Anthropic·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

Jun 2026Remote

Summary

Anthropic software engineer screen with a ledger simulation problem. The kind of question that looks manageable until you realize the expiry-ordering constraint basically forces you toward a heap, and if you miss that, your solution falls apart on the efficiency requirement.

Questions Asked (1)

Design and implement a prepaid credit ledger that supports adding time-limited grants, spending credits (always consuming the soonest-to-expire credits first), and querying the current balance, where expired grants are dropped before any spend or balance check.

Algorithms & Data StructuresData ModelingSystem Design

Author's notes

My first instinct was a plain sorted list and I started coding that up before catching myself.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases, then propose a data structure that efficiently supports the three operations: adding grants, spending credits (soonest-to-expire first), and querying balance with expiration cleanup. Implement the solution with a priority queue or sorted structure, ensuring that expired grants are removed before any spend or balance check, and analyze the time complexity of each operation.

Pro tip: Demonstrate foresight by discussing how to handle concurrent access and persistence, and mention that using a min-heap keyed by expiration time gives O(log n) insertion and O(1) amortized expiration cleanup, which is optimal for this use case.

1. Clarify Requirements and Edge Cases

Ask questions to confirm assumptions: Are grants added with an expiration timestamp? Should spending consume partial grants? What happens if spending exceeds available credits? How to handle concurrent operations?

2. Choose Data Structures

Select a min-heap (priority queue) ordered by expiration time to efficiently retrieve the soonest-to-expire grant. Optionally, maintain a separate total balance for O(1) queries, updating it on add, spend, and expiration.

3. Design Operations

For addGrant: insert into heap and update balance. For spend: first remove expired grants from heap top, then consume credits from the heap in order, updating balance. For getBalance: remove expired grants, then return balance.

4. Analyze Complexity and Optimize

Discuss time complexity: addGrant O(log n), spend O(k log n) where k is number of grants consumed, getBalance O(m log n) where m is number of expired grants removed. Mention that amortized cost of expiration cleanup is O(log n) per grant.

5. Address Scalability and Edge Cases

Consider concurrency (locks or atomic operations), persistence (database or append-only log), and edge cases like spending more than available, grants with same expiration, and clock skew.

Key Points to Mention

Use a min-heap keyed by expiration timestamp to efficiently retrieve the soonest-to-expire grant.
Maintain a running total balance to allow O(1) balance queries after expiration cleanup.
Expired grants are lazily removed: only when they reach the top of the heap during spend or balance check.
Spending consumes credits from the heap in order, potentially partially consuming a grant.
Time complexity: O(log n) for addGrant, O(k log n) for spend (k grants consumed), O(m log n) for getBalance (m expired grants removed).
Discuss concurrency control (e.g., mutex) and persistence (e.g., database transactions) for production readiness.

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