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Robinhood·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Robinhood software engineer coding round, one problem the whole time. The question looked deceptively clean on the surface but the referral chain propagation part tripped me up more than I expected.

Questions Asked (1)

Q1

Design and implement a referral leaderboard: given two arrays where rh_users[i] referred new_users[i], a referrer gets credit for every downstream user in their chain (not just direct referrals). Return the top 3 users with at least one referral, sorted by count descending then name ascending, in the format '<user> <count>'.

Algorithms & Data StructuresSystem Design
Author's notes

The tricky part wasn't the sorting, it was figuring out how to propagate credit up the chain.

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AI HintsAI Generated

Suggested Approach

Model the referral relationships as a directed graph and compute the size of each user's downstream subtree using DFS or BFS. Then filter users with at least one referral, sort by count descending and name ascending, and return the top 3 in the required format.

Pro tip: Clarify edge cases upfront: cycles, multiple roots, and users with zero referrals. Also discuss time/space complexity and potential optimizations like memoization or iterative traversal to avoid recursion limits.

1. Understand the problem and clarify requirements

Confirm that a referrer gets credit for all downstream users, not just direct referrals. Ask about input size, potential cycles, and whether the graph is a forest (each new user has exactly one referrer).

2. Build the referral graph

Create an adjacency list mapping each referrer to their direct referrals. Identify all unique users and determine root nodes (users who are not referred by anyone).

3. Compute downstream counts

For each user, traverse their subtree (using DFS or BFS) to count all descendants. Use memoization to avoid recomputing counts for shared subtrees, or process nodes in reverse topological order if the graph is a DAG.

4. Filter, sort, and format results

Exclude users with zero referrals. Sort the remaining users by count descending, then by name ascending. Take the top 3 and format each as '<user> <count>'.

5. Analyze complexity and edge cases

Discuss time and space complexity (e.g., O(N) for traversal with memoization). Address edge cases: cycles, multiple roots, fewer than 3 users with referrals, and large inputs.

Key Points to Mention

  • Graph representation: adjacency list for referrals.
  • Traversal algorithm: DFS or BFS to count all downstream users.
  • Memoization or dynamic programming to avoid redundant computations.
  • Sorting criteria: count descending, then name ascending.
  • Handling cycles and ensuring no infinite loops.
  • Time and space complexity analysis.

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