Meta·Software Engineer·Technical Phone Screen·Senior

Senior

Jun 2026

Summary

Meta SWE interview that went deep on object-oriented design plus algorithmic complexity. The problem looked like a simple banking CRUD task at first glance but the top-k follow-up is where things got interesting.

Questions Asked (1)

Design and implement an in-memory banking system supporting account creation with an optional initial balance, deposits, and transfers between accounts. Transfers should be rejected if the source account has insufficient funds. For each account, track the total cumulative amount debited outward, then implement a function that returns the top N accounts by outgoing total, breaking ties by account ID ascending, formatted as 'outgoingAmount:accountId'.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

I went straight to a hash map keyed by account ID storing balance and cumulative outgoing amount, which was fine.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design the data structures and algorithms for account management and top-N retrieval. Implement the core operations with careful attention to edge cases and efficiency, and finally analyze trade-offs and potential optimizations.

Pro tip: Demonstrate awareness of real-world banking concerns like atomicity and concurrency, and discuss how the top-N function could be optimized for frequent calls (e.g., using a heap or maintaining a sorted structure).

1. Clarify Requirements and Constraints

Ask about expected scale (number of accounts, operations per second), concurrency requirements, and whether the top-N function is called frequently. Confirm tie-breaking rules and output format.

2. Design Data Structures

Choose appropriate structures: a hash map for account lookup (ID to account object), and for each account store balance and cumulative outgoing amount. Consider additional structures for efficient top-N retrieval.

3. Implement Core Operations

Implement createAccount, deposit, and transfer with proper validation (e.g., sufficient funds). Ensure outgoing totals are updated correctly on transfers. Handle edge cases like zero or negative amounts.

4. Implement Top-N Function

Design an algorithm to return top N accounts by outgoing total, sorted descending, with ties broken by account ID ascending. Use a min-heap of size N for O(M log N) time, where M is number of accounts, or sort all accounts if M is small.

5. Analyze Trade-offs and Optimizations

Discuss time/space complexity of operations, potential concurrency issues (e.g., locking for transfers), and optimizations like caching top-N results or using a balanced tree for dynamic ordering.

Key Points to Mention

Use a hash map for O(1) account lookup by ID.
Maintain cumulative outgoing amount per account, updated only on successful transfers.
For top-N, use a min-heap of size N to achieve O(M log N) time, or sort if M is small.
Tie-breaking: when outgoing amounts are equal, sort by account ID ascending.
Concurrency: consider thread-safety for transfers (e.g., locking accounts in a consistent order to avoid deadlocks).
Edge cases: insufficient funds, non-existent accounts, zero/negative amounts, and N larger than number of accounts.

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