Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Meta data engineer interview with a graph/social network traversal problem. Pretty standard algorithmic question but the specifics tripped me up a bit in how to handle deduplication cleanly.

Questions Asked (1)

Given a follow graph represented as a dictionary (e.g. {A:[B,C], B:[C,D], C:[E]}), find all accounts that a user's followees follow, excluding anyone the user already follows themselves. No duplicates, order doesn't matter.

Algorithms & Data Structures

Author's notes

My first instinct was to just flatten everything and filter, which works but I kept second-guessing myself on the dedup step.

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AI HintsAI Generated

Suggested Approach

Clarify the input format and edge cases, then propose a solution using a set to collect followees-of-followees and subtract the user's direct follows. Discuss time and space complexity, and consider if the graph is large or if the user has many followees.

Pro tip: Mention that you would handle the case where the user is not in the graph or has no followees, and that you'd use a set for O(1) lookups and deduplication. Also, note that the order doesn't matter, so a set is ideal.

1. Clarify the problem

Ask clarifying questions: Is the graph directed? Can there be cycles? Should we include the user themselves if they appear? What if the user has no followees?

2. Outline the approach

Explain that you will iterate over the user's followees, then for each followee, iterate over their followees. Collect all into a set, then remove the user's direct followees and the user themselves if present.

3. Walk through an example

Use the given example to demonstrate: for user A, followees are B and C. B follows C and D; C follows E. Collect {C, D, E}, remove direct follows {B, C}, result {D, E}.

4. Analyze complexity

State that time complexity is O(F * G) where F is number of followees and G is average number of followees per followee, but more precisely O(total edges from followees). Space complexity is O(R) where R is the result size.

5. Discuss edge cases and optimizations

Mention handling missing keys, empty followees, and potential for large graphs. Suggest using a set for deduplication and O(1) membership checks.

Key Points to Mention

Use a set to collect results and ensure no duplicates.
Subtract the user's direct followees from the collected set.
Handle cases where the user or followees are not in the graph.
Time complexity: O(sum of out-degrees of followees).
Space complexity: O(number of unique followees-of-followees).
Order doesn't matter, so returning a set or list is fine.

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