); if (['(', '{', '['].includes(char)) { stack.push(char); } else { const top = stack.pop(); if ((char === ')' && top !== '(') || (char === '}' && top !== '{') || (char === ']' && top !== '[')) { return false; } } } return stack.length === 0"See full answer

Tiago R. - "function canFinish(numCourses, prerequisites) { if (prerequisites.length === 0) return true; const dependencies = new Map(prerequisites); const visited = new Set(); for (let [course, precourse] of prerequisites) { visited.add(course); while (!visited.has(precourse)) { visited.add(precourse); if (dependencies.has(precourse)) { precourse = dependencies.get(precourse); if (visited.has(precourse)) { "See full answer

Avon T. - "Initialize left pointer: Set a left pointer left to 0. Iterate through the array: Iterate through the array from left to right. If the current element is not 0, swap it with the element at the left pointer and increment left. Time complexity: O(n). The loop iterates through the entire array once, making it linear time. Space complexity: O(1). The algorithm operates in-place, modifying the input array directly without using additional data structures. "See full answer

Tiago R. - "function mostCommonWords(text) { const frequencyTable = new Map(); const words = text.toLowerCase().replace(//g, '').split(' '); for (let word of words) { frequencyTable.set(word, (frequencyTable.get(word) || 0)+1); } frequencyTable.delete(''); return [...frequencyTable.entries()].sort(([w1, f1], [w2, f2]) => f2-f1 !== 0? f2-f1 : w1.charCodeAt(0)-w2.charCodeAt(0) ); } `"See full answer

Tiago R. - "class Node { constructor(data) { this.data = data; this.left = null; this.right = null; } } function exploreSubtree(node) { let leftHeight = 0; let rightHeight = 0; let maxDiameter = 0; // visit left if (node.left) { const leftVisit = exploreSubtree(node.left); leftHeight = leftVisit.height + 1; maxDiameter = Math.max(maxDiameter, leftVisit.maxDiameter); } // visit right if (node.right) { con"See full answer

Sammy R. - "In python def find_duplicates(arr1: List[int], arr2: List[int]) -> List[int]: result = list(set(arr1) & set(arr2)) return result "See full answer

Sachin R. - "If 0's aren't a concern, couldn't we just multiply all numbers. and then divide product by each number in the list ? if there's more than one zero, then we just return an array of 0s if there's one zero, then we just replace 0 with product and rest 0s. what am i missing?"See full answer

Jordan Z. - "Maybe we can use this solution: 1, connect all the strings together, and add an integer value ahead each string. 2, use Huffmans algorithm to encode the step 1 result, to make the result size smaller. 3, return the root of Huffmans tree. This solution man be slower than the common serialize method, but it can save a lot of memory, I think, at lease doing serialize is mainly for tranfering data or storing data."See full answer

Matthew K. - " function climbStairs(n) { // 4 iterations of Dynamic Programming solutions: // Step 1: Recursive: // if (n <= 2) return n // return climbStairs(n-1) + climbStairs(n-2) // Step 2: Top-down Memoization // const memo = {0:0, 1:1, 2:2} // function f(x) { // if (x in memo) return memo[x] // memo[x] = f(x-1) + f(x-2) // return memo[x] // } // return f(n) // Step 3: Bottom-up Tabulation // const tab = [0,1,2] // f"See full answer