I started with the naive approach of searching each word independently using DFS and backtracking.
Build a trie from the list of words to efficiently guide the search, then perform DFS from each cell, exploring adjacent cells while marking visited cells to avoid reuse. Prune the search when the current path is not a prefix of any word in the trie, and collect words when a complete word is found.
Pro tip: Mention that you can optimize by removing words from the trie as they are found to avoid duplicate searches, and discuss the trade-off between time and space complexity.
Ask about grid size, word list size, word length, and whether words can be formed multiple times. Confirm that each cell can be used at most once per word.
Explain that a trie (prefix tree) is ideal for storing the word list, enabling efficient prefix checks during DFS and pruning branches early.
For each cell, start a DFS that explores all four directions, marking cells as visited and unmarking on backtrack. At each step, check if the current path corresponds to a node in the trie.
When a trie node marks the end of a word, add it to the result set. Optionally, remove the word from the trie to avoid finding it again from other starting cells.
Discuss time complexity: O(N * M * 4^L) worst-case without trie, but with trie it's O(N * M * 3^L) where L is max word length. Space complexity: O(total characters in words) for trie plus recursion stack.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.