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krahets committed Dec 13, 2022
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4 changes: 3 additions & 1 deletion docs/chapter_computational_complexity/space_time_tradeoff.md
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理想情况下,我们希望算法的时间复杂度和空间复杂度都能够达到最优,而实际上,同时优化时间复杂度和空间复杂度是非常困难的。

**降低时间复杂度,往往是以提升空间复杂度为代价的,反之亦然。** 我们把牺牲内存空间来提升算法运行速度的思路称为「以空间换时间」;反之,称之为「以时间换空间」。选择哪种思路取决于我们更看重哪个方面。大多数情况下,内存空间不会成为算法瓶颈,因此以空间换时间更加常用。
**降低时间复杂度,往往是以提升空间复杂度为代价的,反之亦然。** 我们把牺牲内存空间来提升算法运行速度的思路称为「以空间换时间」;反之,称之为「以时间换空间」。选择哪种思路取决于我们更看重哪个方面。

大多数情况下,时间都是比空间更宝贵的,只要空间复杂度不要太离谱、能接受就行,**因此以空间换时间最为常用**

## 示例题目 *

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2 changes: 1 addition & 1 deletion docs/chapter_tree/avl_tree.md
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## AVL 树典型应用

- 组织存储大型数据,适用于高频查找、低频增删场景
- 组织存储大型数据,适用于高频查找、低频增删场景
- 用于建立数据库中的索引系统;

!!! question "为什么红黑树比 AVL 树更受欢迎?"
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4 changes: 2 additions & 2 deletions mkdocs.yml
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site_name: Hello 算法
site_url: https://www.hello-algo.com/
site_author: Krahets
site_description: Your first book to learn Data Structure And Algorithm.
site_description: 一本动画图解、能运行、可提问的数据结构与算法入门书
# Repository
repo_name: krahets/hello-algo
repo_url: https://github.com/krahets/hello-algo
edit_uri: https://github.com/krahets/hello-algo/tree/master/docs/

# Copyright
copyright: Copyright © 2020 - 2022 Krahets
copyright: Copyright © 2022 Krahets

# Configuration
theme:
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