g0201_0300.s0208_implement_trie_prefix_tree.Trie Maven / Gradle / Ivy

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package g0201_0300.s0208_implement_trie_prefix_tree;

// #Medium #Top_100_Liked_Questions #Top_Interview_Questions #String #Hash_Table #Design #Trie
// #Level_2_Day_16_Design #Udemy_Trie_and_Heap
// #Big_O_Time_O(word.length())_or_O(prefix.length())_Space_O(N)
// #2022_06_28_Time_34_ms_(99.90%)_Space_51_MB_(94.92%)

/**
 * 208 - Implement Trie (Prefix Tree)\.
 *
 * Medium
 *
 * A [**trie** ](https://en.wikipedia.org/wiki/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.
 *
 * **Example 1:**
 *
 * **Input**
 *
 *     ["Trie", "insert", "search", "search", "startsWith", "insert", "search"]
 *     [ [], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
 *
 * **Output:** [null, null, true, false, true, null, true]
 *
 * **Explanation:**
 *
 *     Trie trie = new Trie();
 *     trie.insert("apple"); trie.search("apple"); // return True
 *     trie.search("app"); // return False
 *     trie.startsWith("app"); // return True
 *     trie.insert("app");
 *     trie.search("app"); // return True 
 *
 * **Constraints:**
 *
 * *   `1 <= word.length, prefix.length <= 2000`
 * *   `word` and `prefix` consist only of lowercase English letters.
 * *   At most 3 * 10⁴ calls **in total** will be made to `insert`, `search`, and `startsWith`.
**/
@SuppressWarnings("java:S1104")
public class Trie {
    private TrieNode root;
    private boolean startWith;

    private static class TrieNode {
        // Initialize your data structure here.
        public TrieNode[] children;
        public boolean isWord;

        public TrieNode() {
            children = new TrieNode[26];
        }
    }

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

    // Inserts a word into the trie.
    public void insert(String word) {
        insert(word, root, 0);
    }

    private void insert(String word, TrieNode root, int idx) {
        if (idx == word.length()) {
            root.isWord = true;
            return;
        }
        int index = word.charAt(idx) - 'a';
        if (root.children[index] == null) {
            root.children[index] = new TrieNode();
        }
        insert(word, root.children[index], idx + 1);
    }

    // Returns if the word is in the trie.
    public boolean search(String word) {
        return search(word, root, 0);
    }

    public boolean search(String word, TrieNode root, int idx) {
        if (idx == word.length()) {
            startWith = true;
            return root.isWord;
        }
        int index = word.charAt(idx) - 'a';
        if (root.children[index] == null) {
            startWith = false;
            return false;
        }
        return search(word, root.children[index], idx + 1);
    }

    // Returns if there is any word in the trie
    // that starts with the given prefix.
    public boolean startsWith(String prefix) {
        search(prefix);
        return startWith;
    }
}