Rippling Mobile Engineer Coding Questions

To improve performance and reduce latency, Rippling needs a mechanism to cache frequently accessed API responses while ensuring the least recently used data is evicted when the cache reaches capacity.
Implement a class LRUCache with the following methods:
- LRUCache(int capacity) initializes the LRU cache with a positive size capacity.
- int get(int key) returns the value of the key if the key exists, otherwise returns -1.
- void put(int key, int value) updates or inserts the value if the key is not already present. When the cache reaches its capacity, it should invalidate the least recently used item before inserting a new item.Example 1:
Input: LRUCache cache = new LRUCache(2); cache.put(1, 1); cache.put(2, 2); cache.get(1); // returns 1
Output: 1
Explanation: The cache has the key 1.Example 2:
Input: cache.put(3, 3); // evicts key 2
Output: cache.get(2); // returns -1 (not found)Constraints:
- capacity will be a positive integer.
- The total number of calls to get and put will not exceed 10^4.

To enhance the user experience, Rippling needs an efficient method to fetch and display notifications for users in real-time, balancing between performance and battery usage.
Given a string notifications representing the incoming notifications and an integer k, return the maximum number of distinct notifications that can be obtained in any sliding window of size k.Example 1:
Input: notifications = "abcabcbb", k = 3
Output: 3
Explanation: The distinct notifications in the window can be abc.Example 2:
Input: notifications = "aabbcc", k = 2
Output: 2
Explanation: The distinct notifications in the window can be ab, bc, or ca.Constraints:
- 1 <= notifications.length <= 10^5
- 1 <= k <= 10^5
- notifications consists of lowercase English letters.