Merge pull request #1 from trekhleb/master

Update fork

Author: juanjofg

.gitignore

@@ -1,3 +1,5 @@
 node_modules
 .idea
 coverage
+.vscode
+.DS_Store

.travis.yml

@@ -3,8 +3,11 @@ dist: trusty
 language: node_js
 node_js:
   - node
+install:
+  - npm install -g codecov
+  - npm install
 script:
   - npm run ci
-  - npm run codecov
+  - codecov
 notifications:
   email: false

CONTRIBUTING.md

@@ -1,5 +1,25 @@
 ## Contributing
 
+**General Rules**
+
 - As much as possible, try to follow the existing format of markdown and code.
 - Don't forget to run `npm run lint` and `npm test` before submitting pull requests.
 - Make sure that **100%** of your code is covered by tests.
+
+**Contributing New Translation**
+
+- Create new `README.xx-XX.md` file with translation alongside with 
+main `README.md` file where `xx-XX` is [locale and country/region codes](http://www.lingoes.net/en/translator/langcode.htm).
+For example `en-US`, `zh-CN`, `zh-TW`, `ko-KR` etc.
+- You may also translate all other sub-folders by creating 
+related `README.xx-XX.md` files in each of them.
+
+**Contributing New Algorithms**
+
+- Make your pull requests to be **specific** and **focused**. Instead of 
+contributing "several sorting algorithms" all at once contribute them all 
+one by one separately (i.e. one pull request for "Quick Sort", another one
+for "Heap Sort" and so on).
+- Provide **README.md** for each of the algorithms **with explanations** of
+the algorithm and **with links** to further readings.
+- Describe what you do in code using **comments**.

