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My first instinct was to just do DFS for each word separately.
Build a trie from the dictionary words to enable efficient prefix pruning during a single DFS traversal of the grid. For each cell, perform DFS while simultaneously walking the trie, marking cells as visited to avoid reuse, and collecting any complete words found. This avoids redundant searches for each word and handles a large dictionary efficiently.
Pro tip: Mention that you can optimize memory and speed by storing words at trie nodes and pruning nodes after they are found if duplicates are not needed, and discuss trade-offs between trie and hash set approaches.
Ask about grid size, dictionary size, whether words can be reused, and if output should be unique. This helps choose the right data structures and algorithms.
Insert all dictionary words into a trie, storing the complete word at terminal nodes. This allows prefix-based pruning during search.
For each cell, start a DFS that moves in four directions, checking if the current path is a prefix in the trie. Mark cells as visited and unmark on backtrack.
When a terminal node is reached, add the word to the result set. Optionally, remove the word from the trie to avoid duplicates and prune further.
Discuss time complexity O(m*n*4^L) worst-case but pruned by trie, and space O(total characters in dictionary). Mention possible optimizations like early termination.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.