Unraveling Uniqueness and Anagram Mysteries with JavaScript Sets

Welcome to our focused exploration of JavaScript's Set and its remarkable applications in solving algorithmic challenges. In this lesson, "Unraveling Uniqueness and Anagram Mysteries with JavaScript Sets", we'll explore how this powerful data structure can be used to approach and solve certain types of problems commonly encountered in technical interviews.

Picture this: you're given a vast list of words, and you must identify the final word that stands proudly solitary — the last word that is not repeated. Imagine sorting through a database of unique identifiers and finding one identifier towards the end of the list that is unlike any others.

The straightforward approach would be to examine each word in reverse, comparing it to every other word for uniqueness. This brute-force method would result in poor time complexity, $O(n^2)$, which is less than ideal for large datasets.

We can use two Set instances: wordsSet to maintain unique words and duplicatesSet to keep track of duplicate words. By the end, we can remove all duplicated words from wordsSet to achieve our goal. Here is how to use Set to solve the problem:

Create a Set instance to store unique words:

let wordsSet = new Set();

Initialize another Set to monitor duplicates:

let duplicatesSet = new Set();

Iterate the word array, filling wordsSet and duplicatesSet:

for (let word of words) {
    if (wordsSet.has(word)) {
        duplicatesSet.add(word);
    } else {
        wordsSet.add(word);
    }
}

Use a loop to remove all duplicated words from wordsSet:

duplicatesSet.forEach(word => wordsSet.delete(word));

Now, wordsSet only contains unique words. Find the last unique word by iterating through the original word list from the end:

let lastUniqueWord = "";
for(let i = words.length - 1; i >= 0; i--){
    if(wordsSet.has(words[i])){
        lastUniqueWord = words[i];
        break;
    }
}

And finally, return the last unique word:

return lastUniqueWord;

This efficient approach, with a time complexity closer to $O(n)$, is far superior to the naive method and showcases your proficiency at solving algorithmic problems with JavaScript's Set.