Looked easy and kind of is, but I spent a minute overthinking whether to use a set or a map.
Clarify the problem and edge cases, then propose a solution using a hash set to store the Morse representations of each word. Iterate through the array, convert each word to its Morse code, and add it to the set. Finally, return the size of the set as the count of distinct representations.
Pro tip: Mention that the Morse code mapping can be stored in an array of 26 strings for O(1) lookup per character, and emphasize that the solution is O(N*L) time and O(N*L) space where N is the number of words and L is the average word length.
Restate the problem in your own words and confirm with the interviewer. Ask clarifying questions about input constraints, such as the maximum number of words and word length, and whether the Morse code mapping is provided or standard.
Decide on using a hash set to track distinct Morse representations. Explain that you will convert each word to its Morse code by concatenating the codes for each letter, then insert into the set.
Write code to iterate through the array, convert each word to Morse, and add to the set. Use a precomputed array for the Morse code mapping to ensure efficient lookups.
State the time complexity: O(N * L) where N is the number of words and L is the average length, as each character is processed once. Space complexity is O(N * L) for storing the Morse strings in the set.
Walk through a few test cases, including edge cases like empty array, single word, and words that produce the same Morse code. Verify that the set correctly captures distinct representations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.