← Anthropic Interview Insights
My first instinct was to just try all subsets and track which characters were used, and that's basically the right move since the input is capped at 16 strings.
Model each string as a 26-bit mask and use backtracking to explore subsets, pruning when the combined mask has overlapping bits. Track the maximum total length of valid concatenations. Optimize by pre-filtering strings with duplicate characters and sorting to improve pruning.
Pro tip: Mention that the problem is NP-hard (related to set packing), so exponential time is expected; focus on pruning and bitmask efficiency. Also, clarify that the order of concatenation doesn't matter for uniqueness, so you're essentially selecting a set of strings with disjoint character sets.
Confirm that the concatenation order doesn't affect character uniqueness and that each string can be used at most once. Check for edge cases like empty strings or strings with duplicate characters.
Convert each string to a 26-bit integer mask representing its unique characters. Discard any string that has duplicate characters internally, as it can never be part of a valid concatenation.
Use DFS/backtracking to try including or excluding each string. Maintain a combined mask and total length; only include a string if its mask doesn't overlap with the combined mask.
Sort strings by length descending to find good solutions early, and prune branches where the remaining potential length cannot exceed the current maximum. Use memoization on the combined mask if needed.
Explain that the worst-case time is O(2^n) due to subset exploration, but bitmask operations and pruning make it efficient for typical inputs. Space is O(n) for recursion depth.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.