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7.2 &nbsp; 二叉树遍历
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第 8 章 &nbsp;
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第 9 章 &nbsp;
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9.2 &nbsp; 图基础操作
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第 10 章 &nbsp; 搜索
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10.2 &nbsp; 二分查找插入点
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10.3 &nbsp; 二分查找边界
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10.4 &nbsp; 哈希优化策略
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10.5 &nbsp; 重识搜索算法
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第 11 章 &nbsp; 排序
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11.2 &nbsp; 选择排序
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11.3 &nbsp; 冒泡排序
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11.7 &nbsp; 堆排序
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11.8 &nbsp; 桶排序
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11.9 &nbsp; 计数排序
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11.10 &nbsp; 基数排序
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第 12 章 &nbsp; 分治
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12.1 &nbsp; 分治算法
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12.4 &nbsp; 汉诺塔问题
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第 13 章 &nbsp; 回溯
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第 14 章 &nbsp; 动态规划
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14.2 &nbsp; DP 问题特性
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14.3 &nbsp; DP 解题思路
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14.4 &nbsp; 0-1 背包问题
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14.6 &nbsp; 编辑距离问题
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<h1 id="76">7.6 &nbsp; 小结<a class="headerlink" href="#76" title="Permanent link">&para;</a></h1>
<h3 id="1">1. &nbsp; 重点回顾<a class="headerlink" href="#1" title="Permanent link">&para;</a></h3>
<ul>
<li>二叉树是一种非线性数据结构,体现“一分为二”的分治逻辑。每个二叉树节点包含一个值以及两个指针,分别指向其左子节点和右子节点。</li>
<li>对于二叉树中的某个节点,其左(右)子节点及其以下形成的树被称为该节点的左(右)子树。</li>
<li>二叉树的相关术语包括根节点、叶节点、层、度、边、高度和深度等。</li>
<li>二叉树的初始化、节点插入和节点删除操作与链表操作方法类似。</li>
<li>常见的二叉树类型有完美二叉树、完全二叉树、完满二叉树和平衡二叉树。完美二叉树是最理想的状态,而链表是退化后的最差状态。</li>
<li>二叉树可以用数组表示,方法是将节点值和空位按层序遍历顺序排列,并根据父节点与子节点之间的索引映射关系来实现指针。</li>
<li>二叉树的层序遍历是一种广度优先搜索方法,它体现了“一圈一圈向外扩展”的逐层遍历方式,通常通过队列来实现。</li>
<li>前序、中序、后序遍历皆属于深度优先搜索,它们体现了“先走到尽头,再回溯继续”的遍历方式,通常使用递归来实现。</li>
<li>二叉搜索树是一种高效的元素查找数据结构,其查找、插入和删除操作的时间复杂度均为 <span class="arithmatex">\(O(\log n)\)</span> 。当二叉搜索树退化为链表时,各项时间复杂度会劣化至 <span class="arithmatex">\(O(n)\)</span></li>
<li>AVL 树,也称平衡二叉搜索树,它通过旋转操作确保在不断插入和删除节点后树仍然保持平衡。</li>
<li>AVL 树的旋转操作包括右旋、左旋、先右旋再左旋、先左旋再右旋。在插入或删除节点后AVL 树会从底向顶执行旋转操作,使树重新恢复平衡。</li>
</ul>
<h3 id="2-q-a">2. &nbsp; Q &amp; A<a class="headerlink" href="#2-q-a" title="Permanent link">&para;</a></h3>
<p><strong>Q</strong>:对于只有一个节点的二叉树,树的高度和根节点的深度都是 <span class="arithmatex">\(0\)</span> 吗?</p>
<p>是的,因为高度和深度通常定义为“经过的边的数量”。</p>
<p><strong>Q</strong>:二叉树中的插入与删除一般由一套操作配合完成,这里的“一套操作”指什么呢?可以理解为资源的子节点的资源释放吗?</p>
<p>拿二叉搜索树来举例,删除节点操作要分三种情况处理,其中每种情况都需要进行多个步骤的节点操作。</p>
<p><strong>Q</strong>:为什么 DFS 遍历二叉树有前、中、后三种顺序,分别有什么用呢?</p>
<p>与顺序和逆序遍历数组类似,前序、中序、后序遍历是三种二叉树遍历方法,我们可以使用它们得到一个特定顺序的遍历结果。例如在二叉搜索树中,由于节点大小满足 <code>左子节点值 &lt; 根节点值 &lt; 右子节点值</code> ,因此我们只要按照“左 <span class="arithmatex">\(\rightarrow\)</span><span class="arithmatex">\(\rightarrow\)</span> 右”的优先级遍历树,就可以获得有序的节点序列。</p>
<p><strong>Q</strong>:右旋操作是处理失衡节点 <code>node</code><code>child</code><code>grand_child</code> 之间的关系,那 <code>node</code> 的父节点和 <code>node</code> 原来的连接不需要维护吗?右旋操作后岂不是断掉了?</p>
<p>我们需要从递归的视角来看这个问题。右旋操作 <code>right_rotate(root)</code> 传入的是子树的根节点,最终 <code>return child</code> 返回旋转之后的子树的根节点。子树的根节点和其父节点的连接是在该函数返回后完成的,不属于右旋操作的维护范围。</p>
<p><strong>Q</strong>:在 C++ 中,函数被划分到 <code>private</code><code>public</code> 中,这方面有什么考量吗?为什么要将 <code>height()</code> 函数和 <code>updateHeight()</code> 函数分别放在 <code>public</code><code>private</code> 中呢?</p>
<p>主要看方法的使用范围,如果方法只在类内部使用,那么就设计为 <code>private</code> 。例如,用户单独调用 <code>updateHeight()</code> 是没有意义的,它只是插入、删除操作中的一步。而 <code>height()</code> 是访问节点高度,类似于 <code>vector.size()</code> ,因此设置成 <code>public</code> 以便使用。</p>
<p><strong>Q</strong>:如何从一组输入数据构建一棵二叉搜索树?根节点的选择是不是很重要?</p>
<p>是的,构建树的方法已在二叉搜索树代码中的 <code>build_tree()</code> 方法中给出。至于根节点的选择,我们通常会将输入数据排序,然后将中点元素作为根节点,再递归地构建左右子树。这样做可以最大程度保证树的平衡性。</p>
<p><strong>Q</strong>:在 Java 中,字符串对比是否一定要用 <code>equals()</code> 方法?</p>
<p>在 Java 中,对于基本数据类型,<code>==</code> 用于对比两个变量的值是否相等。对于引用类型,两种符号的工作原理是不同的。</p>
<ul>
<li><code>==</code> :用来比较两个变量是否指向同一个对象,即它们在内存中的位置是否相同。</li>
<li><code>equals()</code>:用来对比两个对象的值是否相等。</li>
</ul>
<p>因此,如果要对比值,我们应该使用 <code>equals()</code> 。然而,通过 <code>String a = "hi"; String b = "hi";</code> 初始化的字符串都存储在字符串常量池中,它们指向同一个对象,因此也可以用 <code>a == b</code> 来比较两个字符串的内容。</p>
<p><strong>Q</strong>:广度优先遍历到最底层之前,队列中的节点数量是 <span class="arithmatex">\(2^h\)</span> 吗?</p>
<p>是的,例如高度 <span class="arithmatex">\(h = 2\)</span> 的满二叉树,其节点总数 <span class="arithmatex">\(n = 7\)</span> ,则底层节点数量 <span class="arithmatex">\(4 = 2^h = (n + 1) / 2\)</span></p>
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