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3.2. &nbsp; 基本数据类型
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3.3. &nbsp; 数字编码 *
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3.4. &nbsp; 字符编码 *
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4.2. &nbsp; 链表
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4.3. &nbsp; 列表
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5.1. &nbsp; 栈
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5.2. &nbsp; 队列
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5.3. &nbsp; 双向队列
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6.2. &nbsp; 哈希冲突（New）
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7.2. &nbsp; 二叉树遍历
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7.4. &nbsp; 二叉搜索树
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7.5. &nbsp; AVL 树 *
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8.2. &nbsp; 建堆操作
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9.2. &nbsp; 图基础操作
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10.1. &nbsp; 二分查找
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10.2. &nbsp; 二分查找边界
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10.3. &nbsp; 哈希优化策略
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10.4. &nbsp; 重识搜索算法
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11.1. &nbsp; 排序算法
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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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11.4. &nbsp; 插入排序
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11.5. &nbsp; 快速排序
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11.6. &nbsp; 归并排序
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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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1.2.1. &nbsp; 算法定义
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1.2.2. &nbsp; 数据结构定义
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<div class="md-content" data-md-component="content">
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<a href="https://github.com/krahets/hello-algo/tree/main/docs/chapter_introduction/what_is_dsa.md" title="编辑此页" class="md-content__button md-icon">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M10 20H6V4h7v5h5v3.1l2-2V8l-6-6H6c-1.1 0-2 .9-2 2v16c0 1.1.9 2 2 2h4v-2m10.2-7c.1 0 .3.1.4.2l1.3 1.3c.2.2.2.6 0 .8l-1 1-2.1-2.1 1-1c.1-.1.2-.2.4-.2m0 3.9L14.1 23H12v-2.1l6.1-6.1 2.1 2.1Z"/></svg>
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<h1 id="12">1.2. &nbsp; 算法是什么<a class="headerlink" href="#12" title="Permanent link">&para;</a></h1>
<h2 id="121">1.2.1. &nbsp; 算法定义<a class="headerlink" href="#121" title="Permanent link">&para;</a></h2>
<p>「算法 Algorithm」是在有限时间内解决特定问题的一组指令或操作步骤。算法具有以下特性：</p>
<ul>
<li>问题是明确的，包含清晰的输入和输出定义。</li>
<li>具有可行性，能够在有限步骤、时间和内存空间下完成。</li>
<li>各步骤都有确定的含义，相同的输入和运行条件下，输出始终相同。</li>
</ul>
<h2 id="122">1.2.2. &nbsp; 数据结构定义<a class="headerlink" href="#122" title="Permanent link">&para;</a></h2>
<p>「数据结构 Data Structure」是计算机中组织和存储数据的方式。为了提高数据存储和操作性能，数据结构的设计目标包括：</p>
<ul>
<li>空间占用尽量减少，节省计算机内存。</li>
<li>数据操作尽可能快速，涵盖数据访问、添加、删除、更新等。</li>
<li>提供简洁的数据表示和逻辑信息，以便使得算法高效运行。</li>
</ul>
<p>数据结构设计是一个充满权衡的过程，这意味着要在某方面取得优势，往往需要在另一方面作出妥协。例如，链表相较于数组，在数据添加和删除操作上更加便捷，但牺牲了数据访问速度；图相较于链表，提供了更丰富的逻辑信息，但需要占用更大的内存空间。</p>
<h2 id="123">1.2.3. &nbsp; 数据结构与算法的关系<a class="headerlink" href="#123" title="Permanent link">&para;</a></h2>
<p>「数据结构」与「算法」高度相关且紧密结合，具体表现在：</p>
<ul>
<li>数据结构是算法的基石。数据结构为算法提供了结构化存储的数据，以及用于操作数据的方法。</li>
<li>算法是数据结构发挥的舞台。数据结构本身仅存储数据信息，通过结合算法才能解决特定问题。</li>
<li>特定算法通常有对应最优的数据结构。算法通常可以基于不同的数据结构进行实现，但最终执行效率可能相差很大。</li>
</ul>
<p><img alt="数据结构与算法的关系" src="../what_is_dsa.assets/relationship_between_data_structure_and_algorithm.png" /></p>
<p align="center"> Fig. 数据结构与算法的关系 </p>
<p>类比「LEGO 乐高」和「数据结构与算法」，则对应关系如下表所示。</p>
<div class="center-table">
<table>
<thead>
<tr>
<th>数据结构与算法</th>
<th>LEGO 乐高</th>
</tr>
</thead>
<tbody>
<tr>
<td>输入数据</td>
<td>未拼装的积木</td>
</tr>
<tr>
<td>数据结构</td>
<td>积木组织形式，包括形状、大小、连接方式等</td>
</tr>
<tr>
<td>算法</td>
<td>把积木拼成目标形态的一系列操作步骤</td>
</tr>
<tr>
<td>输出数据</td>
<td>积木模型</td>
</tr>
</tbody>
</table>
</div>
<p>值得注意的是，数据结构与算法独立于编程语言。正因如此，本书得以提供多种编程语言的实现。</p>
<div class="admonition tip">
<p class="admonition-title">约定俗成的简称</p>
<p>在实际讨论时，我们通常会将「数据结构与算法」简称为「算法」。例如，众所周知的 LeetCode 算法题目，实际上同时考察了数据结构和算法两方面的知识。</p>
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