diff --git a/README-zh-Hant.md b/README-zh-Hant.md
index 47a8f0f9..fba5e12c 100755
--- a/README-zh-Hant.md
+++ b/README-zh-Hant.md
@@ -50,7 +50,7 @@
 * [如何处理一个系统设计面试题](#如何处理一个系统设计面试题)
 * [系统设计面试题，**含解答**](#系统设计面试题和解答)
 * [面向对象设计面试题，**含解答**](#面向对象设计面试问题及解答)
-* [其他系统设计面试题](#额外的系统设计面试问题)
+* [其它系统设计面试题](#其它系统设计面试题)
 
 ## 抽认卡
 
@@ -178,14 +178,14 @@
 * [附录](#附录)
     * [2 的次方表](#2-的次方表)
     * [每个程序员都应该知道的延迟数](#每个程序员都应该知道的延迟数)
-    * [其他系统设计面试题](#额外的系统设计面试问题)
-    * [真实架构](#真实的设计架构)
-    * [公司架构](#公司的系统架构)
+    * [其它系统设计面试题](#其它系统设计面试题)
+    * [真实架构](#真实架构)
+    * [公司的系统架构](#公司的系统架构)
     * [公司工程博客](#公司工程博客)
 * [开发中](#正在开发中)
-* [致谢](#Credits)
+* [致谢](#致谢)
 * [联系方式](#联系方式)
-* [许可](#License)
+* [许可](#许可)
 
 ## 学习指引
 
@@ -217,11 +217,11 @@
 | ---------------------------------------- | ---- | ---- | ---- |
 | 阅读 [系统设计主题](#系统设计主题的索引) 以获得一个关于系统如何工作的宽泛的认识 | :+1: | :+1: | :+1: |
 | 阅读一些你要面试的[公司工程博客](#公司工程博客)的文章            | :+1: | :+1: | :+1: |
-| 阅读 [真实世界的架构](#真实的设计架构)                   | :+1: | :+1: | :+1: |
+| 阅读 [真实世界的架构](#真实架构)                   | :+1: | :+1: | :+1: |
 | 复习 [如何处理一个系统设计面试题](#如何处理一个系统设计面试题)       | :+1: | :+1: | :+1: |
 | 完成 [系统设计面试题和解答](#系统设计面试题和解答)             | 一些   | 很多   | 大部分  |
 | 完成 [面向对象设计面试题和解答](#面向对象设计面试问题及解答)        | 一些   | 很多   | 大部分  |
-| 复习 [其他系统设计面试题和解答](#额外的系统设计面试问题)          | 一些   | 很多   | 大部分  |
+| 复习 [其它系统设计面试题](#其它系统设计面试题)          | 一些   | 很多   | 大部分  |
 ## 如何处理一个系统设计面试题
 
 > 如何处理一个系统设计面试题。
@@ -1612,7 +1612,7 @@ Notes
 * [关于建设大型分布式系统的的设计方案、课程和建议](http://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf)
 * [关于建设大型可拓展分布式系统的软件工程咨询](https://static.googleusercontent.com/media/research.google.com/en//people/jeff/stanford-295-talk.pdf)
 
-### 额外的系统设计面试问题
+### 其它系统设计面试题
 
 > 常见的系统设计面试问题，给出了如何解决的方案链接
 
@@ -1641,7 +1641,7 @@ Notes
 | 设计一个垃圾回收系统              | [stuffwithstuff.com](http://journal.stuffwithstuff.com/2013/12/08/babys-first-garbage-collector/)<br/>[washington.edu](http://courses.cs.washington.edu/courses/csep521/07wi/prj/rick.pdf) |
 | 添加更多的系统设计问题             | [Contribute](#contributing)              |
 
