International Morse Code defines a standard encoding where each letter is mapped to a series of dots and dashes, as follows: “a” maps to “.-“, “b” maps to “-…”, “c” maps to “-.-.”, and so on. For convenience, the full table for the 26 letters of the English alphabet is given below:

1	[".-","-...","-.-.","-..",".","..-.","--.","....","..",".---","-.-",".-..","--","-.","---",".--.","--.-",".-.","...","-","..-","...-",".--","-..-","-.--","--.."]

[".-","-...","-.-.","-..",".","..-.","--.","....","..",".---","-.-",".-..","--","-.","---",".--.","--.-",".-.","...","-","..-","...-",".--","-..-","-.--","--.."]

Now, given a list of words, each word can be written as a concatenation of the Morse code of each letter. For example, “cba” can be written as “-.-..–…”, (which is the concatenation “-.-.” + “-…” + “.-“). We’ll call such a concatenation, the transformation of a word.

Return the number of different transformations among all words we have.

Example:
Input: words = [“gin”, “zen”, “gig”, “msg”]
Output: 2
Explanation:
The transformation of each word is:
“gin” – “–…-.”
“zen” – “–…-.”
“gig” – “–…–.”
“msg” – “–…–.”

There are 2 different transformations, “–…-.” and “–…–.”.
Note:

The length of words will be at most 100.
Each words[i] will have length in range [1, 12].
words[i] will only consist of lowercase letters.

C++ Unique Morse Code Words

We can use a unordered_set (hash set) to store the unique morse code words. We need to construct the morse code words by lookup up the morse table.

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class Solution {
public:
    int uniqueMorseRepresentations(vector<string>& words) {
        vector<string> morseTable = {".-","-...","-.-.","-..",".","..-.","--.","....","..",".---","-.-",".-..","--","-.","---",".--.","--.-",".-.","...","-","..-","...-",".--","-..-","-.--","--.."};
        unordered_set<string> outcome;
        for (const auto &s: words) {
            string r = "";
            for (const auto &c: s) {
                r += morseTable[c - 97];
            }
            outcome.insert(r);
        }
        return outcome.size();
    }
};

class Solution {
public:
    int uniqueMorseRepresentations(vector<string>& words) {
        vector<string> morseTable = {".-","-...","-.-.","-..",".","..-.","--.","....","..",".---","-.-",".-..","--","-.","---",".--.","--.-",".-.","...","-","..-","...-",".--","-..-","-.--","--.."};
        unordered_set<string> outcome;
        for (const auto &s: words) {
            string r = "";
            for (const auto &c: s) {
                r += morseTable[c - 97];
            }
            outcome.insert(r);
        }
        return outcome.size();
    }
};

The above C++ morse code algorithm took 8ms to complete on the leetcode online judge. The space complexity is O(N) where N is the number of strings. and the time complexity is O(NMM) where the N is the number of string and M is the average length of the string, as the string concatenation could be very time costly.

Java Unique Morse Code Words

In Java, we can speed up the string concatenation (during the process of constructing the morse code words) by using a StringBuilder – which does not copy the entire string when concatenating the string.

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class Solution {
    public int uniqueMorseRepresentations(String[] words) {
        String[] morseTable = new String[] {".-","-...","-.-.","-..",".","..-.","--.","....","..",".---","-.-",".-..","--","-.","---",".--.","--.-",".-.","...","-","..-","...-",".--","-..-","-.--","--.."};
        Set<String> outcome = new HashSet<>();
        for (String s: words) {
            StringBuilder sb = new StringBuilder();
            for (int i = 0; i < s.length(); ++ i) {
                sb.append(morseTable[s.charAt(i) - 97]);
            }
            outcome.add(sb.toString());
        }
        return outcome.size();
    }
}

class Solution {
    public int uniqueMorseRepresentations(String[] words) {
        String[] morseTable = new String[] {".-","-...","-.-.","-..",".","..-.","--.","....","..",".---","-.-",".-..","--","-.","---",".--.","--.-",".-.","...","-","..-","...-",".--","-..-","-.--","--.."};
        Set<String> outcome = new HashSet<>();
        for (String s: words) {
            StringBuilder sb = new StringBuilder();
            for (int i = 0; i < s.length(); ++ i) {
                sb.append(morseTable[s.charAt(i) - 97]);
            }
            outcome.add(sb.toString());
        }
        return outcome.size();
    }
}

The above Java morse code took 4ms to complete on leetcode online judge. The space complexity is O(N) where N is the number of string and the time complexity is O(NM) where N is the number of string and M is the average length of the string.

–EOF (The Ultimate Computing & Technology Blog) —