## Round 1 - Coding ## Problem You are given a list of employee work sessions as `[employee_id, start_time, end_time]` tuples. Extend your Level 1 implementation to support: 1. `get_overlapping_sessions(emp_id)` — return all sessions for the employee that overlap with at least one other session of the same employee. 2. `get_total_hours(emp_id, date)` — return total worked hours on a given date, merging any overlapping intervals before summing. ```python class WorkHoursRegister: def add_session(self, emp_id: str, start: int, end: int) -> None: ... def get_overlapping_sessions(self, emp_id: str) -> list[tuple[int,int]]: ... def get_total_hours(self, emp_id: str, date: str) -> float: ... ``` ``` Input: add_session("E1", 9, 11) add_session("E1", 10, 13) add_session("E1", 15, 17) get_total_hours("E1", "2024-01-01") -> 6.0 get_overlapping_sessions("E1") -> [(9,11),(10,13)] ``` ## Follow-ups 1. How would you handle sessions spanning midnight (e.g., 23:00 to 01:00 next day)? 2. What's the time complexity of your merge step, and can you do better than O(n log n)? 3. If two employees share a shift (same start/end), how would you detect scheduling conflicts across the whole team? 4. How would you persist this register so it survives a service restart?

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Working Hours Register Program - Level 2: Time Interval Merging and Overlap Detection

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Round 1 - Coding Problem You are given a list of employee work sessions as [employee_id, start_time, end_time] tuples. Extend your Level 1 implementation to support: get_overlapping_sessions(emp_id) — return all sessions for the employee that overlap with at least one other session of the same employee. get_total_hours(emp_id, date) — return total worked hours on a given date, merging any overlapping intervals before summing. Follow-ups How would you handle sessions spanning midnight (e.g., 23:0…

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Working Hours Register Program - Level 2: Time Interval Merging and Overlap Detection

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