The parsing part was fine, I sorted by timestamp per plate and computed speed as 36000 divided by the time delta.
First, clarify the input format and constraints, then design a solution that groups log entries by vehicle plate and sorts timestamps to compute segment speeds. Use a hash map to track per-vehicle segment speeds and apply the speeding criteria, ensuring O(n log n) time due to sorting.
Pro tip: Mention edge cases like multiple vehicles with the same plate, missing timestamps, or non-uniform segment lengths, and discuss how to handle them gracefully. Also, consider if the log entries are already sorted by time to optimize.
Ask about the log entry format, segment lengths, time units, and whether entries are sorted. Confirm the exact speeding criteria and output format.
Use a hash map to group entries by plate, storing a list of (timestamp, segment_id) pairs. Sort each list by timestamp to compute speeds between consecutive entries.
For each vehicle, iterate through sorted entries, calculate speed for each segment, and track if any segment >=130 km/h or count segments >=120 km/h. Mark vehicle as speeding if criteria met.
Consider missing data, duplicate timestamps, and non-uniform segment lengths. If input is large, discuss memory and time trade-offs, and potential streaming approach.
Walk through a small example to verify logic, and mention unit tests for boundary conditions like exactly 130 km/h or exactly two segments at 120 km/h.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.