I went straight to a Trie and tracked how many words pass through each node as I insert.
Use a trie to efficiently find the shortest unique prefix for each word. Insert all words into the trie, tracking the count of words passing through each node. Then, for each word, traverse the trie until reaching a node with count 1, which marks the shortest unique prefix.
Pro tip: Clarify edge cases upfront, such as duplicate words (which have no unique prefix) and empty strings. Mention that a trie uses O(total characters) space and time, which is optimal for this problem.
Confirm that the output should preserve input order and that if no unique prefix exists (e.g., duplicate words), return the full word or handle as specified. Discuss constraints like word length and list size.
Select a trie (prefix tree) because it naturally groups words by common prefixes and allows efficient prefix searches. Alternatively, consider sorting but note that it disrupts original order.
Insert each word into the trie, incrementing a counter at each node to track how many words share that prefix. This count helps identify when a prefix becomes unique.
For each word, traverse the trie from the root, following its characters until the node's count is 1. The path taken up to that node is the shortest unique prefix.
State time complexity O(N * L) where N is number of words and L is average length, and space O(N * L). Walk through examples, including duplicates and words that are prefixes of others.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.