Count longest subsequence in interval list
Last updated: February 18, 2026
Quick Overview
Given a list of intervals, your task is to count the number of longest subsequences that can be formed where each interval in the subsequence does not overlap with the others. An interval is represented as a pair of integers [start, end], and you should return the count of such longest non-overlapping subsequences.
Waymo
February 18, 202625
5
143 solved
Given a list of intervals, your task is to count the number of longest subsequences that can be formed where each interval in the subsequence does not overlap with the others. An interval is represented as a pair of integers [start, end], and you should return the count of such longest non-overlapping subsequences.
Coding interviews at Waymo focus on problem-solving approach as much as the final solution. The interviewer wants to see you break down the problem, consider edge cases, and optimize iteratively. Communication throughout the process is key.
What the Interviewer Expects
- Recognize the underlying problem pattern (sliding window, two pointers, BFS/DFS, etc.)
- Discuss multiple approaches and trade-offs before coding
- Implement an optimal solution with clean, production-quality code
- Handle all edge cases including boundary conditions and invalid input
- Optimize both time and space complexity with clear justification
- Test your solution systematically with well-chosen examples
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 test this solution thoroughly?
- Can you optimize the space complexity of your solution?
- Can you solve this in a single pass?
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Problem Analysis
To solve the problem of counting the longest non-overlapping subsequences of intervals, we can identify that it exhibits properties of dynamic programming combined with sorting. The main challenge is ...
Approach
- Sort the intervals: First, sort the list of intervals by their end times. This allows us to consider the earliest finishing intervals first, which helps in maximizing the number of intervals we...
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