Greedy on interval list
Last updated: December 12, 2025
Quick Overview
Given a list of intervals, each defined by a start and end time, implement a function that selects the maximum number of non-overlapping intervals that can be attended. The function should take a list of intervals as input and return the maximum count of non-overlapping intervals as output.
Instacart
December 12, 202558
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1,674 solved
Given a list of intervals, each defined by a start and end time, implement a function that selects the maximum number of non-overlapping intervals that can be attended. The function should take a list of intervals as input and return the maximum count of non-overlapping intervals as output.
Instacart 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
- What is the worst-case input for your solution?
- Can you solve this iteratively instead of recursively (or vice versa)?
- What happens if the input contains duplicates?
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Problem Analysis
This problem can be categorized as an 'Interval Scheduling Maximization' problem, which is commonly solved using a greedy algorithm. The goal is to select the maximum number of non-overlapping interva...
Approach
- Sort the Intervals: Begin by sorting the list of intervals based on their end time. For example, if we have intervals
[(1, 3), (2, 4), (3, 5), (6, 8)], sorting them will give us `[(1, 3), (2,...
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