The core trick is that users appear lazily so you can't preallocate anything.
Use a hash map to track each user's connection count and a set to track unique connections, updating both on connect and disconnect events. After processing all events, count users whose connection count exceeds n.
Pro tip: Clarify edge cases upfront: what if a disconnect occurs for a non-existent connection? Should duplicate connects be ignored? Handling these gracefully shows attention to detail.
Ask about input format, duplicate events, disconnecting non-existent connections, and whether n is inclusive. Confirm expected output.
Use a hash map to store each user's connection count and a set to store unique undirected connections (e.g., sorted tuple or frozenset).
For each event, update the connection set and adjust counts for both users. On connect, add if new; on disconnect, remove if exists.
Iterate through the connection count map and count users with count > n. Return the count.
State time O(E) and space O(U + C). Discuss potential optimizations for large-scale streams, like incremental counting.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.