LeetCode 208: Implement Trie (Prefix Tree) Solution

Master LeetCode problem 208 (Implement Trie (Prefix Tree)), a medium challenge, with our optimized solutions in Java, C++, and Python. Explore detailed explanations, test your code in our interactive editor, and prepare for coding interviews.

208. Implement Trie (Prefix Tree)

Medium

Hash Table String Design Trie

Problem Explanation

Explanation

A Trie, also known as a Prefix Tree, is a tree-like data structure used to store a dynamic set of strings. Each node in the Trie represents a single character. By following the path from the root to a particular node, we can reconstruct the string formed by the characters along that path.

For this problem, we need to implement a Trie class with the following functionalities:

Trie() - Initialize the Trie data structure.
insert(String word) - Insert a word into the Trie.
search(String word) - Check if a word exists in the Trie.
startsWith(String prefix) - Check if any word in the Trie starts with a given prefix.

To implement these functionalities, we can use a TrieNode class to represent each node in the Trie. Each TrieNode will have a map to store references to its children nodes. The root of the Trie corresponds to an empty string, and each character in the word corresponds to a level in the Trie.

Time Complexity

Insertion: O(m), where m is the length of the word being inserted.
Search: O(m), where m is the length of the word being searched.
StartsWith: O(m), where m is the length of the prefix being checked.

Space Complexity

O(n*m), where n is the number of words inserted and m is the average length of the words.

Solution Code

class Trie {
    private TrieNode root;

    public Trie() {
        root = new TrieNode();
    }

    public void insert(String word) {
        TrieNode node = root;
        for (char c : word.toCharArray()) {
            if (!node.containsKey(c)) {
                node.put(c, new TrieNode());
            }
            node = node.get(c);
        }
        node.setEnd();
    }

    public boolean search(String word) {
        TrieNode node = searchPrefix(word);
        return node != null && node.isEnd();
    }

    public boolean startsWith(String prefix) {
        return searchPrefix(prefix) != null;
    }

    private TrieNode searchPrefix(String prefix) {
        TrieNode node = root;
        for (char c : prefix.toCharArray()) {
            if (node.containsKey(c)) {
                node = node.get(c);
            } else {
                return null;
            }
        }
        return node;
    }

    class TrieNode {
        private TrieNode[] links;
        private final int R = 26;
        private boolean isEnd;

        public TrieNode() {
            links = new TrieNode[R];
        }

        public boolean containsKey(char ch) {
            return links[ch - 'a'] != null;
        }

        public TrieNode get(char ch) {
            return links[ch - 'a'];
        }

        public void put(char ch, TrieNode node) {
            links[ch - 'a'] = node;
        }

        public void setEnd() {
            isEnd = true;
        }

        public boolean isEnd() {
            return isEnd;
        }
    }
}

Try It Yourself

Loading code editor...

Frequently Asked Questions

How to solve LeetCode 208 (Implement Trie (Prefix Tree))?

This page provides optimized solutions for LeetCode problem 208 (Implement Trie (Prefix Tree)) in Java, C++, and Python, along with a detailed explanation and an interactive code editor to test your code.

What is the time complexity of LeetCode 208 (Implement Trie (Prefix Tree))?

The time complexity for LeetCode 208 (Implement Trie (Prefix Tree)) varies by solution. Check the detailed explanation section for specific complexities in Java, C++, and Python implementations.

Can I run code for LeetCode 208 on DevExCode?

Yes, DevExCode provides an interactive code editor where you can write, test, and run your code for LeetCode 208 in Java, C++, or Python.

Back to LeetCode Solutions