Count Server Replacements

You have n servers with IDs "s1", "s2",..., "sn". The system processes a sequence of log entries, where each entry is formatted as:
"<server_id> <status>", where status is either "success" or "error"
For each server, track its consecutive errors:
If a server records three "error" logs in a row, it is considered faulty and is replaced. The replacement server keeps the same ID.
After a replacement, that server's consecutive error count resets to 0.
A "success" log also resets that server's consecutive error count to 0.
Your task is to determine the total number of server replacements that occur while processing all log entries.

Function
countServerReplacements(n: int, logs: String[]) → int

Examples
Example 1
n = 2
logs = ["s1 error", "s1 error", "s2 error", "s1 error", "s1 error", "s2 success"]
return = 1

This is a hash-table simulation, one pass over the logs. Keep a map from server ID to its current consecutive error count. For each log, split on the space. If the status is "error", increment that server's count. When it hits 3, add one to the replacement total and reset that count to 0. If the status is "success", reset the count to 0. Walk through Example 1 and you get exactly one replacement: s1 hits three errors at its fourth log, and s2 never gets there. The pitfalls are a shared counter across servers, forgetting to reset after a replacement (so the fourth error counts as another), and not resetting on success. Time is O(m) for m logs, space is O(n). Ignore n for the logic, since the map handles unseen IDs fine. StealthCoder is the safety net on the live OA if the loop logic slips under pressure, but the solution is short enough to write cold.

If you see this problem in your OA tomorrow, the play is to recognize the pattern in 30 seconds. StealthCoder buys you that recognition.