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"question": {
"questionId": "3305",
"questionFrontendId": "3045",
"categoryTitle": "Algorithms",
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"title": "Count Prefix and Suffix Pairs II",
"titleSlug": "count-prefix-and-suffix-pairs-ii",
"content": "<p>You are given a <strong>0-indexed</strong> string array <code>words</code>.</p>\n\n<p>Let&#39;s define a <strong>boolean</strong> function <code>isPrefixAndSuffix</code> that takes two strings, <code>str1</code> and <code>str2</code>:</p>\n\n<ul>\n\t<li><code>isPrefixAndSuffix(str1, str2)</code> returns <code>true</code> if <code>str1</code> is <strong>both</strong> a <span data-keyword=\"string-prefix\">prefix</span> and a <span data-keyword=\"string-suffix\">suffix</span> of <code>str2</code>, and <code>false</code> otherwise.</li>\n</ul>\n\n<p>For example, <code>isPrefixAndSuffix(&quot;aba&quot;, &quot;ababa&quot;)</code> is <code>true</code> because <code>&quot;aba&quot;</code> is a prefix of <code>&quot;ababa&quot;</code> and also a suffix, but <code>isPrefixAndSuffix(&quot;abc&quot;, &quot;abcd&quot;)</code> is <code>false</code>.</p>\n\n<p>Return <em>an integer denoting the <strong>number</strong> of index pairs </em><code>(i<em>, </em>j)</code><em> such that </em><code>i &lt; j</code><em>, and </em><code>isPrefixAndSuffix(words[i], words[j])</code><em> is </em><code>true</code><em>.</em></p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:</strong> words = [&quot;a&quot;,&quot;aba&quot;,&quot;ababa&quot;,&quot;aa&quot;]\n<strong>Output:</strong> 4\n<strong>Explanation:</strong> In this example, the counted index pairs are:\ni = 0 and j = 1 because isPrefixAndSuffix(&quot;a&quot;, &quot;aba&quot;) is true.\ni = 0 and j = 2 because isPrefixAndSuffix(&quot;a&quot;, &quot;ababa&quot;) is true.\ni = 0 and j = 3 because isPrefixAndSuffix(&quot;a&quot;, &quot;aa&quot;) is true.\ni = 1 and j = 2 because isPrefixAndSuffix(&quot;aba&quot;, &quot;ababa&quot;) is true.\nTherefore, the answer is 4.</pre>\n\n<p><strong class=\"example\">Example 2:</strong></p>\n\n<pre>\n<strong>Input:</strong> words = [&quot;pa&quot;,&quot;papa&quot;,&quot;ma&quot;,&quot;mama&quot;]\n<strong>Output:</strong> 2\n<strong>Explanation:</strong> In this example, the counted index pairs are:\ni = 0 and j = 1 because isPrefixAndSuffix(&quot;pa&quot;, &quot;papa&quot;) is true.\ni = 2 and j = 3 because isPrefixAndSuffix(&quot;ma&quot;, &quot;mama&quot;) is true.\nTherefore, the answer is 2. </pre>\n\n<p><strong class=\"example\">Example 3:</strong></p>\n\n<pre>\n<strong>Input:</strong> words = [&quot;abab&quot;,&quot;ab&quot;]\n<strong>Output:</strong> 0\n<strong>Explanation: </strong>In this example, the only valid index pair is i = 0 and j = 1, and isPrefixAndSuffix(&quot;abab&quot;, &quot;ab&quot;) is false.\nTherefore, the answer is 0.</pre>\n\n<p>&nbsp;</p>\n<p><strong>Constraints:</strong></p>\n\n<ul>\n\t<li><code>1 &lt;= words.length &lt;= 10<sup>5</sup></code></li>\n\t<li><code>1 &lt;= words[i].length &lt;= 10<sup>5</sup></code></li>\n\t<li><code>words[i]</code> consists only of lowercase English letters.</li>\n\t<li>The sum of the lengths of all <code>words[i]</code> does not exceed <code>5 * 10<sup>5</sup></code>.</li>\n</ul>\n",