-### 真实的设计架构
+### 真实架构
 
 > 关于现实中真实的系统是怎么设计的文章。
 
@@ -1659,54 +1659,54 @@ Notes
 
 | 类型              | 系统                                       | 引用                                       |
 | --------------- | ---------------------------------------- | ---------------------------------------- |
-| Data processing | **MapReduce** - Distributed data processing from Google | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/mapreduce-osdi04.pdf) |
-| Data processing | **Spark** - Distributed data processing from Databricks | [slideshare.net](http://www.slideshare.net/AGrishchenko/apache-spark-architecture) |
-| Data processing | **Storm** - Distributed data processing from Twitter | [slideshare.net](http://www.slideshare.net/previa/storm-16094009) |
+| Data processing | **MapReduce** - Google的分布式数据处理 | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/mapreduce-osdi04.pdf) |
+| Data processing | **Spark** - Databricks 的分布式数据处理 | [slideshare.net](http://www.slideshare.net/AGrishchenko/apache-spark-architecture) |
+| Data processing | **Storm** - Twitter 的分布式数据处理 | [slideshare.net](http://www.slideshare.net/previa/storm-16094009) |
 |                 |                                          |                                          |
-| Data store      | **Bigtable** - Distributed column-oriented database from Google | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/chang06bigtable.pdf) |
-| Data store      | **HBase** - Open source implementation of Bigtable | [slideshare.net](http://www.slideshare.net/alexbaranau/intro-to-hbase) |
-| Data store      | **Cassandra** - Distributed column-oriented database from Facebook | [slideshare.net](http://www.slideshare.net/planetcassandra/cassandra-introduction-features-30103666) |
-| Data store      | **DynamoDB** - Document-oriented database from Amazon | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/decandia07dynamo.pdf) |
-| Data store      | **MongoDB** - Document-oriented database | [slideshare.net](http://www.slideshare.net/mdirolf/introduction-to-mongodb) |
-| Data store      | **Spanner** - Globally-distributed database from Google | [research.google.com](http://research.google.com/archive/spanner-osdi2012.pdf) |
-| Data store      | **Memcached** - Distributed memory caching system | [slideshare.net](http://www.slideshare.net/oemebamo/introduction-to-memcached) |
-| Data store      | **Redis** - Distributed memory caching system with persistence and value types | [slideshare.net](http://www.slideshare.net/dvirsky/introduction-to-redis) |
+| Data store      | **Bigtable** - Google 的列式数据库 | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/chang06bigtable.pdf) |
+| Data store      | **HBase** - Bigtable 的开源实现 | [slideshare.net](http://www.slideshare.net/alexbaranau/intro-to-hbase) |
+| Data store      | **Cassandra** - Facebook 的列式数据库 | [slideshare.net](http://www.slideshare.net/planetcassandra/cassandra-introduction-features-30103666) |
+| Data store      | **DynamoDB** - Amazon 的文档数据库 | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/decandia07dynamo.pdf) |
+| Data store      | **MongoDB** - 文档数据库 | [slideshare.net](http://www.slideshare.net/mdirolf/introduction-to-mongodb) |
+| Data store      | **Spanner** - Google 的全球分布数据库 | [research.google.com](http://research.google.com/archive/spanner-osdi2012.pdf) |
+| Data store      | **Memcached** - 分布式内存缓存系统 | [slideshare.net](http://www.slideshare.net/oemebamo/introduction-to-memcached) |
+| Data store      | **Redis** - 能够持久化及具有值类型的分布式内存缓存系统 | [slideshare.net](http://www.slideshare.net/dvirsky/introduction-to-redis) |
 |                 |                                          |                                          |
-| File system     | **Google File System (GFS)** - Distributed file system | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/gfs-sosp2003.pdf) |
-| File system     | **Hadoop File System (HDFS)** - Open source implementation of GFS | [apache.org](https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html) |
+| File system     | **Google File System (GFS)** - 分布式文件系统 | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/gfs-sosp2003.pdf) |
+| File system     | **Hadoop File System (HDFS)** - GFS 的开源实现 | [apache.org](https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html) |
 |                 |                                          |                                          |
-| Misc            | **Chubby** - Lock service for loosely-coupled distributed systems from Google | [research.google.com](http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/archive/chubby-osdi06.pdf) |
-| Misc            | **Dapper** - Distributed systems tracing infrastructure | [research.google.com](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36356.pdf) |
-| Misc            | **Kafka** - Pub/sub message queue from LinkedIn | [slideshare.net](http://www.slideshare.net/mumrah/kafka-talk-tri-hug) |
-| Misc            | **Zookeeper** - Centralized infrastructure and services enabling synchronization | [slideshare.net](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper) |
-|                 | Add an architecture                      | [Contribute](#contributing)              |
+| Misc            | **Chubby** - Google 的分布式系统的低耦合锁服务 | [research.google.com](http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/archive/chubby-osdi06.pdf) |
+| Misc            | **Dapper** - 分布式系统跟踪基础设施 | [research.google.com](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36356.pdf) |
+| Misc            | **Kafka** - LinkedIn 的发布订阅消息系统 | [slideshare.net](http://www.slideshare.net/mumrah/kafka-talk-tri-hug) |
+| Misc            | **Zookeeper** - 集中的基础架构和协调服务 | [slideshare.net](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper) |
+|                 | 添加更多                      | [Contribute](#contributing)              |
 
