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chapter_graph/graph_operations/index.html
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<p>以下是基于邻接矩阵表示图的实现代码。</p>
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<div class="highlight"><span class="filename">graph_adjacency_matrix.java</span><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="cm">/* 基于邻接矩阵实现的无向图类 */</span>
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<li>如果类似邻接矩阵那样，使用顶点列表索引来区分不同顶点。那么，假设我们想要删除索引为 <span class="arithmatex">\(i\)</span> 的顶点，则需要遍历整个邻接表，将其中 <span class="arithmatex">\(&gt; i\)</span> 的索引全部减 <span class="arithmatex">\(1\)</span> ，这样操作效率较低。</li>
<li>因此我们考虑引入顶点类 <code>Vertex</code> ，使得每个顶点都是唯一的对象，此时删除顶点时就无需改动其余顶点了。</li>
</ul>
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<div class="highlight"><span class="filename">graph_adjacency_list.java</span><pre><span></span><code><a id="__codelineno-12-1" name="__codelineno-12-1" href="#__codelineno-12-1"></a><span class="cm">/* 基于邻接表实现的无向图类 */</span>

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chapter_graph/graph_traversal/index.html
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<li>循环步骤 <code>2.</code> ，直到所有顶点被访问完成后结束。</li>
</ol>
<p>为了防止重复遍历顶点，我们需要借助一个哈希表 <code>visited</code> 来记录哪些节点已被访问。</p>
<div class="tabbed-set tabbed-alternate" data-tabs="1:12"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><input id="__tabbed_1_2" name="__tabbed_1" type="radio" /><input id="__tabbed_1_3" name="__tabbed_1" type="radio" /><input id="__tabbed_1_4" name="__tabbed_1" type="radio" /><input id="__tabbed_1_5" name="__tabbed_1" type="radio" /><input id="__tabbed_1_6" name="__tabbed_1" type="radio" /><input id="__tabbed_1_7" name="__tabbed_1" type="radio" /><input id="__tabbed_1_8" name="__tabbed_1" type="radio" /><input id="__tabbed_1_9" name="__tabbed_1" type="radio" /><input id="__tabbed_1_10" name="__tabbed_1" type="radio" /><input id="__tabbed_1_11" name="__tabbed_1" type="radio" /><input id="__tabbed_1_12" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1">Java</label><label for="__tabbed_1_2">C++</label><label for="__tabbed_1_3">Python</label><label for="__tabbed_1_4">Go</label><label for="__tabbed_1_5">JavaScript</label><label for="__tabbed_1_6">TypeScript</label><label for="__tabbed_1_7">C</label><label for="__tabbed_1_8">C#</label><label for="__tabbed_1_9">Swift</label><label for="__tabbed_1_10">Zig</label><label for="__tabbed_1_11">Dart</label><label for="__tabbed_1_12">Rust</label></div>
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<div class="highlight"><span class="filename">graph_bfs.java</span><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="cm">/* 广度优先遍历 BFS */</span>
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<h3 id="_3">算法实现<a class="headerlink" href="#_3" title="Permanent link">&para;</a></h3>
<p>这种“走到尽头 + 回溯”的算法形式通常基于递归来实现。与 BFS 类似，在 DFS 中我们也需要借助一个哈希表 <code>visited</code> 来记录已被访问的顶点，以避免重复访问顶点。</p>
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<div class="highlight"><span class="filename">graph_dfs.java</span><pre><span></span><code><a id="__codelineno-12-1" name="__codelineno-12-1" href="#__codelineno-12-1"></a><span class="cm">/* 深度优先遍历 DFS 辅助函数 */</span>