The 60-second answer
Use a hash map plus doubly linked list so lookup, insert, delete, and recency updates are constant time. Target O(1) average per operation and O(capacity) space.
Build the answer in this order
1
Clarify constraints
Use a hash map plus doubly linked list so lookup, insert, delete, and recency updates are constant time.
2
Choose the approach
Target O(1) average per operation and O(capacity) space.
3
Prove complexity
Call out edge cases such as capacity zero, updating existing keys, deleting head/tail, and repeated access.
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
- Define invariants for sentinel nodes and map/list consistency before coding mutations.
- If concurrency is introduced, discuss lock granularity and why naive locking can serialize the cache.
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.