The aa case is what gets you if you're not paying attention.
Model each string as a bitmask of its letters, discarding any string with duplicate letters. Then use dynamic programming over subsets of the 26-letter alphabet to find the maximum total length of a set of strings with disjoint masks. Alternatively, use backtracking with pruning or meet-in-the-middle for efficiency.
Pro tip: Clarify constraints first (e.g., array size, string length, alphabet size) to choose the right approach; for Meta interviews, discussing trade-offs between brute force and optimized DP shows depth.
Ask about input size, character set (e.g., lowercase English letters), and whether empty strings or duplicates are allowed. This determines the feasible algorithmic complexity.
For each string, compute a bitmask of its characters. If any character repeats within the string, discard it because it can never be part of a valid subset.
Use DP over masks: dp[mask] = maximum total length achievable using a subset of strings whose combined mask is exactly 'mask'. For each valid string mask, update dp[new_mask] = max(dp[new_mask], dp[mask] + len) if mask & string_mask == 0.
If the number of strings is large, consider meet-in-the-middle or branch-and-bound. For 26 letters, DP over 2^26 states is too large, so use a hash map for reachable states or iterate only over valid combinations.
Discuss time and space complexity (e.g., O(2^26) worst-case but often much less). Walk through a small example to verify correctness and edge cases like no valid subset.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.