 ### 公司的系统架构
 
 | Company        | Reference(s)                             |
 | -------------- | ---------------------------------------- |
-| Amazon         | [Amazon architecture](http://highscalability.com/amazon-architecture) |
-| Cinchcast      | [Producing 1,500 hours of audio every day](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html) |
-| DataSift       | [Realtime datamining At 120,000 tweets per second](http://highscalability.com/blog/2011/11/29/datasift-architecture-realtime-datamining-at-120000-tweets-p.html) |
-| DropBox        | [How we've scaled Dropbox](https://www.youtube.com/watch?v=PE4gwstWhmc) |
-| ESPN           | [Operating At 100,000 duh nuh nuhs per second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html) |
-| Google         | [Google architecture](http://highscalability.com/google-architecture) |
-| Instagram      | [14 million users, terabytes of photos](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)<br/>[What powers Instagram](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances) |
-| Justin.tv      | [Justin.Tv's live video broadcasting architecture](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html) |
-| Facebook       | [Scaling memcached at Facebook](https://cs.uwaterloo.ca/~brecht/courses/854-Emerging-2014/readings/key-value/fb-memcached-nsdi-2013.pdf)<br/>[TAO: Facebook’s distributed data store for the social graph](https://cs.uwaterloo.ca/~brecht/courses/854-Emerging-2014/readings/data-store/tao-facebook-distributed-datastore-atc-2013.pdf)<br/>[Facebook’s photo storage](https://www.usenix.org/legacy/event/osdi10/tech/full_papers/Beaver.pdf) |
-| Flickr         | [Flickr architecture](http://highscalability.com/flickr-architecture) |
-| Mailbox        | [From 0 to one million users in 6 weeks](http://highscalability.com/blog/2013/6/18/scaling-mailbox-from-0-to-one-million-users-in-6-weeks-and-1.html) |
-| Pinterest      | [From 0 To 10s of billions of page views a month](http://highscalability.com/blog/2013/4/15/scaling-pinterest-from-0-to-10s-of-billions-of-page-views-a.html)<br/>[18 million visitors, 10x growth, 12 employees](http://highscalability.com/blog/2012/5/21/pinterest-architecture-update-18-million-visitors-10x-growth.html) |
-| Playfish       | [50 million monthly users and growing](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html) |
-| PlentyOfFish   | [PlentyOfFish architecture](http://highscalability.com/plentyoffish-architecture) |
-| Salesforce     | [How they handle 1.3 billion transactions a day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html) |
-| Stack Overflow | [Stack Overflow architecture](http://highscalability.com/blog/2009/8/5/stack-overflow-architecture.html) |
-| TripAdvisor    | [40M visitors, 200M dynamic page views, 30TB data](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html) |
-| Tumblr         | [15 billion page views a month](http://highscalability.com/blog/2012/2/13/tumblr-architecture-15-billion-page-views-a-month-and-harder.html) |
-| Twitter        | [Making Twitter 10000 percent faster](http://highscalability.com/scaling-twitter-making-twitter-10000-percent-faster)<br/>[Storing 250 million tweets a day using MySQL](http://highscalability.com/blog/2011/12/19/how-twitter-stores-250-million-tweets-a-day-using-mysql.html)<br/>[150M active users, 300K QPS, a 22 MB/S firehose](http://highscalability.com/blog/2013/7/8/the-architecture-twitter-uses-to-deal-with-150m-active-users.html)<br/>[Timelines at scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)<br/>[Big and small data at Twitter](https://www.youtube.com/watch?v=5cKTP36HVgI)<br/>[Operations at Twitter: scaling beyond 100 million users](https://www.youtube.com/watch?v=z8LU0Cj6BOU) |
-| Uber           | [How Uber scales their real-time market platform](http://highscalability.com/blog/2015/9/14/how-uber-scales-their-real-time-market-platform.html) |
-| WhatsApp       | [The WhatsApp architecture Facebook bought for $19 billion](http://highscalability.com/blog/2014/2/26/the-whatsapp-architecture-facebook-bought-for-19-billion.html) |
