Introduction

In this blog post, we'll share the most commonly asked coding interview questions at ByteDance. 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: LRU Cache

Design a data structure that follows the constraints of a Least Recently Used (LRU) cache. Implement the LRUCache class: LRUCache(int capacity) Initialize the LRU cache with positive size capacity. int get(int key) Return the value of the key if the key exists, otherwise return -1. void put(int key, int value) Update the value of the key if the key exists. Otherwise, add the key-value pair to the cache. If the number of keys exceeds the capacity from this operation, evict the least recently used key. The functions get and put must each run in O(1) average time complexity. Example 1: Input ["LRUCache", "put", "put", "get", "put", "get", "put", "get", "get", "get"] [[2], [1, 1], [2, 2], [1], [3, 3], [2], [4, 4], [1], [3], [4]] Output [null, null, null, 1, null, -1, null, -1, 3, 4] Explanation LRUCache lRUCache = new LRUCache(2); lRUCache.put(1, 1); // cache is {1=1} lRUCache.put(2, 2); // cache is {1=1, 2=2} lRUCache.get(1); // return 1 lRUCache.put(3, 3); // LRU key was 2, evicts key 2, cache is {1=1, 3=3} lRUCache.get(2); // returns -1 (not found) lRUCache.put(4, 4); // LRU key was 1, evicts key 1, cache is {4=4, 3=3} lRUCache.get(1); // return -1 (not found) lRUCache.get(3); // return 3 lRUCache.get(4); // return 4 Constraints: 1 <= capacity <= 3000 0 <= key <= 104 0 <= value <= 105 At most 2 * 105 calls will be made to get and put.

Topics: Hash Table, Linked List, Design, Doubly-Linked List

Problem #2: Regular Expression Matching

Given an input string s and a pattern p, implement regular expression matching with support for '.' and '' where: '.' Matches any single character.​​​​ '' Matches zero or more of the preceding element. The matching should cover the entire input string (not partial). Example 1: Input: s = "aa", p = "a" Output: false Explanation: "a" does not match the entire string "aa". Example 2: Input: s = "aa", p = "a" Output: true Explanation: '' means zero or more of the preceding element, 'a'. Therefore, by repeating 'a' once, it becomes "aa". Example 3: Input: s = "ab", p = "." Output: true Explanation: "." means "zero or more () of any character (.)". Constraints: 1 <= s.length <= 20 1 <= p.length <= 20 s contains only lowercase English letters. p contains only lowercase English letters, '.', and ''. It is guaranteed for each appearance of the character '*', there will be a previous valid character to match.

Topics: String, Dynamic Programming, Recursion

Problem #3: Add Two Numbers

You are given two non-empty linked lists representing two non-negative integers. The digits are stored in reverse order, and each of their nodes contains a single digit. Add the two numbers and return the sum as a linked list. You may assume the two numbers do not contain any leading zero, except the number 0 itself. Example 1: Input: l1 = [2,4,3], l2 = [5,6,4] Output: [7,0,8] Explanation: 342 + 465 = 807. Example 2: Input: l1 = [0], l2 = [0] Output: [0] Example 3: Input: l1 = [9,9,9,9,9,9,9], l2 = [9,9,9,9] Output: [8,9,9,9,0,0,0,1] Constraints: The number of nodes in each linked list is in the range [1, 100]. 0 <= Node.val <= 9 It is guaranteed that the list represents a number that does not have leading zeros.

Topics: Linked List, Math, Recursion

Problem #4: Combination Sum II

Given a collection of candidate numbers (candidates) and a target number (target), find all unique combinations in candidates where the candidate numbers sum to target. Each number in candidates may only be used once in the combination. Note: The solution set must not contain duplicate combinations. Example 1: Input: candidates = [10,1,2,7,6,1,5], target = 8 Output: [ [1,1,6], [1,2,5], [1,7], [2,6] ] Example 2: Input: candidates = [2,5,2,1,2], target = 5 Output: [ [1,2,2], [5] ] Constraints: 1 <= candidates.length <= 100 1 <= candidates[i] <= 50 1 <= target <= 30

Topics: Array, Backtracking

Problem #5: Maximal Square

Given an m x n binary matrix filled with 0's and 1's, find the largest square containing only 1's and return its area. Example 1: Input: matrix = [["1","0","1","0","0"],["1","0","1","1","1"],["1","1","1","1","1"],["1","0","0","1","0"]] Output: 4 Example 2: Input: matrix = [["0","1"],["1","0"]] Output: 1 Example 3: Input: matrix = [["0"]] Output: 0 Constraints: m == matrix.length n == matrix[i].length 1 <= m, n <= 300 matrix[i][j] is '0' or '1'.

