Merge overlapping time intervals for payment scheduling
Last updated: August 6, 2025
Quick Overview
Given a list of payment processing windows (start_time, end_time) for different merchants, merge overlapping windows to find the consolidated processing schedule. Handle timezone-aware timestamps and edge cases.
Affirm
August 6, 20256
3
4,668 solved
Given a list of payment processing windows (start_time, end_time) for different merchants, merge overlapping windows to find the consolidated processing schedule. Handle timezone-aware timestamps and edge cases.
This classic interval merging problem is framed in Affirm's payment scheduling context. It tests fundamental algorithm skills and appears in phone screens to assess baseline coding ability.
What the Interviewer Expects
- Sort intervals by start time as the first step
- Iterate and merge overlapping intervals efficiently
- Handle edge cases: adjacent intervals, single interval, empty list
- Write clean Python with proper variable naming
- Analyze time and space complexity
Key Topics to Cover
How to Approach This
- Clarify input constraints and edge cases before writing code.
- Walk through your approach verbally and confirm with the interviewer before coding.
- Start with a brute force solution, then optimize. Mention time and space complexity.
- Test your solution with examples, including edge cases like empty input or duplicates.
- Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
- How would you find the gaps between merged intervals?
- How would you handle intervals arriving in a stream rather than all at once?
- How would you weight-merge intervals where each has a priority?
- What if you needed to find the maximum number of overlapping intervals at any point?
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Problem Analysis
This problem requires merging overlapping intervals, which is a classic interval problem. The primary pattern here is sorting combined with a linear scan, which allows us to efficiently merge overlapp...
Approach
- Sort the Intervals: Start by sorting the list of intervals based on their
start_time. For example, given the intervals[(1, 3), (2, 4), (5, 7), (6, 8)], sorting will yield `[(1, 3), (2, 4),...
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