← Instacart Interview Insights
I spent the first few minutes just restating the problem back, which was probably annoying.
Clarify the existing priority rules and data structures, then model wheelchair passengers as consuming both a dedicated spot and general capacity. Process passengers in priority order, attempting to board each; if a wheelchair passenger cannot fit due to either constraint, skip them and continue. Return the boarded and left-behind lists.
Pro tip: Explicitly state your assumptions about priority ordering and capacity constraints, and discuss how you'd handle edge cases like multiple wheelchairs or zero general capacity. This shows attention to detail and real-world robustness.
Review the current priority boarding logic, data structures, and how general capacity is tracked. Identify where wheelchair support needs to be integrated.
Each wheelchair passenger requires one of two dedicated spots and also consumes general capacity equal to their size. Ensure both constraints are checked atomically.
Iterate through passengers in the given priority order. For each, check if they can board: for wheelchair users, verify both a dedicated spot and enough general capacity; for others, only general capacity.
If a passenger cannot board, add them to the left-behind list and continue to the next passenger without stopping. This ensures higher-priority passengers who can't fit don't block lower-priority ones.
After processing all passengers, return the boarded list (in boarding order) and the left-behind list (in original priority order).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.