← Anthropic Interview Insights
The naive approach of running a DFS per word is fine for small word lists but the problem explicitly says the list can be huge, up to 30k words.
Use a Trie to store the word list for efficient prefix pruning, then perform DFS from each cell in the grid, marking cells as visited to avoid reuse. Collect found words in a set to eliminate duplicates, and finally sort the results lexicographically.
Pro tip: Mention that you can optimize by removing words from the Trie as they are found to avoid redundant searches, and discuss trade-offs between DFS and BFS or using a Trie vs. a hash set.
Restate the problem to ensure understanding: grid dimensions, adjacency rules, no cell reuse, and output requirements. Ask about edge cases like empty grid or empty word list.
Decide on a Trie for the word list to enable prefix pruning, and a visited matrix or set to track cells in the current path. Consider using a set for results to handle duplicates.
Outline a DFS approach: for each cell, if its character matches a child of the current Trie node, recurse to adjacent unvisited cells. If a word end is reached, add to results.
Discuss time complexity: O(m*n*4^L) worst-case, where L is max word length, but Trie pruning reduces practical time. Space complexity: O(total characters in words) for Trie plus recursion stack.
Mention optimizations like removing found words from Trie, early termination if no words remain, and handling duplicates by using a set. Also address sorting the final list.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.