211. Add and Search Word - Data structure design

布满荆棘的人生 2022-04-24 16:56 128阅读 0赞

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.
    
    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.

本题与[208. Implement Trie (Prefix Tree)][208. Implement Trie _Prefix Tree]类似，都是前缀树的应用。详细代码如下：

/**
     * 208. Implement Trie (Prefix Tree)
     * 前缀树的节点定义
     */
    class TrieNode {
        private TrieNode[] links;//最多有26个子节点
        private final int MAX_NODE = 26;
        private boolean isEnd;//判断该节点是否是尾结点（即是否存在从根节点到该节点的单词）
    
        public TrieNode() {
            links = new TrieNode[MAX_NODE];
        }
    
        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 boolean isEnd() {
            return isEnd;
        }
    
        public void setEnd(boolean end) {
            isEnd = end;
        }
    }
    
    /**
     * Your WordDictionary object will be instantiated and called as such:
     * WordDictionary obj = new WordDictionary();
     * obj.addWord(word);
     * boolean param_2 = obj.search(word);
     */
    class WordDictionary {
        private TrieNode root;
    
        /** Initialize your data structure here. */
        public WordDictionary() {
            root = new TrieNode();
        }
    
        /** Adds a word into the data structure. */
        public void addWord(String word) {
            TrieNode node = root;
            for(int i = 0; i < word.length(); ++i) {
                char ch = word.charAt(i);
                if(!node.containsKey(ch)) {
                    node.put(ch, new TrieNode());
                }
                node = node.get(ch);
            }
            node.setEnd(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 searchFrom(word, root);
        }
    
        private boolean searchFrom(String word, TrieNode node) {
            if(node == null || word == null) return false;
            for(int i = 0; i < word.length(); ++i) {
                char ch = word.charAt(i);
                if(ch != '.') {
                    if(!node.containsKey(ch)) {
                        return false;
                    }
                    node = node.get(ch);
                } else {
                    String sub = word.substring(i+1);
                    for(char cc = 'a'; cc <= 'z'; ++cc) {
                        if(searchFrom(sub, node.get(cc)))
                            return true;
                    }
                    return false;
                }
            }
            return node != null && node.isEnd();
        }
    }

[208. Implement Trie _Prefix Tree]: https://blog.csdn.net/weixin_41704428/article/details/89675182