The 60-second answer
Use a size-k max heap for streaming-friendly selection, or quickselect for average linear time. Target O(n log k) time and O(k) space with the heap approach.
Build the answer in this order
1
Clarify constraints
Use a size-k max heap for streaming-friendly selection, or quickselect for average linear time.
2
Choose the approach
Target O(n log k) time and O(k) space with the heap approach.
3
Prove complexity
Call out edge cases such as k=0, k>=n, equal distances, and avoiding unnecessary square roots.
4
Test edge cases
Explain the invariant before coding, then dry-run a small case and state time/space complexity.
A useful interview mental model
This is the shape of a strong answer—not a script to memorize.
01Clarify
02Approach
03Implement
04Test
05Complexity
Senior-level signal
- Choose heap vs quickselect based on streaming requirements and worst-case guarantees, not habit.
- Use squared distance to avoid floating-point work and explain tie behavior if deterministic output is needed.
What the interviewer is really testing
Problem decomposition, correctness, data-structure choice, complexity reasoning, and clean implementation under pressure.
Likely follow-up questions
Can you improve the time or space complexity?
Which edge case is most likely to break this solution?
How would you test this under interview time pressure?
Common weak-answer patterns
- Starting to code before constraints are clear.
- Giving complexity without explaining why it is correct.
- Skipping adversarial and boundary cases.