Count minimum cost in interval list
Last updated: February 12, 2026
Quick Overview
Count the number of longest subsequence in the given interval list.
PlanetScale
Coding & Algorithms
Machine Learning Engineer
PlanetScale
February 12, 2026Machine Learning Engineer
Technical Screen
Coding & Algorithms
Hard
10
8
3,992 solved
Count the number of longest subsequence in the given interval list.
PlanetScale uses this problem in the Technical Screen to evaluate your algorithmic thinking. They expect you to discuss multiple approaches, analyze trade-offs between them, and implement the optimal solution with clean, readable code.
What the Interviewer Expects
- Quickly identify the optimal approach and its theoretical basis
- Handle complex algorithm design with multiple interacting components
- Write concise, elegant code under time pressure
- Prove correctness of your approach and discuss alternative solutions
- Optimize beyond the obvious: discuss constant factor improvements
- Address follow-up variations and explain how the solution generalizes
Key Topics to Cover
Dynamic programming and memoization
Edge cases and input validation
Binary search and divide and conquer
Tree structures and recursion
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
- Can you optimize the space complexity of your solution?
- What if the input doesn't fit in memory?
- How would your solution change if the input was sorted?
- How would you modify your solution to handle streaming input?
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Practice DSA ProblemsSample Answer
Problem Analysis
This problem involves finding the longest subsequence in a list of intervals, which suggests that we need to compare overlapping intervals. The two-pointer technique is a natural fit here, as it allow...
Approach
- Sort the Intervals: Start by sorting the intervals based on their start times. If two intervals have the same start time, sort them by their end times.
- Initialize Variables: Use a variab...
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