Question Details
Problem
Design a PermanentStack class that behaves like a standard stack but never truly destroys data. When you pop() an element, it is moved to an internal "archive" rather than discarded. All previously popped elements must remain retrievable.
python
class PermanentStack:
def push(self, val: int) -> None: ...
def pop(self) -> int: ... # removes from active, archives it
def peek(self) -> int: ... # top of active stack
def restore(self) -> int: ... # moves most-recently archived back to active
def get_archive(self) -> list[int]: ... # all archived values, oldest first
Example:
push(1), push(2), push(3)
pop() -> 3 (archive: [3])
pop() -> 2 (archive: [3, 2])
restore() -> 2 (active top: 2, archive: [3])
get_archive() -> [3]
Follow-ups
- What if restore() must reinstate elements in LIFO order from the archive?
- How would you implement undo_all() to move every archived element back in original push order?
- What are the time and space complexities of each operation?
- How would you persist this structure to disk so it survives a process restart?
Full Details
Problem
Design a PermanentStack class that behaves like a standard stack but never truly destroys data. When you pop() an element, it is moved to an internal "archive" rather than discarded. All previously popped elements must remain retrievable.
python
class PermanentStack:
def push(self, val: int) -> None: ...
def pop(self) -> int: ... # removes from active, archives it
def peek(self) -> int: ... # top of active stack
def restore(self) -> int: ... # moves most-recently archived back to active
def get_archive(self) -> list[int]: ... # all archived values, oldest first
Example:
push(1), push(2), push(3)
pop() -> 3 (archive: [3])
pop() -> 2 (archive: [3, 2])
restore() -> 2 (active top: 2, archive: [3])
get_archive() -> [3]
Follow-ups
- What if restore() must reinstate elements in LIFO order from the archive?
- How would you implement undo_all() to move every archived element back in original push order?
- What are the time and space complexities of each operation?
- How would you persist this structure to disk so it survives a process restart?
About This Question
This is a reported interview question from a affirm interview during the phone round.
It covers the following topics: Coding, Ood, Onsite, Phone, Stack .
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This question was reported by a candidate who interviewed at Affirm. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.
Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Affirm are the higher-signal extractions to take from this report.
For broader preparation context, the Affirm interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.
How To Practice This Type of Question
Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.
Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Affirm reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Affirm Round
Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.
The single most predictive failure mode in Affirm reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.