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Commit 01451b1

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‎README.zh-CN.md‎

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- https://coolshell.cn/articles/4671.html
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- https://www.cs.usfca.edu/~galles/visualization/Algorithms.html
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- https://www.cs.usfca.edu/~galles/visualization/source.html
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- [常用数据结构对比及其应用场景](https://www.jianshu.com/p/ec17d738327f)

‎examples/README.md‎

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Java程序员3面小米,被俩算法题难倒,微软员工6分钟解决,真丢脸
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https://zhuanlan.zhihu.com/p/38850888
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各种算法题等
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https://blog.csdn.net/v_JULY_v
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为什么算法这么难? https://zhuanlan.zhihu.com/p/25101438
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‎examples/hash/README.md‎

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- [MD5](https://baike.baidu.com/item/MD5)
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- [SHA家族](https://baike.baidu.com/item/SHA%E5%AE%B6%E6%97%8F/9849595)
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- [npm: md5](https://www.npmjs.com/package/md5)
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- [常见hash算法的原理](http://www.cnblogs.com/zhoug2020/p/6984191.html)
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- [转 从头到尾彻底解析Hash表算法](https://www.cnblogs.com/dancheblog/p/3512284.html)
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- [Hash 函数的常用算法和应用领域](http://www.cnblogs.com/qianxun/archive/2011/07/03/2096773.html)

‎examples/uuid/README.md‎

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世界上的任何两台计算机都不会生成重复的 GUID 值。GUID 主要用于在拥有多个节点、多台计算机的网络或系统中,分配必须具有唯一性的标识符。在 Windows 平台上,GUID 应用非常广泛:注册表、类及接口标识、数据库、甚至自动生成的机器名、目录名等。一个GUID可以在后台数据库中操作一个主键。
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## 适用于分布式唯一标识码的生成算法有哪些?
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- 利用数据库生成
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- 利用Redis/MongoDB/zookeeper生成
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- UUID
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- UUID有基于MAC地址的,加上时间和时钟序列的,也有基于伪随机数的,基于加密哈希的。
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- Twitter的snowflake算法
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- Twitter开源,基于zk,41位时间戳(毫秒数)+10位机器的ID+12位毫秒内的流水号+1位符号位(永远是0)。
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- 优点:性能不错,单机内递增。
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- 缺点:依赖zk;依赖于机器时钟,分布式环境内可能会不是全局递增。
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- 百度 UidGenerator
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- UidGenerator是百度开源的分布式ID生成器,基于于snowflake算法的实现,看起来感觉还行。不过,国内开源的项目维护性真是担忧。
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- 美团 Leaf
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- Leaf 是美团开源的分布式ID生成器,能保证全局唯一性、趋势递增、单调递增、信息安全,里面也提到了几种分布式方案的对比,但也需要依赖关系数据库、Zookeeper等中间件。
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参考资料:
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- https://blog.csdn.net/forlong401/article/details/7580147
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- https://blog.csdn.net/yuanlianming663/article/details/1842267
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- https://www.cnblogs.com/pangguoming/p/7090906.html
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- http://www.cnblogs.com/snandy/p/3261754.html
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- https://m.zjurl.cn/answer/6640244087003808014/?iid=59688834959
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- https://tech.meituan.com/2017/04/21/mt-leaf.html

‎src/data-structures/hash-table/README.zh-CN.md‎

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- [Wikipedia](https://en.wikipedia.org/wiki/Hash_table)
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- [YouTube](https://www.youtube.com/watch?v=shs0KM3wKv8&index=4&list=PLLXdhg_r2hKA7DPDsunoDZ-Z769jWn4R8)
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- [LinkedHashMap、HashMap比较](https://www.jianshu.com/p/979bc680b79f)

‎src/data-structures/linked-list/LinkedList.js‎

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return nodes;
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}
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/**
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* @param {*[]} values - Array of values that need to be converted to linked list.
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* @return {LinkedList}
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*/
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fromArray(values) {
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values.forEach(value => this.append(value));
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return this;
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}
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/**
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* @param {function} [callback]
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* @return {string}

‎src/data-structures/linked-list/README.zh-CN.md‎

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| :-------: | :-------: | :-------: | :-------: |
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| O(n) | O(n) | O(1) | O(1) |
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这里删除的时间复杂度怎么会是 O(1) 呢,这里明明需要遍历,应该是O(n)
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如果已知需要删除的**节点**,那么可以使用以下方法优化到 O(1)
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参考:https://mp.weixin.qq.com/s/4Tg_NsXS8Z4DQPBIxwJplg
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### 空间复杂度
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O(n)

‎src/data-types/index.js‎

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/* eslint no-var: 0, no-unused-vars: 0, prefer-const: 0 */
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// number
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var nine = 9;

‎ts/data-types/index.ts‎

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/* eslint no-var: 0, no-unused-vars: 0, prefer-const: 0 */
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// number
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var nine = 9;
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const three: number = 3;
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let two: number = 2;
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// boolean
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const bool: boolean = false;
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// 命名名称必须有效,改为如下
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const decThree: number = 3;
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let decTwo: number = 2;
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let testa: number = 2;
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// boolean
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let isDone: boolean = false;
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// string
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const city: string = 'shanghai';
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// null
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let nul: null = null;
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// undefined
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let empty;
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// let bigInter = 23142314231412345663451234n;

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