Introduction

In this blog post, we'll share the most commonly asked coding interview questions at Cloudflare. 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: Design Circular Queue

Design your implementation of the circular queue. The circular queue is a linear data structure in which the operations are performed based on FIFO (First In First Out) principle, and the last position is connected back to the first position to make a circle. It is also called "Ring Buffer". One of the benefits of the circular queue is that we can make use of the spaces in front of the queue. In a normal queue, once the queue becomes full, we cannot insert the next element even if there is a space in front of the queue. But using the circular queue, we can use the space to store new values. Implement the MyCircularQueue class: MyCircularQueue(k) Initializes the object with the size of the queue to be k. int Front() Gets the front item from the queue. If the queue is empty, return -1. int Rear() Gets the last item from the queue. If the queue is empty, return -1. boolean enQueue(int value) Inserts an element into the circular queue. Return true if the operation is successful. boolean deQueue() Deletes an element from the circular queue. Return true if the operation is successful. boolean isEmpty() Checks whether the circular queue is empty or not. boolean isFull() Checks whether the circular queue is full or not. You must solve the problem without using the built-in queue data structure in your programming language. Example 1: Input ["MyCircularQueue", "enQueue", "enQueue", "enQueue", "enQueue", "Rear", "isFull", "deQueue", "enQueue", "Rear"] [[3], [1], [2], [3], [4], [], [], [], [4], []] Output [null, true, true, true, false, 3, true, true, true, 4] Explanation MyCircularQueue myCircularQueue = new MyCircularQueue(3); myCircularQueue.enQueue(1); // return True myCircularQueue.enQueue(2); // return True myCircularQueue.enQueue(3); // return True myCircularQueue.enQueue(4); // return False myCircularQueue.Rear(); // return 3 myCircularQueue.isFull(); // return True myCircularQueue.deQueue(); // return True myCircularQueue.enQueue(4); // return True myCircularQueue.Rear(); // return 4 Constraints: 1 <= k <= 1000 0 <= value <= 1000 At most 3000 calls will be made to enQueue, deQueue, Front, Rear, isEmpty, and isFull.

Topics: Array, Linked List, Design, Queue

Problem #2: Design a Stack With Increment Operation

Design a stack that supports increment operations on its elements. Implement the CustomStack class: CustomStack(int maxSize) Initializes the object with maxSize which is the maximum number of elements in the stack. void push(int x) Adds x to the top of the stack if the stack has not reached the maxSize. int pop() Pops and returns the top of the stack or -1 if the stack is empty. void inc(int k, int val) Increments the bottom k elements of the stack by val. If there are less than k elements in the stack, increment all the elements in the stack. Example 1: Input ["CustomStack","push","push","pop","push","push","push","increment","increment","pop","pop","pop","pop"] [[3],[1],[2],[],[2],[3],[4],[5,100],[2,100],[],[],[],[]] Output [null,null,null,2,null,null,null,null,null,103,202,201,-1] Explanation CustomStack stk = new CustomStack(3); // Stack is Empty [] stk.push(1); // stack becomes [1] stk.push(2); // stack becomes [1, 2] stk.pop(); // return 2 --> Return top of the stack 2, stack becomes [1] stk.push(2); // stack becomes [1, 2] stk.push(3); // stack becomes [1, 2, 3] stk.push(4); // stack still [1, 2, 3], Do not add another elements as size is 4 stk.increment(5, 100); // stack becomes [101, 102, 103] stk.increment(2, 100); // stack becomes [201, 202, 103] stk.pop(); // return 103 --> Return top of the stack 103, stack becomes [201, 202] stk.pop(); // return 202 --> Return top of the stack 202, stack becomes [201] stk.pop(); // return 201 --> Return top of the stack 201, stack becomes [] stk.pop(); // return -1 --> Stack is empty return -1. Constraints: 1 <= maxSize, x, k <= 1000 0 <= val <= 100 At most 1000 calls will be made to each method of increment, push and pop each separately.

Topics: Array, Stack, Design

Problem #3: 4Sum

Given an array nums of n integers, return an array of all the unique quadruplets [nums[a], nums[b], nums[c], nums[d]] such that: 0 <= a, b, c, d < n a, b, c, and d are distinct. nums[a] + nums[b] + nums[c] + nums[d] == target You may return the answer in any order. Example 1: Input: nums = [1,0,-1,0,-2,2], target = 0 Output: [[-2,-1,1,2],[-2,0,0,2],[-1,0,0,1]] Example 2: Input: nums = [2,2,2,2,2], target = 8 Output: [[2,2,2,2]] Constraints: 1 <= nums.length <= 200 -109 <= nums[i] <= 109 -109 <= target <= 109

Topics: Array, Two Pointers, Sorting

Problem #4: 3Sum

Given an integer array nums, return all the triplets [nums[i], nums[j], nums[k]] such that i != j, i != k, and j != k, and nums[i] + nums[j] + nums[k] == 0. Notice that the solution set must not contain duplicate triplets. Example 1: Input: nums = [-1,0,1,2,-1,-4] Output: [[-1,-1,2],[-1,0,1]] Explanation: nums[0] + nums[1] + nums[2] = (-1) + 0 + 1 = 0. nums[1] + nums[2] + nums[4] = 0 + 1 + (-1) = 0. nums[0] + nums[3] + nums[4] = (-1) + 2 + (-1) = 0. The distinct triplets are [-1,0,1] and [-1,-1,2]. Notice that the order of the output and the order of the triplets does not matter. Example 2: Input: nums = [0,1,1] Output: [] Explanation: The only possible triplet does not sum up to 0. Example 3: Input: nums = [0,0,0] Output: [[0,0,0]] Explanation: The only possible triplet sums up to 0. Constraints: 3 <= nums.length <= 3000 -105 <= nums[i] <= 105

Topics: Array, Two Pointers, Sorting

Problem #5: Number of Islands

Given an m x n 2D binary grid grid which represents a map of '1's (land) and '0's (water), return the number of islands. An island is surrounded by water and is formed by connecting adjacent lands horizontally or vertically. You may assume all four edges of the grid are all surrounded by water. Example 1: Input: grid = [ ["1","1","1","1","0"], ["1","1","0","1","0"], ["1","1","0","0","0"], ["0","0","0","0","0"] ] Output: 1 Example 2: Input: grid = [ ["1","1","0","0","0"], ["1","1","0","0","0"], ["0","0","1","0","0"], ["0","0","0","1","1"] ] Output: 3 Constraints: m == grid.length n == grid[i].length 1 <= m, n <= 300 grid[i][j] is '0' or '1'.

Topics: Array, Depth-First Search, Breadth-First Search, Union Find, Matrix

Problem #6: Reaching Points

Given four integers sx, sy, tx, and ty, return true if it is possible to convert the point (sx, sy) to the point (tx, ty) through some operations, or false otherwise. The allowed operation on some point (x, y) is to convert it to either (x, x + y) or (x + y, y). Example 1: Input: sx = 1, sy = 1, tx = 3, ty = 5 Output: true Explanation: One series of moves that transforms the starting point to the target is: (1, 1) -> (1, 2) (1, 2) -> (3, 2) (3, 2) -> (3, 5) Example 2: Input: sx = 1, sy = 1, tx = 2, ty = 2 Output: false Example 3: Input: sx = 1, sy = 1, tx = 1, ty = 1 Output: true Constraints: 1 <= sx, sy, tx, ty <= 109

Topics: Math