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My first instinct was to just iterate once and handle priority inline, which got messy fast.
Clarify the input format and constraints, then propose an efficient algorithm that separates priority and non-priority passengers while preserving arrival order. Implement the solution with careful handling of capacity and edge cases, and analyze time and space complexity.
Pro tip: Mention that you can achieve O(n) time by processing the input once and using a queue for each group, which is optimal since you must examine every passenger. This shows you think about efficiency and practical implementation.
Ask about input format (e.g., list of passengers with priority flag and arrival order), output format, and any constraints on capacity or passenger count. Confirm that priority passengers board first in arrival order, then non-priority fill remaining spots.
Propose using two queues (or lists) to separate priority and non-priority passengers while preserving arrival order. Then dequeue priority passengers until capacity is reached, followed by non-priority passengers until capacity is full.
Write code that iterates through passengers, enqueues them into the appropriate queue, then builds the boarded list by dequeuing from priority first, then non-priority, up to capacity. The remaining passengers in both queues are left behind.
Consider cases like capacity 0, all priority, all non-priority, more passengers than capacity, and exactly capacity. Verify that arrival order is preserved within each group.
State that time complexity is O(n) and space complexity is O(n) in the worst case. Discuss potential optimizations like early termination if capacity is reached, or using a single pass with counters if only counts are needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.