Add and Search Word - Data structure design-优快云博客

本文介绍了一种使用前缀树解决字典树问题的方法，包括添加单词、搜索单词以及处理正则表达式的搜索。通过实例演示了如何实现此功能，并提供了关键代码段。

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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.

这也是一道用前缀树来解决的题目，做了稍微的变形，多了一个对于' . '的检测，对于如何构造一个前缀树，大家可以参考[url=http://kickcode.iteye.com/blog/2273461]Implement Trie (Prefix Tree)[/url]这篇文章。这道题目的代码如下：


class TrieNode {
    boolean isLast;
    TrieNode[] trieNode;
    public TrieNode() {
        trieNode = new TrieNode[26];
        isLast = false;
    }
}

public class WordDictionary {
    TrieNode root;
    public WordDictionary() {
        root = new TrieNode();
    }
    // Adds a word into the data structure.

    public void addWord(String word) {
        TrieNode cur = root;
        for(char c : word.toCharArray()) {
            if(cur.trieNode[c - 'a'] == null)
                cur.trieNode[c - 'a'] = new TrieNode();
            cur = cur.trieNode[c - 'a'];
        }
        cur.isLast = 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) {
        TrieNode cur = root;
        if(root == null) return false;
        return search(word, cur, 0);
    }
    public boolean search(String word, TrieNode cur, int index) {
        if(cur == null) return false;
        if(index == word.length()) return cur.isLast;
        char c = word.charAt(index);
        if(c == '.') {
            for(TrieNode node : cur.trieNode) {
                if(search(word, node, index + 1))
                    return true;
            }
        } else {
            cur = cur.trieNode[c - 'a'];
            return search(word, cur, index + 1);
        }
        return false;
    }
}

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