Topics: Array, Dynamic Programming, Matrix

Problem #6: Minimum Area Rectangle

You are given an array of points in the X-Y plane points where points[i] = [xi, yi]. Return the minimum area of a rectangle formed from these points, with sides parallel to the X and Y axes. If there is not any such rectangle, return 0. Example 1: Input: points = [[1,1],[1,3],[3,1],[3,3],[2,2]] Output: 4 Example 2: Input: points = [[1,1],[1,3],[3,1],[3,3],[4,1],[4,3]] Output: 2 Constraints: 1 <= points.length <= 500 points[i].length == 2 0 <= xi, yi <= 4 * 104 All the given points are unique.

Topics: Array, Hash Table, Math, Geometry, Sorting

Problem #7: Number of Good Leaf Nodes Pairs

You are given the root of a binary tree and an integer distance. A pair of two different leaf nodes of a binary tree is said to be good if the length of the shortest path between them is less than or equal to distance. Return the number of good leaf node pairs in the tree. Example 1: Input: root = [1,2,3,null,4], distance = 3 Output: 1 Explanation: The leaf nodes of the tree are 3 and 4 and the length of the shortest path between them is 3. This is the only good pair. Example 2: Input: root = [1,2,3,4,5,6,7], distance = 3 Output: 2 Explanation: The good pairs are [4,5] and [6,7] with shortest path = 2. The pair [4,6] is not good because the length of ther shortest path between them is 4. Example 3: Input: root = [7,1,4,6,null,5,3,null,null,null,null,null,2], distance = 3 Output: 1 Explanation: The only good pair is [2,5]. Constraints: The number of nodes in the tree is in the range [1, 210]. 1 <= Node.val <= 100 1 <= distance <= 10

Topics: Tree, Depth-First Search, Binary Tree

Problem #8: Rotting Oranges

You are given an m x n grid where each cell can have one of three values: 0 representing an empty cell, 1 representing a fresh orange, or 2 representing a rotten orange. Every minute, any fresh orange that is 4-directionally adjacent to a rotten orange becomes rotten. Return the minimum number of minutes that must elapse until no cell has a fresh orange. If this is impossible, return -1. Example 1: Input: grid = [[2,1,1],[1,1,0],[0,1,1]] Output: 4 Example 2: Input: grid = [[2,1,1],[0,1,1],[1,0,1]] Output: -1 Explanation: The orange in the bottom left corner (row 2, column 0) is never rotten, because rotting only happens 4-directionally. Example 3: Input: grid = [[0,2]] Output: 0 Explanation: Since there are already no fresh oranges at minute 0, the answer is just 0. Constraints: m == grid.length n == grid[i].length 1 <= m, n <= 10 grid[i][j] is 0, 1, or 2.

Topics: Array, Breadth-First Search, Matrix

Problem #9: Longest Common Subsequence

Given two strings text1 and text2, return the length of their longest common subsequence. If there is no common subsequence, return 0. A subsequence of a string is a new string generated from the original string with some characters (can be none) deleted without changing the relative order of the remaining characters. For example, "ace" is a subsequence of "abcde". A common subsequence of two strings is a subsequence that is common to both strings. Example 1: Input: text1 = "abcde", text2 = "ace" Output: 3 Explanation: The longest common subsequence is "ace" and its length is 3. Example 2: Input: text1 = "abc", text2 = "abc" Output: 3 Explanation: The longest common subsequence is "abc" and its length is 3. Example 3: Input: text1 = "abc", text2 = "def" Output: 0 Explanation: There is no such common subsequence, so the result is 0. Constraints: 1 <= text1.length, text2.length <= 1000 text1 and text2 consist of only lowercase English characters.

Topics: String, Dynamic Programming

Problem #10: Best Time to Buy and Sell Stock

You are given an array prices where prices[i] is the price of a given stock on the ith day. You want to maximize your profit by choosing a single day to buy one stock and choosing a different day in the future to sell that stock. Return the maximum profit you can achieve from this transaction. If you cannot achieve any profit, return 0. Example 1: Input: prices = [7,1,5,3,6,4] Output: 5 Explanation: Buy on day 2 (price = 1) and sell on day 5 (price = 6), profit = 6-1 = 5. Note that buying on day 2 and selling on day 1 is not allowed because you must buy before you sell. Example 2: Input: prices = [7,6,4,3,1] Output: 0 Explanation: In this case, no transactions are done and the max profit = 0. Constraints: 1 <= prices.length <= 105 0 <= prices[i] <= 104

Topics: Array, Dynamic Programming