Introduction

In this blog post, we'll share the most commonly asked coding interview questions at Okta. 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: Insert Delete GetRandom O(1)

Implement the RandomizedSet class: RandomizedSet() Initializes the RandomizedSet object. bool insert(int val) Inserts an item val into the set if not present. Returns true if the item was not present, false otherwise. bool remove(int val) Removes an item val from the set if present. Returns true if the item was present, false otherwise. int getRandom() Returns a random element from the current set of elements (it's guaranteed that at least one element exists when this method is called). Each element must have the same probability of being returned. You must implement the functions of the class such that each function works in average O(1) time complexity. Example 1: Input ["RandomizedSet", "insert", "remove", "insert", "getRandom", "remove", "insert", "getRandom"] [[], [1], [2], [2], [], [1], [2], []] Output [null, true, false, true, 2, true, false, 2] Explanation RandomizedSet randomizedSet = new RandomizedSet(); randomizedSet.insert(1); // Inserts 1 to the set. Returns true as 1 was inserted successfully. randomizedSet.remove(2); // Returns false as 2 does not exist in the set. randomizedSet.insert(2); // Inserts 2 to the set, returns true. Set now contains [1,2]. randomizedSet.getRandom(); // getRandom() should return either 1 or 2 randomly. randomizedSet.remove(1); // Removes 1 from the set, returns true. Set now contains [2]. randomizedSet.insert(2); // 2 was already in the set, so return false. randomizedSet.getRandom(); // Since 2 is the only number in the set, getRandom() will always return 2. Constraints: -231 <= val <= 231 - 1 At most 2 * 105 calls will be made to insert, remove, and getRandom. There will be at least one element in the data structure when getRandom is called.

Topics: Array, Hash Table, Math, Design, Randomized

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