Find minimum cost in array
Last updated: May 13, 2026
Quick Overview
Given a array, find the kth largest element efficiently using Sliding Window.
Jane Street
May 13, 2026118
9
3,580 solved
Given a array, find the kth largest element efficiently using Sliding Window.
Coding interviews at Jane Street 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
- 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
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 solve this in a single pass?
- What if the input doesn't fit in memory?
- Can you optimize the space complexity of your solution?
Sharpen Your Skills on Codemia
Practice similar problems with our interactive workspace, get AI feedback, and track your progress.
Practice DSA ProblemsSample Answer
Problem Analysis
To tackle the problem of finding the kth largest element in an array using the Sliding Window technique, we need to consider how we can efficiently manage a dynamic set of elements. The sliding window...
Approach
- Initialize a max-heap: We will use a max-heap to keep track of the largest elements. The max-heap will store elements in a way that we can easily access the kth largest element.
- **Iterate t...
Submit Your Answer
