LeetCode 208. Implement Trie (Prefix Tree)

Question

A trie (pronounced as “try”) or prefix tree is a tree data structure used to efficiently store and retrieve keys in a dataset of strings. There are various applications of this data structure, such as autocomplete and spellchecker.

Implement the Trie class:

• Trie() Initializes the trie object.
• void insert(String word) Inserts the string word into the trie.
• boolean search(String word) Returns true if the string word is in the trie (i.e., was inserted before), and false otherwise.
• boolean startsWith(String prefix) Returns true if there is a previously inserted string word that has the prefix prefix, and false otherwise.

https://leetcode.com/problems/implement-trie-prefix-tree/

• Solution1

class Trie {
    TrieNode root;
    public Trie() {
        root = new TrieNode();
    }
    
    public void insert(String word) {
        TrieNode node = root;
        for (char c : word.toCharArray()) {
            if (node.children[c-'a']==null) node.children[c-'a'] = new TrieNode();
            node = node.children[c - 'a'];
        }
        node.isWord = true;
    }
    
    public boolean search(String word) {
        TrieNode node = root;
        for (char c : word.toCharArray()) {
            if (node.children[c - 'a']==null) return false;
            node = node.children[c-'a'];
        }
        return node.isWord;
    }
    
    public boolean startsWith(String prefix) {
        TrieNode node = root;
        for (char c: prefix.toCharArray()){
            if(node.children[c-'a']==null) return false;
            node = node.children[c-'a'];
        }
        return true;
    }
    
class TrieNode {
    TrieNode[] children;
    boolean isWord;
    public TrieNode(){
        children = new TrieNode[26];
    }
}
}

Complexity:

Time complexity: O( n)

Space complexity: O(1)