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Commit a1c451d

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211. Add and Search Word - Data structure design💥. (#73)
* 211 solved💥. * add more ut case for 211🙏 * optimize code🤞🏻 * clean code
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‎README.md‎

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* [144. Binary Tree Preorder Traversal](src/0144_binary_tree_preorder_traversal/binary_tree_preorder_traversal.go)   *`binary tree;`*   *`pre-order traversal`*
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* [208. Implement Trie (Prefix Tree)](src/0208_implement_trie_prefix_tree/impltrie.go)   *`trie`*
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* [226. Invert Binary Tree](src/0226_invert_binary_tree/invert_binary_tree.go)   *`binary tree`*
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* [211. Add and Search Word - Data structure design](src/0211_add_and_search_word/add_and_search_word.go)   *`trie`*
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* [235. Lowest Common Ancestor of a Binary Search Tree](src/0235_lowest_common_ancestor_of_a_binary_search_tree/lcaoabst.go)   *`binary tree`*
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* [257. Binary Tree Paths](src/0257_binary_tree_paths/binary_tree_paths.go)   *`binary tree`*
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* [307. Range Sum Query - Mutable](src/0307_Range_Sum_Query_Mutable/range_sum_query_mut.go)   *`segment tree`*
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/*
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211. Add and Search Word - Data structure design
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https://leetcode.com/problems/add-and-search-word-data-structure-design/
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*/
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// time: 2019年01月31日
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package aasw
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type node struct {
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isWord bool
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next map[byte]*node
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}
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// WordDictionary supports two operations(addWord, search)
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type WordDictionary struct {
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root *node
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}
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// Constructor initialize data structure here.
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func Constructor() WordDictionary {
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return WordDictionary{&node{next: make(map[byte]*node)}}
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}
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// AddWord adds a word into the trie.
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func (trie *WordDictionary) AddWord(word string) {
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cur := trie.root
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for i := 0; i < len(word); i++ {
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if _, ok := cur.next[word[i]]; !ok {
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cur.next[word[i]] = &node{next: make(map[byte]*node)}
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}
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cur = cur.next[word[i]]
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}
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if !cur.isWord {
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cur.isWord = true
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}
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}
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// Search returns if the word is in the trie.
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// a word could contain the dot character '.' to represent any ont letter.
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func (trie *WordDictionary) Search(word string) bool {
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return match(trie.root, word, 0)
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}
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func match(n *node, word string, index int) bool {
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if index == len(word) {
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return n.isWord
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}
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if word[index] != '.' {
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if _, ok := n.next[word[index]]; !ok {
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return false
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}
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return match(n.next[word[index]], word, index+1)
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} else {
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for _, nextNode := range n.next {
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if match(nextNode, word, index+1) {
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return true
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}
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}
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return false
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}
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}
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package aasw
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import "testing"
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func TestAddAndSearchWord(t *testing.T) {
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obj := Constructor()
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for _, word := range []string{"bad", "dad", "mad"}{
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obj.AddWord(word)
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}
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for i, j := range map[string]bool{"pad": false, "bad": true, ".ad": true, "b..": true, "b..d": false} {
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if res := obj.Search(i); res != j {
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t.Errorf("expected %t, got %t", j, res)
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}
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}
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}

‎src/README.md‎

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|0206|[206. Reverse Linked List](0206_reverse_linked_list/reverse_linked_list.go)|Easy|*`linked list`*|
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|0208|[208. Implement Trie (Prefix Tree)](0208_implement_trie_prefix_tree/impltrie.go)|Medium|*`trie`*|
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|0209|[Minimum Size Subarray Sum](./0209_minimum_size_subarray_sum/minimum_size_subarray_sum.go)|Medium|*`sliding window`*|
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|0211|[211. Add and Search Word - Data structure design](0211_add_and_search_word/add_and_search_word.go)|Medium|*`trie`*|
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|0215|[215. Kth Largest Element in an Array](0215_kth_largest_element_in_an_array/kthleiaa.go)|Medium|*`sort`*|
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|0217|[217. Contains Duplicate](0217_contains_duplicate/contains_duplicate.go)|Easy|*`map`*|
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|0219|[219. Contains Duplicate II](0219_contains_duplicate_2/contains_duplicate_2.go)|Easy|*`map`*|

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