codelucas/cracking-the-da-vinci-code-with-google-interview-problems-and-nlp-in-python

Combines backtracking permutation generation with a trie-based prefix validation against the Google 10K most common English words to efficiently enumerate valid anagrams from character sequences. Rather than computing all 17! permutations, the algorithm prunes the search space by rejecting branches that don't form valid English word prefixes or complete words at space boundaries, reducing practical runtime from theoretical 355 trillion operations to ~140 seconds. Includes deduplication heuristics and word-boundary constraints to surface meaningful phrase candidates from anagram puzzles.

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