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Airbnb·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026Remote

Summary

Airbnb coding screen for a software engineer role. One question, but it had enough layers to keep me busy for the whole session. Sorting, priority logic, and partial refunds all stacked on top of each other.

Questions Asked (1)

Q1

Given a list of payments (each with a method like CREDIT, CREDIT_CARD, or PAYPAL, a date, and an amount), a refund total to disburse, and any previously issued refunds against those payments, return the list of refund records that fully consume the refund amount. Rules: exhaust a single payment before moving to the next, prefer methods in order CREDIT then CREDIT_CARD then PAYPAL, and within the same method prefer more recent payments first.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I got the basic structure pretty fast, sort by method priority then by date descending, then greedily walk the list.

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AI HintsAI Generated

Suggested Approach

Clarify the input/output format and edge cases, then outline a greedy algorithm that sorts payments by method priority and date descending, tracks remaining refundable amount per payment, and iterates to allocate the refund. Discuss time/space complexity and potential trade-offs with alternative approaches.

Pro tip: Mention that you would confirm whether the refund amount can be partially fulfilled and how to handle rounding or currency precision, as these details often matter in production payment systems.

1. Clarify requirements and edge cases

Ask about input format, whether refunds can be partial, how to handle insufficient total refundable amount, and any constraints on payment methods or dates.

2. Design the algorithm

Propose sorting payments by method priority (CREDIT, CREDIT_CARD, PAYPAL) and within each method by date descending. Then iterate through sorted payments, allocating refunds until the total is met.

3. Handle data structures and tracking

Use a map or list to track remaining refundable amount per payment after subtracting previous refunds. Accumulate refund records as you allocate.

4. Analyze complexity and trade-offs

Discuss O(n log n) time due to sorting and O(n) space. Mention that if payments are already grouped or sorted, a linear scan could suffice.

5. Test with examples

Walk through a simple example to verify correctness, including cases where refunds span multiple payments and where previous refunds reduce available amounts.

Key Points to Mention

  • Greedy approach: exhaust one payment before moving to the next
  • Sorting criteria: method priority then date descending
  • Tracking remaining refundable amount per payment after previous refunds
  • Edge cases: insufficient total refundable amount, zero refund, exact match
  • Time and space complexity: O(n log n) time, O(n) space
  • Potential for partial refunds and how to represent them in output

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