Openai·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

Jun 2026

Summary

Interviewed for a SWE role at OpenAI and got a coding problem around credit systems, the kind of thing that sounds straightforward until you actually start modeling it out.

Questions Asked (1)

Given a sequence of events representing credit issuance and usage (where credits can expire or have usage constraints), write a function that computes the user's remaining credit pool and total available credits.

Algorithms & Data StructuresSystem Design

Author's notes

I went straight to a linear scan approach, tracking each credit batch with its expiry and remaining balance.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the event types and credit rules (e.g., expiration, usage constraints) and the expected output format. Then design a data structure to track credit batches with their remaining amounts and expiration times, processing events in order. Finally, implement the function, test with edge cases, and analyze time/space complexity.

Pro tip: Demonstrate production-level thinking by discussing how to handle out-of-order events, idempotency, and concurrency, and mention that in a real system you'd use a database with transactions to ensure consistency.

1. Clarify requirements and constraints

Ask about event types, credit expiration rules, usage constraints (e.g., FIFO, LIFO, priority), and the exact output format. Confirm assumptions about event ordering and data types.

2. Design data structures and algorithm

Choose a data structure to track credit batches (e.g., queue for FIFO, priority queue for expiration). Outline the algorithm: process events sequentially, update batches on issuance, deduct on usage, and remove expired credits.

3. Implement the function

Write clean code with helper functions for adding credits, consuming credits, and expiring credits. Handle edge cases like insufficient credits or expired batches.

4. Test and validate

Walk through examples, including edge cases (e.g., usage exceeding available credits, credits expiring before use). Verify the remaining pool and total available credits.

5. Analyze complexity and discuss optimizations

State time and space complexity. Discuss potential optimizations (e.g., lazy expiration, batch processing) and trade-offs.

Key Points to Mention

Event types: credit issuance, usage, expiration, and possibly adjustments.
Credit consumption strategy: FIFO, LIFO, or earliest-expiry-first.
Handling expiration: check and remove expired credits before each operation.
Data structures: queue, priority queue, or balanced tree for efficient expiration.
Edge cases: insufficient credits, multiple expirations, zero-amount events.
Time and space complexity: O(n log n) with priority queue, O(n) with queue if events sorted by expiration.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.