{"id":34542,"date":"2024-11-01T09:29:12","date_gmt":"2024-11-01T09:29:12","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=34542"},"modified":"2024-11-01T11:40:50","modified_gmt":"2024-11-01T11:40:50","slug":"javascript-coding-test-course-try","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/34542\/","title":{"rendered":"JavaScript Coding Test Course, Try"},"content":{"rendered":"

<\/p>\n

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.<\/p>\n

What is a Trie?<\/h2>\n

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.<\/p>\n

Problem: Word Search<\/h2>\n

Below is a problem utilizing the Trie data structure.<\/p>\n

\n

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.<\/p>\n<\/blockquote>\n

Problem-Solving Strategy<\/h2>\n
    \n
  1. First, implement the Trie structure.<\/li>\n
  2. Insert the given list of words into the Trie.<\/li>\n
  3. Use the search term to explore all possible words in the Trie.<\/li>\n<\/ol>\n

    Trie Implementation<\/h2>\n

    To implement a Trie, the following basic structure is needed:<\/p>\n

    class TrieNode {\n    constructor() {\n        this.children = {};\n        this.isEndOfWord = false;\n    }\n}\n\nclass Trie {\n    constructor() {\n        this.root = new TrieNode();\n    }\n\n    insert(word) {\n        let node = this.root;\n        for (let char of word) {\n            if (!node.children[char]) {\n                node.children[char] = new TrieNode();\n            }\n            node = node.children[char];\n        }\n        node.isEndOfWord = true;\n    }\n\n    search(prefix) {\n        let node = this.root;\n        for (let char of prefix) {\n            if (!node.children[char]) return [];\n            node = node.children[char];\n        }\n        return this._findAllWords(node, prefix);\n    }\n\n    _findAllWords(node, prefix) {\n        const results = [];\n        if (node.isEndOfWord) {\n            results.push(prefix);\n        }\n        for (let char in node.children) {\n            results.push(...this._findAllWords(node.children[char], prefix + char));\n        }\n        return results;\n    }\n}<\/code><\/pre>\n
    Inserting and Searching Words<\/h2>\n
    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:<\/p>\n
    const getWords = (words, searchWord) => {\n    const trie = new Trie();\n    for (let word of words) {\n        trie.insert(word);\n    }\n    return trie.search(searchWord);\n};\n\nconst wordsList = [\"apple\", \"app\", \"apricot\", \"banana\", \"bat\", \"ball\"];\nconst searchTerm = \"ap\";\nconst foundWords = getWords(wordsList, searchTerm);\nconsole.log(foundWords); \/\/ [\"apple\", \"app\", \"apricot\"]<\/code><\/pre>\n
    Code Explanation<\/h2>\n
    In the above code, the getWords<\/code> function first inserts the provided list of words into the Trie, then searches the Trie with the given search term. The insert<\/code> method takes a word and connects each character as a node, while the search<\/code> method finds and returns all words corresponding to the given prefix.<\/p>\n
    Complexity Analysis<\/h2>\n
    The performance of insertion and search in the Trie varies depending on the length of the string and the depth of the tree:<\/p>\n