-| YouTube        | [YouTube scalability](https://www.youtube.com/watch?v=w5WVu624fY8)<br/>[YouTube architecture](http://highscalability.com/youtube-architecture) |
+| Amazon         | [Amazon 的架构](http://highscalability.com/amazon-architecture) |
+| Cinchcast      | [每天产生 1500 小时的音频](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html) |
+| DataSift       | [每秒实时挖掘 120000 条 tweet](http://highscalability.com/blog/2011/11/29/datasift-architecture-realtime-datamining-at-120000-tweets-p.html) |
+| DropBox        | [我们如何缩放 Dropbox](https://www.youtube.com/watch?v=PE4gwstWhmc) |
+| ESPN           | [每秒操作 100000 次](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html) |
+| Google         | [Google 的架构](http://highscalability.com/google-architecture) |
+| Instagram      | [1400 万用户，达到兆级别的照片存储](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)<br/>[是什么在驱动 Instagram](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances) |
+| Justin.tv      | [Justin.Tv 的直播广播架构](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html) |
+| Facebook       | [Facebook 的可扩展 memcached](https://cs.uwaterloo.ca/~brecht/courses/854-Emerging-2014/readings/key-value/fb-memcached-nsdi-2013.pdf)<br/>[TAO: Facebook 社交图的分布式数据存储](https://cs.uwaterloo.ca/~brecht/courses/854-Emerging-2014/readings/data-store/tao-facebook-distributed-datastore-atc-2013.pdf)<br/>[Facebook 的图片存储](https://www.usenix.org/legacy/event/osdi10/tech/full_papers/Beaver.pdf) |
+| Flickr         | [Flickr 的架构](http://highscalability.com/flickr-architecture) |
+| Mailbox        | [在 6 周内从 0 到 100 万用户](http://highscalability.com/blog/2013/6/18/scaling-mailbox-from-0-to-one-million-users-in-6-weeks-and-1.html) |
+| Pinterest      | [从零到每月数十亿的浏览量](http://highscalability.com/blog/2013/4/15/scaling-pinterest-from-0-to-10s-of-billions-of-page-views-a.html)<br/>[1800 万访问用户，10 倍增长，12 名员工](http://highscalability.com/blog/2012/5/21/pinterest-architecture-update-18-million-visitors-10x-growth.html) |
+| Playfish       | [月用户量 5000 万并在不断增长](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html) |
+| PlentyOfFish   | [PlentyOfFish 的架构](http://highscalability.com/plentyoffish-architecture) |
+| Salesforce     | [他们每天如何处理 13 亿笔交易](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html) |
+| Stack Overflow | [Stack Overflow 的架构](http://highscalability.com/blog/2009/8/5/stack-overflow-architecture.html) |
+| TripAdvisor    | [40M 访问者，200M 页面浏览量，30TB 数据](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html) |
+| Tumblr         | [每月 150 亿的浏览量](http://highscalability.com/blog/2012/2/13/tumblr-architecture-15-billion-page-views-a-month-and-harder.html) |
+| Twitter        | [Making Twitter 10000 percent faster](http://highscalability.com/scaling-twitter-making-twitter-10000-percent-faster)<br/>[每天使用 MySQL 存储2.5亿条 tweet](http://highscalability.com/blog/2011/12/19/how-twitter-stores-250-million-tweets-a-day-using-mysql.html)<br/>[150M 活跃用户，300K QPS，22 MB/S 的防火墙](http://highscalability.com/blog/2013/7/8/the-architecture-twitter-uses-to-deal-with-150m-active-users.html)<br/>[可扩展时间表](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)<br/>[Twitter 的大小数据](https://www.youtube.com/watch?v=5cKTP36HVgI)<br/>[Twitter 的行为：规模超过 1 亿用户](https://www.youtube.com/watch?v=z8LU0Cj6BOU) |
+| Uber           | [Uber 如何扩展自己的实时化市场](http://highscalability.com/blog/2015/9/14/how-uber-scales-their-real-time-market-platform.html) |
+| WhatsApp       | [Facebook 用 190 亿美元购买 WhatsApp 的架构](http://highscalability.com/blog/2014/2/26/the-whatsapp-architecture-facebook-bought-for-19-billion.html) |
+| YouTube        | [YouTube 的可扩展性](https://www.youtube.com/watch?v=w5WVu624fY8)<br/>[YouTube 的架构](http://highscalability.com/youtube-architecture) |
 
 ### 公司工程博客
 
@@ -1769,7 +1769,7 @@ Notes
 * 直接存储器访问（DMA）控制器
 * [Contribute](#contributing)
 
-## Credits
+## 致谢
 
 整个仓库都提供了证书和源
 
@@ -1791,7 +1791,7 @@ Notes
 
 可以在我的 [GitHub 主页](https://github.com/donnemartin)上找到我的联系方式
 
-## License
+## 许可 
 
     Creative Commons Attribution 4.0 International License (CC BY 4.0)