The approach came to me pretty quickly: sort the letters of each word in the list to build a lookup map, then do the same for each token in the scrambled input and check against the map.
Clarify the problem constraints (e.g., case sensitivity, duplicates, word list size) and then propose an efficient solution using a hash map from sorted word signatures to original words. For each scrambled token, sort its characters to form a key and look up the corresponding word, concatenating results to decode the message.
Pro tip: Mention that you would preprocess the word list into a hash map for O(1) lookups, and discuss trade-offs like memory usage versus speed, and how to handle multiple words with the same anagram (e.g., store a list or pick the first).
Ask about input format, case sensitivity, duplicate words, and whether the scrambled tokens are guaranteed to have a match. Confirm output format (e.g., space-separated words).
Propose building a hash map where keys are sorted character strings (anagram signatures) and values are the corresponding valid words. Discuss handling collisions (multiple words with same signature).
Split the message into tokens, sort each token's characters to form a key, and look up the key in the hash map. If found, replace the token with the mapped word; otherwise, handle the error (e.g., leave as is or raise exception).
Explain time complexity: O(N * K log K) for preprocessing (N words of length K) and O(M * L log L) for decoding (M tokens of length L). Space complexity O(N * K). Discuss alternatives like counting character frequencies to avoid sorting.
Walk through a small example, test edge cases (empty message, no match, duplicate anagrams), and confirm the solution works as expected.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.