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Stripe·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Stripe SWE interview with a straightforward coding problem around transaction processing. Nothing too wild, just needed to think through the data carefully.

Questions Asked (1)

Q1

Given a list of transactions where each entry has a sender, a receiver, and an amount, compute the final balance for every user. Only output users whose balance ends up non-zero.

Algorithms & Data Structures
Author's notes

Pretty much a hash map problem once you see it clearly.

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AI HintsAI Generated

Suggested Approach

Use a hash map to accumulate net balances: for each transaction, subtract the amount from the sender's balance and add it to the receiver's. After processing all transactions, filter the map to include only users with non-zero balances. This approach is O(n) time and O(u) space, where n is the number of transactions and u is the number of unique users.

Pro tip: Clarify edge cases upfront, such as self-transactions (sender equals receiver), zero-amount transactions, and whether balances should be integers or floating-point. Mentioning these shows attention to detail and prevents incorrect assumptions.

1. Clarify requirements and edge cases

Ask about input format, data types (e.g., integer vs. decimal amounts), and edge cases like self-transactions, zero amounts, and duplicate users. Confirm that only non-zero balances should be output.

2. Choose data structures

Select a hash map (dictionary) to store each user's net balance, allowing O(1) average-time updates. Consider whether to use a language-specific structure like HashMap in Java or dict in Python.

3. Process transactions

Iterate through the list of transactions. For each, subtract the amount from the sender's balance and add it to the receiver's balance, creating entries if they don't exist. Handle self-transactions by skipping or netting to zero.

4. Filter and output results

After processing, iterate through the hash map and collect users whose balance is not zero. Return the result in the required format (e.g., a map or list of tuples).

5. Analyze complexity and test

State the time complexity O(n) and space complexity O(u). Walk through a small example to verify correctness, including edge cases like self-transactions and zero amounts.

Key Points to Mention

  • Use a hash map for O(1) average-time updates to balances.
  • Time complexity: O(n) where n is the number of transactions; space complexity: O(u) where u is the number of unique users.
  • Handle edge cases: self-transactions (sender == receiver), zero-amount transactions, and users with zero net balance after all transactions.
  • Consider data types: use integers for exact arithmetic or decimals with proper rounding if amounts are fractional.
  • Filter out zero balances at the end to meet the output requirement.
  • Test with a small example to demonstrate correctness and discuss potential pitfalls.

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