SoFi·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Coding screen for a software engineer role at SoFi. One algorithmic problem, reasonably well-scoped, but the edge cases were trickier than they looked at first glance.

Questions Asked (1)

You're given a flat list of strings that encodes records in repeating triplets (id, name, tag). Find the second most frequent tag. If all tags share the same frequency, return 'notag'. If there's a tie for second place, return whichever tag appeared first in the input. Solution should run in O(n).

Algorithms & Data Structures

Author's notes

I got the basic frequency counting part pretty fast, but the tie-breaking rule tripped me up.

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AI HintsAI Generated

Suggested Approach

First, clarify that the input is a flat list where every three consecutive elements form a record (id, name, tag), so tags are at indices 2, 5, 8, etc. Then, in a single pass, count tag frequencies while recording the first occurrence index of each tag. Finally, determine the highest and second highest frequencies, handling ties by first occurrence, and return 'notag' if all frequencies are equal.

Pro tip: Mention that you can track the top two frequencies and their earliest tags in one pass without sorting, which keeps the solution O(n) and avoids extra space beyond the hash map. Also, explicitly handle edge cases like fewer than two distinct tags or all tags having the same frequency.

1. Clarify input structure and constraints

Confirm that the list length is a multiple of 3 and that tags are at indices 2, 5, 8, etc. Ask about edge cases: empty list, single record, or all tags identical.

2. Design the counting strategy

Use a hash map to count tag frequencies and another map (or store in the same map) to record the first occurrence index of each tag. Iterate through the list in steps of 3 to process only tags.

3. Determine the top two frequencies

While counting, maintain the highest and second highest frequencies and the earliest tag for each. Alternatively, after counting, find the maximum frequency, then find the maximum frequency less than that, considering first occurrence for ties.

4. Handle ties and special cases

If all tags have the same frequency, return 'notag'. If there is a tie for second place, return the tag that appeared first in the input. Ensure that if there is only one distinct tag, return 'notag'.

5. Analyze complexity and test

State that the solution runs in O(n) time and O(k) space where k is the number of distinct tags. Walk through a small example to verify correctness, including tie-breaking.

Key Points to Mention

Single-pass O(n) solution using a hash map for frequency counting and first occurrence tracking.
Handling of ties for second place by comparing first occurrence indices.
Edge case: all tags have the same frequency → return 'notag'.
Edge case: fewer than two distinct tags → return 'notag'.
Space complexity O(k) where k is the number of distinct tags, which is acceptable.
Avoid sorting to maintain O(n) time; instead, track top two frequencies during iteration.

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