Microsoft Mobile Engineer Interview Questions

In Microsoft Teams, quick access to frequently used API responses is critical for a smooth user experience. Implement an LRU Cache to store API responses efficiently.Function Signature:
python
def __init__(self, capacity: int) -> None:
def get(self, key: int) -> int:
def put(self, key: int, value: int) -> None:
Example 1:
Input: cache = LRUCache(2), cache.put(1, 1), cache.put(2, 2)
Output: cache.get(1)
Explanation: Returns 1, indicating that the key 1 was found.Example 2:
Input: cache.put(3, 3)
Output: cache.get(2)
Explanation: Returns -1, indicating that the key 2 was removed from the cache.Constraints:
- 1 <= capacity <= 3000
- 0 <= key <= 10^4
- 0 <= value <= 10^4

Microsoft's mobile applications require efficient background task management to optimize battery usage while maintaining performance. Implement a function that uses a sliding window approach to calculate the maximum number of tasks that can run concurrently without exceeding the device's battery capacity.Function Signature:
python
def max_concurrent_tasks(battery_capacity: int, tasks: List[int]) -> int:
Example 1:
Input: battery_capacity = 10, tasks = [2, 1, 3, 1, 2]
Output: 3
Explanation: The maximum tasks that can run concurrently with total battery consumption within capacity is 3 (tasks [2, 1, 1]).Example 2:
Input: battery_capacity = 5, tasks = [2, 4, 3, 1]
Output: 1
Explanation: The maximum tasks that can run concurrently is 1 (task [1]).Constraints:
- 1 <= battery_capacity <= 100
- 1 <= tasks.length <= 1000
- 1 <= tasks[i] <= 10

To help users manage their tasks in Microsoft To-Do, you need to design a background task scheduler that handles task reminders efficiently, even when the app is not active. Implement a class that schedules tasks to send notifications based on user-configured times.Class Signature:
python
class TaskScheduler:
def __init__(self):
def schedule_task(self, task: Task, time: str) -> None:
def execute_tasks(self) -> None:
Example 1:
Input: task_scheduler = TaskScheduler(), task_scheduler.schedule_task(task, '2023-12-01T10:00:00')
Output: None
Explanation: The task will be scheduled to remind the user at the specified time.Example 2:
Input: task_scheduler.execute_tasks()
Output: ['Task Reminder']
Explanation: Notifies the user about scheduled tasks due to be reminded.Constraints:
- 1 <= tasks.count <= 100
- 1 <= task.title.length <= 100

As OneNote is often used in offline scenarios, designing a sync engine that efficiently reconciles data between local storage and the server is crucial. Design a class that can sync notes created offline with a remote database when a user's internet connection is restored.Class Signature:
python
class SyncEngine:
def __init__(self, local_db: Database, remote_db: Database):
def create_note(self, note: Note) -> None:
def sync(self) -> None:
Example 1:
Input: sync_engine = SyncEngine(local_db, remote_db), sync_engine.create_note(note)
Output: None
Explanation: A note is created offline, awaiting sync.Example 2:
Input: sync_engine.sync()
Output: True
Explanation: All offline notes are successfully synced to the remote database.Constraints:
- 1 <= notes.count <= 1000
- 1 <= note.content.length <= 10^4