My first instinct was to just filter and sort, which works fine.
Clarify the problem constraints (e.g., input size, whether the list is static or dynamic, and if the output should be sorted). Then propose a solution using a trie for efficient prefix lookup, followed by sorting the results, or simply filter and sort if the list is small. Discuss trade-offs between preprocessing and query time.
Pro tip: Mention that if the list is static and many queries will be made, building a trie with sorted children allows retrieving results in lexicographical order without an extra sort. This shows you think about scalability and real-world usage.
Ask about input size, whether the word list is static or dynamic, expected number of queries, and if the output must be sorted. This determines the optimal approach.
Propose iterating through the list, checking if each word starts with the prefix, collecting matches, and then sorting them. Mention time complexity O(N * L + M log M) where N is list size, L is prefix length, and M is number of matches.
Explain how to build a trie from the word list, then traverse to the node corresponding to the prefix. Collect all words in the subtree, which are already in lexicographical order if children are stored in sorted order.
Compare the simple approach (O(N) per query) with the trie approach (O(L) to find prefix node + O(M) to collect results). Discuss preprocessing time and memory overhead of the trie.
Consider empty prefix, no matches, prefix longer than any word, and case sensitivity. Ensure the solution returns an empty list when appropriate.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.