My first instinct was pure recursion and I coded it up fine for small inputs, but I hadn't thought about the overlapping subproblems until I was almost done.
Use backtracking to explore all possible segmentations of the string, checking at each step if the current prefix is a valid word in the dictionary. To optimize, precompute the dictionary as a hash set for O(1) lookups and consider memoization to avoid redundant computations on overlapping subproblems.
Pro tip: Discuss the trade-offs between backtracking with memoization and dynamic programming, and mention how to handle large inputs by pruning invalid paths early. Also, clarify with the interviewer whether the output should be sorted or if duplicates are possible.
Confirm input constraints, output format, and whether words can be reused. Discuss edge cases like empty string, empty dictionary, and strings with no valid segmentation.
Decide between backtracking, dynamic programming, or a trie-based approach. Explain why backtracking with memoization is suitable for generating all valid sentences.
Write code that recursively tries all possible prefixes, checks if they are in the dictionary, and builds sentences. Use memoization to cache results for substrings to avoid recomputation.
Discuss time and space complexity, and suggest optimizations like using a trie for prefix matching or pruning branches when no words match.
Walk through examples, including edge cases, to ensure correctness. Verify that all valid sentences are generated without duplicates.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.