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Pinterest·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Pinterest SWE interview with two coding problems back to back. The questions were more design-flavored than pure leetcode grind, which I wasn't totally expecting.

Questions Asked (2)

Q1

Implement a LineReader class with a nextLine() method that reads complete lines from a chunked stream source, where each chunk can contain zero or more newlines and the chunks must be processed with O(L_max) additional memory.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

This one took me a minute to get comfortable with.

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AI HintsAI Generated

Suggested Approach

Clarify the interface and constraints, then design a stateful LineReader that buffers only the current partial line and scans each chunk for newlines. Emphasize that memory is bounded by the longest line, not the chunk size, and handle edge cases like empty chunks, trailing newlines, and EOF.

Pro tip: Explicitly state that you will not buffer entire chunks; instead, you process each chunk incrementally and only keep the current line fragment. This shows you understand the memory constraint and can avoid a common pitfall.

1. Clarify requirements and interface

Ask about the chunk source (e.g., iterator, callback), whether nextLine() blocks, and how EOF is signaled. Confirm that memory should be O(L_max) where L_max is the longest line length.

2. Design stateful reader

Maintain a buffer for the current partial line and an index into the current chunk. On nextLine(), scan the chunk for newline characters, appending to the buffer until a newline is found or the chunk ends.

3. Handle chunk boundaries and newlines

When a chunk ends without a newline, keep the partial line in the buffer and fetch the next chunk. When a newline is found, return the accumulated line and reset the buffer.

4. Manage EOF and edge cases

At EOF, return any remaining buffered line (if non-empty) or null/empty to signal end. Handle empty chunks, consecutive newlines (empty lines), and lines split across multiple chunks.

5. Analyze complexity and trade-offs

Explain that time is O(total characters) and memory is O(L_max). Discuss alternative designs (e.g., using a queue of chunks) and why they might violate the memory constraint.

Key Points to Mention

  • Memory bound: only store the current partial line, not entire chunks.
  • Incremental scanning: process each chunk character by character or using indexOf for newlines.
  • State management: track current chunk and position across nextLine() calls.
  • Edge cases: empty chunks, multiple newlines, line spanning chunks, EOF with/without trailing newline.
  • Time complexity: O(total input size) with no re-scanning of characters.
  • Trade-offs: simplicity vs. performance (e.g., using StringBuilder vs. char array).

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

Q2

Given a list of money transfer transactions between people, compute a list of payback transfers so that every person's net balance returns to zero. You don't need to minimize the number of payback transactions.

Algorithms & Data Structures
Author's notes

The 'you don't need to minimize' part is a gift and I almost ignored it.

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AI HintsAI Generated

Suggested Approach

First, compute each person's net balance by summing all incoming and outgoing transactions. Then, separate people into debtors (negative balance) and creditors (positive balance), and greedily match debtors with creditors to settle debts until all balances are zero.

Pro tip: Clarify that the problem doesn't require minimizing transactions, so a simple greedy approach is acceptable. Mention that if minimization were required, it becomes NP-hard, showing awareness of complexity.

1. Compute Net Balances

Iterate through all transactions and update a map of person to net balance. For each transaction (A pays B amount X), subtract X from A's balance and add X to B's balance.

2. Separate Debtors and Creditors

Create two lists: one for people with negative balances (debtors) and one for people with positive balances (creditors). Ignore anyone with zero balance.

3. Greedy Matching

Use two pointers or a queue to match debtors and creditors. For each debtor, transfer the minimum of their debt and the creditor's credit, update both balances, and record the transaction.

4. Handle Remaining Balances

Continue matching until all balances are zero. If a debtor or creditor still has a non-zero balance after a match, move to the next person on the opposite list.

5. Return Payback Transfers

Collect all recorded transactions from the matching process and return them as the list of payback transfers.

Key Points to Mention

  • Net balance calculation: sum of incoming minus outgoing for each person.
  • Data structures: use a hash map to store net balances, and lists/queues for debtors and creditors.
  • Greedy algorithm: match largest debt with largest credit to settle efficiently, though not required to minimize transactions.
  • Time complexity: O(N + M) where N is number of people and M is number of transactions, assuming constant time per match.
  • Edge cases: no transactions, all balances zero, single person, floating point precision if amounts are not integers.
  • Alternative approaches: discuss that minimizing transactions is NP-hard, but not needed here.

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