JavaScript Coding Test Course, Try

In this course, we will take a detailed look at solving algorithm problems using JavaScript and the usage of the Trie data structure. The Trie is a very useful data structure to improve the efficiency of string processing. In this course, we will explain the process of solving specific problems using the Trie.

What is a Trie?

A Trie is a tree-like data structure used to store a large number of strings. Common applications include auto-completion, word search, and prefix search. Each node in the Trie corresponds to a character in the string, allowing for efficient word composition through paths.

Problem: Word Search

Below is a problem utilizing the Trie data structure.

When given a list of words and a search term, find all the words in the list that exist, and return all words that contain the search term.

Problem-Solving Strategy

1. First, implement the Trie structure.
2. Insert the given list of words into the Trie.
3. Use the search term to explore all possible words in the Trie.

Trie Implementation

To implement a Trie, the following basic structure is needed:

class TrieNode {
    constructor() {
        this.children = {};
        this.isEndOfWord = false;
    }
}

class Trie {
    constructor() {
        this.root = new TrieNode();
    }

    insert(word) {
        let node = this.root;
        for (let char of word) {
            if (!node.children[char]) {
                node.children[char] = new TrieNode();
            }
            node = node.children[char];
        }
        node.isEndOfWord = true;
    }

    search(prefix) {
        let node = this.root;
        for (let char of prefix) {
            if (!node.children[char]) return [];
            node = node.children[char];
        }
        return this._findAllWords(node, prefix);
    }

    _findAllWords(node, prefix) {
        const results = [];
        if (node.isEndOfWord) {
            results.push(prefix);
        }
        for (let char in node.children) {
            results.push(...this._findAllWords(node.children[char], prefix + char));
        }
        return results;
    }
}

Inserting and Searching Words

Now, I will explain how to insert words into the Trie and find all possible words for a specific search term. The process will be illustrated through the example below:

const getWords = (words, searchWord) => {
    const trie = new Trie();
    for (let word of words) {
        trie.insert(word);
    }
    return trie.search(searchWord);
};

const wordsList = ["apple", "app", "apricot", "banana", "bat", "ball"];
const searchTerm = "ap";
const foundWords = getWords(wordsList, searchTerm);
console.log(foundWords); // ["apple", "app", "apricot"]

Code Explanation

In the above code, the getWords function first inserts the provided list of words into the Trie, then searches the Trie with the given search term. The insert method takes a word and connects each character as a node, while the search method finds and returns all words corresponding to the given prefix.

Complexity Analysis

The performance of insertion and search in the Trie varies depending on the length of the string and the depth of the tree:

• Insertion: O(L), where L is the length of the word.
• Search: O(P + W), where P is the length of the prefix, and W is the number of words returned as a result.

Conclusion

In this course, we learned how to solve string search problems using the Trie data structure in JavaScript. Tries have the capability to efficiently handle large numbers of words, making them particularly useful for implementing features like auto-completion or word search.

Explore more examples and problems regarding the Trie algorithm to enhance your understanding. Stay tuned for more algorithms and data structures in the next course!