208. Implement Trie (Prefix Tree) + 211. Add and Search Word - Data structure design

[huimeich]

Implement a trie with insert, search, and startsWith methods.

Note: You may assume that all inputs are consist of lowercase letters a-z.

class TrieNode {
    boolean hasWord;
    HashMap<Character,TrieNode> childList;
    public TrieNode() {
        childList = new HashMap<Character,TrieNode>();
        hasWord = false;
    }
}

public class Trie {
    private TrieNode root;

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

    // Inserts a word into the trie.
    public void insert(String word) {
        TrieNode temp = root;
        for (int i = 0; i < word.length(); i++) {
            if (temp.childList.get(word.charAt(i)) == null){
                (temp.childList).put((Character)word.charAt(i), new TrieNode());
            } 
            temp = temp.childList.get((Character)word.charAt(i));
            if (i == word.length() - 1) 
                temp.hasWord = true;
        }
    }

    // Returns if the word is in the trie.
    public boolean search(String word) {
        TrieNode temp = root;
        for (char c : word.toCharArray()){
            temp = temp.childList.get((Character)c);
            if (temp == null)  return false;
        }
        return temp.hasWord;
    }

    // Returns if there is any word in the trie
    // that starts with the given prefix.
    public boolean startsWith(String prefix) {
        TrieNode temp = root;
        for (char c : prefix.toCharArray()){
            temp = temp.childList.get((Character)c);
            if (temp == null) return false;
        }
        return true;
    }
}

// Your Trie object will be instantiated and called as such:
// Trie trie = new Trie();
// trie.insert("somestring");
// trie.search("key");

[huimeich]

1. Add and Search Word - Data structure design

Design a data structure that supports the following two operations:

void addWord(word) bool search(word) search(word) can search a literal word or a regular expression string containing only letters a-z or .. A . means it can represent any one letter.

For example:

addWord("bad") addWord("dad") addWord("mad") search("pad") -> false search("bad") -> true search(".ad") -> true search("b..") -> true Note: You may assume that all words are consist of lowercase letters a-z.

public class WordDictionary {

    public class TrieNode {
        HashMap<Character, TrieNode> childList;
        boolean hasWord;
        public TrieNode(){
            childList = new HashMap<Character, TrieNode>();
            hasWord = false;
        }
    }

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

    // Adds a word into the data structure.
    public void addWord(String word) {
        TrieNode temp = root;
        for (int i = 0; i < word.length(); i++){
            Character c = new Character(word.charAt(i));
            if (temp.childList.get((Character)c) == null) {
                temp.childList.put(c, new TrieNode());
            }
            temp = temp.childList.get(c);
            if (i == word.length() - 1) temp.hasWord = true;
        }
    }

    // Returns if the word is in the data structure. A word could
    // contain the dot character '.' to represent any one letter.
    public boolean search(String word) {
        return search(word, root);
    }

    public boolean search(String word, TrieNode trie) {
        TrieNode temp = trie;
        for (int i = 0; i < word.length(); i++){
            Character c = new Character(word.charAt(i));
            if (c.charValue() != '.') {
                if (temp.childList.get(c) == null) return false;
                temp = temp.childList.get(c);
            } else {
                for (TrieNode j : temp.childList.values()) {
                    if (i == word.length() - 1) {
                        if (j.hasWord) return true;
                    } else if ( search(word.substring(i + 1), j) ) {
                        return true;
                    }
                }
                return false;
            }
        }                
        return temp.hasWord;
    }
}

// Your WordDictionary object will be instantiated and called as such:
// WordDictionary wordDictionary = new WordDictionary();
// wordDictionary.addWord("word");
// wordDictionary.search("pattern");