Find kth largest element in interval list
Last updated: May 23, 2026
Quick Overview
Given a interval list, find the minimum cost efficiently using Topological Sort.
Rippling
May 23, 2026128
10
1,067 solved
Given a interval list, find the minimum cost efficiently using Topological Sort.
Rippling 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
- 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?
- What if the input doesn't fit in memory?
- Can you optimize the space complexity of your solution?
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Problem Analysis
The problem requires us to find the minimum cost efficiently using Topological Sort on an interval list. The given intervals can be represented as a directed graph where each interval can be viewed as...
Approach
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Graph Representation: Represent the intervals as a directed graph, where each interval is a node. Create directed edges based on the order of intervals.
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Topological Sort: Use Kahn's al...
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