The classic random pointer version I'd seen before, so my first instinct was to reach for a hashmap mapping old nodes to new ones.
Use a hash map to map each original node to its copy, then set the next, random, and extra pointers of the copies using the map. This achieves O(n) time and O(n) space. Alternatively, for O(1) space, interleave copies with originals and adjust pointers, then separate the lists.
Pro tip: Discuss the trade-off between the hash map approach (simpler, O(n) space) and the interleaving approach (O(1) space but trickier). Mention that the interleaving method is more impressive and shows deeper understanding, but be prepared to explain both.
Confirm that each node has three pointers (next, random, extra) and that the deep copy must be a completely new list with no shared nodes. Ask about constraints like list size and whether modifying the original list is allowed.
Decide between hash map (O(n) space) and interleaving (O(1) space). Explain the trade-offs and pick one based on constraints or interviewer preference.
For hash map: traverse the list, create copies, and store mapping. Then traverse again to set next, random, and extra pointers using the map. For interleaving: insert copies after originals, set pointers, then separate.
Consider empty list, single node, and pointers that are null. Ensure the copy's pointers correctly reflect nulls and that no cycles are accidentally created.
State time and space complexity: both approaches are O(n) time; hash map uses O(n) space, interleaving uses O(1) extra space (excluding output).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.