"translatedTitle": "统计前后缀下标对 II",
"translatedContent": "<p>给你一个下标从 <strong>0</strong> 开始的字符串数组 <code>words</code> 。</p>\n\n<p>定义一个 <strong>布尔 </strong>函数 <code>isPrefixAndSuffix</code> ,它接受两个字符串参数 <code>str1</code> 和 <code>str2</code> </p>\n\n<ul>\n\t<li>当 <code>str1</code> 同时是 <code>str2</code> 的前缀(<span data-keyword=\"string-prefix\">prefix</span>)和后缀(<span data-keyword=\"string-suffix\">suffix</span>)时,<code>isPrefixAndSuffix(str1, str2)</code> 返回 <code>true</code>,否则返回 <code>false</code>。</li>\n</ul>\n\n<p>例如,<code>isPrefixAndSuffix(\"aba\", \"ababa\")</code> 返回 <code>true</code>,因为 <code>\"aba\"</code> 既是 <code>\"ababa\"</code> 的前缀,也是 <code>\"ababa\"</code> 的后缀,但是 <code>isPrefixAndSuffix(\"abc\", \"abcd\")</code> 返回<code> false</code>。</p>\n\n<p>以整数形式,返回满足 <code>i &lt; j</code> 且 <code>isPrefixAndSuffix(words[i], words[j])</code> 为 <code>true</code> 的下标对 <code>(i, j)</code> 的<strong> 数量 </strong>。</p>\n\n<p>&nbsp;</p>\n\n<p><strong class=\"example\">示例 1</strong></p>\n\n<pre>\n<strong>输入:</strong>words = [\"a\",\"aba\",\"ababa\",\"aa\"]\n<strong>输出:</strong>4\n<strong>解释:</strong>在本示例中,计数的下标对包括:\ni = 0 且 j = 1 ,因为 isPrefixAndSuffix(\"a\", \"aba\") 为 true 。\ni = 0 且 j = 2 ,因为 isPrefixAndSuffix(\"a\", \"ababa\") 为 true 。\ni = 0 且 j = 3 ,因为 isPrefixAndSuffix(\"a\", \"aa\") 为 true 。\ni = 1 且 j = 2 ,因为 isPrefixAndSuffix(\"aba\", \"ababa\") 为 true 。\n因此答案是 4 。</pre>\n\n<p><strong class=\"example\">示例 2</strong></p>\n\n<pre>\n<strong>输入:</strong>words = [\"pa\",\"papa\",\"ma\",\"mama\"]\n<strong>输出:</strong>2\n<strong>解释:</strong>在本示例中,计数的下标对包括:\ni = 0 且 j = 1 ,因为 isPrefixAndSuffix(\"pa\", \"papa\") 为 true 。\ni = 2 且 j = 3 ,因为 isPrefixAndSuffix(\"ma\", \"mama\") 为 true 。\n因此答案是 2 。</pre>\n\n<p><strong class=\"example\">示例 3</strong></p>\n\n<pre>\n<strong>输入:</strong>words = [\"abab\",\"ab\"]\n<strong>输出:</strong>0\n<strong>解释:</strong>在本示例中,唯一有效的下标对是 i = 0 且 j = 1 ,但是 isPrefixAndSuffix(\"abab\", \"ab\") 为 false 。\n因此答案是 0 。</pre>\n\n<p>&nbsp;</p>\n\n<p><strong>提示:</strong></p>\n\n<ul>\n\t<li><code>1 &lt;= words.length &lt;= 10<sup>5</sup></code></li>\n\t<li><code>1 &lt;= words[i].length &lt;= 10<sup>5</sup></code></li>\n\t<li><code>words[i]</code> 仅由小写英文字母组成。</li>\n\t<li>所有 <code>words[i]</code> 的长度之和不超过 <code>5 * 10<sup>5</sup></code> 。</li>\n</ul>\n",
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"We can use a trie to solve it.",
"Process all <code>words[i]</code> from left to right. The trie stores the pair <code>(words[i][j], words[i][words[i].length - j - 1])</code> as a single character; we process all the words in this way.",
"During insertion, keep a counter in each trie node, as in a normal trie. If the current node is the end of a word (namely, the pair on that node is <code>(words[i][words[i].length - 1], words[i][0])</code>), increase the node's counter by <code>1</code>.",
"From left to right, insert each word into the trie, and increase our final result by each node's counter when going down the trie during insertion. This means there was at least one word that is both a prefix and a suffix of the current word before."
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