I knew this problem, which helped, but I still fumbled explaining the bitmask approach cleanly at first.
Model each word as a 26-bit mask and use backtracking with pruning to explore subsets, or use DP over masks to find the maximum total length. Emphasize the trade-offs between exponential brute force and optimized bitmask DP, and discuss how to handle duplicates and overlapping letters.
Pro tip: Mention that you can preprocess to remove words with duplicate letters and deduplicate masks, which drastically reduces the search space. Also, note that the problem is NP-hard, so for large inputs you might need heuristics or approximations.
Ask about input size, character set (e.g., lowercase English), and whether words can have repeated letters. Clarify if the subset must be non-empty and if there are memory/time limits.
Convert each word to a 26-bit integer where each bit indicates presence of a letter. Filter out words with duplicate letters and deduplicate masks to reduce problem size.
For small N (≤20), use backtracking with pruning or meet-in-the-middle. For larger N, use DP over masks (if N small) or branch-and-bound. Discuss complexity and trade-offs.
Write code for the chosen approach, using bitwise operations for fast conflict checks. Prune branches when the current mask conflicts with a word or when the remaining words cannot improve the best.
Test with edge cases (empty list, all words conflicting, etc.). Analyze time/space complexity and discuss potential improvements or alternative approaches.
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