Introduction

In this blog post, we'll share the most commonly asked coding interview questions at Splunk. 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: Longest Increasing Subsequence

Given an integer array nums, return the length of the longest strictly increasing subsequence. Example 1: Input: nums = [10,9,2,5,3,7,101,18] Output: 4 Explanation: The longest increasing subsequence is [2,3,7,101], therefore the length is 4. Example 2: Input: nums = [0,1,0,3,2,3] Output: 4 Example 3: Input: nums = [7,7,7,7,7,7,7] Output: 1 Constraints: 1 <= nums.length <= 2500 -104 <= nums[i] <= 104 Follow up: Can you come up with an algorithm that runs in O(n log(n)) time complexity?

Topics: Array, Binary Search, Dynamic Programming

Problem #2: Find Median from Data Stream

The median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value, and the median is the mean of the two middle values. For example, for arr = [2,3,4], the median is 3. For example, for arr = [2,3], the median is (2 + 3) / 2 = 2.5. Implement the MedianFinder class: MedianFinder() initializes the MedianFinder object. void addNum(int num) adds the integer num from the data stream to the data structure. double findMedian() returns the median of all elements so far. Answers within 10-5 of the actual answer will be accepted. Example 1: Input ["MedianFinder", "addNum", "addNum", "findMedian", "addNum", "findMedian"] [[], [1], [2], [], [3], []] Output [null, null, null, 1.5, null, 2.0] Explanation MedianFinder medianFinder = new MedianFinder(); medianFinder.addNum(1); // arr = [1] medianFinder.addNum(2); // arr = [1, 2] medianFinder.findMedian(); // return 1.5 (i.e., (1 + 2) / 2) medianFinder.addNum(3); // arr[1, 2, 3] medianFinder.findMedian(); // return 2.0 Constraints: -105 <= num <= 105 There will be at least one element in the data structure before calling findMedian. At most 5 * 104 calls will be made to addNum and findMedian. Follow up: If all integer numbers from the stream are in the range [0, 100], how would you optimize your solution? If 99% of all integer numbers from the stream are in the range [0, 100], how would you optimize your solution?

Topics: Two Pointers, Design, Sorting, Heap (Priority Queue), Data Stream

Problem #3: Find First and Last Position of Element in Sorted Array

Given an array of integers nums sorted in non-decreasing order, find the starting and ending position of a given target value. If target is not found in the array, return [-1, -1]. You must write an algorithm with O(log n) runtime complexity. Example 1: Input: nums = [5,7,7,8,8,10], target = 8 Output: [3,4] Example 2: Input: nums = [5,7,7,8,8,10], target = 6 Output: [-1,-1] Example 3: Input: nums = [], target = 0 Output: [-1,-1] Constraints: 0 <= nums.length <= 105 -109 <= nums[i] <= 109 nums is a non-decreasing array. -109 <= target <= 109

Topics: Array, Binary Search

Problem #4: Minimum Height Trees

A tree is an undirected graph in which any two vertices are connected by exactly one path. In other words, any connected graph without simple cycles is a tree. Given a tree of n nodes labelled from 0 to n - 1, and an array of n - 1 edges where edges[i] = [ai, bi] indicates that there is an undirected edge between the two nodes ai and bi in the tree, you can choose any node of the tree as the root. When you select a node x as the root, the result tree has height h. Among all possible rooted trees, those with minimum height (i.e. min(h)) are called minimum height trees (MHTs). Return a list of all MHTs' root labels. You can return the answer in any order. The height of a rooted tree is the number of edges on the longest downward path between the root and a leaf. Example 1: Input: n = 4, edges = [[1,0],[1,2],[1,3]] Output: [1] Explanation: As shown, the height of the tree is 1 when the root is the node with label 1 which is the only MHT. Example 2: Input: n = 6, edges = [[3,0],[3,1],[3,2],[3,4],[5,4]] Output: [3,4] Constraints: 1 <= n <= 2 * 104 edges.length == n - 1 0 <= ai, bi < n ai != bi All the pairs (ai, bi) are distinct. The given input is guaranteed to be a tree and there will be no repeated edges.

Topics: Depth-First Search, Breadth-First Search, Graph, Topological Sort