README.es-ES.md

@@ -0,0 +1,217 @@
+# JavaScript 演算法與資料結構
+
+[![build status](https://travis-ci.org/trekhleb/javascript-algorithms.svg?branch=master)](https://travis-ci.org/trekhleb/javascript-algorithms)
+[![codecov](https://codecov.io/gh/trekhleb/javascript-algorithms/branch/master/graph/badge.svg)](https://codecov.io/gh/trekhleb/javascript-algorithms)
+
+這個知識庫包含許多 JavaScript 的資料結構與演算法的基礎範例。
+每個演算法和資料結構都有其個別的文件，內有相關的解釋以及更多相關的文章或Youtube影片連結。
+
+_Read this in other languages:_
+[_English_](https://github.com/trekhleb/javascript-algorithms/),
+[_简体中文_](README.zh-CN.md),
+[_한국어_](README.ko-KR.md),
+[_日本語_](README.ja-JP.md),
+[_Polski_](README.pl-PL.md),
+[_Français_](README.fr-FR.md),
+[_Español_](README.es-ES.md),
+[_Português_](README.pt-BR.md)
+
+## 資料結構
+
+資料結構是一個電腦用來組織和排序資料的特定方式，透過這樣的方式資料可以有效率地被讀取以及修改。更精確地說，一個資料結構是一個資料值的集合、彼此間的關係，函數或者運作可以應用於資料上。
+
+* [鏈結串列](src/data-structures/linked-list)
+* [貯列](src/data-structures/queue)
+* [堆疊](src/data-structures/stack)
+* [雜湊表](src/data-structures/hash-table)
+* [堆](src/data-structures/heap)
+* [優先貯列](src/data-structures/priority-queue)
+* [字典樹](src/data-structures/trie)
+* [樹](src/data-structures/tree)
+  * [二元搜尋樹](src/data-structures/tree/binary-search-tree)
+  * [AVL樹](src/data-structures/tree/avl-tree)
+  * [紅黑樹](src/data-structures/tree/red-black-tree)
+* [圖](src/data-structures/graph) (有向跟無向皆包含)
+* [互斥集](src/data-structures/disjoint-set)
+
+## 演算法
+
+演算法是一個如何解決一類問題的非模糊規格。演算法是一個具有精確地定義了一系列運作的規則的集合
+
+### 演算法議題分類
+
+* **數學類**
+  * [階層](src/algorithms/math/factorial)
+  * [費伯納西數列](src/algorithms/math/fibonacci)
+  * [Primality Test](src/algorithms/math/primality-test) (排除法)
+  * [歐幾里得算法](src/algorithms/math/euclidean-algorithm) - 計算最大公因數 (GCD)
+  * [最小公倍數](src/algorithms/math/least-common-multiple) (LCM)
+  * [整數拆分](src/algorithms/math/integer-partition)
+* **集合**
+  * [笛卡爾積](src/algorithms/sets/cartesian-product) - 多個集合的乘積
+  * [冪集合](src/algorithms/sets/power-set) - 所有集合的子集合
+  * [排列](src/algorithms/sets/permutations) (有/無重複)
+  * [组合](src/algorithms/sets/combinations) (有/無重複)
+  * [洗牌算法](src/algorithms/sets/fisher-yates) - 隨機置換一有限序列
+  * [最長共同子序列](src/algorithms/sets/longest-common-subsequence) (LCS)
+  * [最長遞增子序列](src/algorithms/sets/longest-increasing-subsequence)
+  * [Shortest Common Supersequence](src/algorithms/sets/shortest-common-supersequence) (SCS)
+  * [背包問題](src/algorithms/sets/knapsack-problem) - "0/1" and "Unbound" ones
+  * [最大子序列問題](src/algorithms/sets/maximum-subarray) - 暴力法以及動態編程的(Kadane's)版本
+* **字串**
+  * [萊文斯坦距離](src/algorithms/string/levenshtein-distance) - 兩序列間的最小編輯距離
+  * [漢明距離](src/algorithms/string/hamming-distance) - number of positions at which the symbols are different
+  * [KMP 演算法](src/algorithms/string/knuth-morris-pratt) - 子字串搜尋
+  * [Rabin Karp 演算法](src/algorithms/string/rabin-karp) - 子字串搜尋
+  * [最長共通子序列](src/algorithms/string/longest-common-substring)
+* **搜尋**
+  * [二元搜尋](src/algorithms/search/binary-search)
+* **排序**
+  * [氣泡排序](src/algorithms/sorting/bubble-sort)
+  * [選擇排序](src/algorithms/sorting/selection-sort)
+  * [插入排序](src/algorithms/sorting/insertion-sort)
+  * [堆排序](src/algorithms/sorting/heap-sort)
+  * [合併排序](src/algorithms/sorting/merge-sort)
+  * [快速排序](src/algorithms/sorting/quick-sort)
+  * [希爾排序](src/algorithms/sorting/shell-sort)
+* **樹**
+  * [深度優先搜尋](src/algorithms/tree/depth-first-search) (DFS)
+  * [廣度優先搜尋](src/algorithms/tree/breadth-first-search) (BFS)
+* **圖**
+  * [深度優先搜尋](src/algorithms/graph/depth-first-search) (DFS)
+  * [廣度優先搜尋](src/algorithms/graph/breadth-first-search) (BFS)
+  * [Dijkstra 演算法](src/algorithms/graph/dijkstra) - 找到所有圖頂點的最短路徑
+  * [Bellman-Ford 演算法](src/algorithms/graph/bellman-ford) - 找到所有圖頂點的最短路徑
+  * [Detect Cycle](src/algorithms/graph/detect-cycle) - for both directed and undirected graphs (DFS and Disjoint Set based versions)
+  * [Prim’s 演算法](src/algorithms/graph/prim) - finding Minimum Spanning Tree (MST) for weighted undirected graph
+  * [Kruskal’s 演算法](src/algorithms/graph/kruskal) - finding Minimum Spanning Tree (MST) for weighted undirected graph
+  * [拓撲排序](src/algorithms/graph/topological-sorting) - DFS method
+  * [關節點](src/algorithms/graph/articulation-points) - Tarjan's algorithm (DFS based)
+  * [橋](src/algorithms/graph/bridges) - DFS based algorithm
+  * [尤拉路徑及尤拉環](src/algorithms/graph/eulerian-path) - Fleury's algorithm - Visit every edge exactly once
+  * [漢彌爾頓環](src/algorithms/graph/hamiltonian-cycle) - Visit every vertex exactly once
+  * [強連通組件](src/algorithms/graph/strongly-connected-components) - Kosaraju's algorithm
+  * [旅行推銷員問題](src/algorithms/graph/travelling-salesman) - shortest possible route that visits each city and returns to the origin city
+  * [Floyd-Warshall algorithm](src/algorithms/graph/floyd-warshall) - 一次循环可以找出所有頂點之间的最短路徑
+* **未分類**
+  * [河內塔](src/algorithms/uncategorized/hanoi-tower)
+  * [N-皇后問題](src/algorithms/uncategorized/n-queens)
+  * [騎士走棋盤](src/algorithms/uncategorized/knight-tour)
+
+### 演算法範型
+
+演算法的範型是一個泛用方法或設計一類底層演算法的方式。它是一個比演算法的概念更高階的抽象化，就像是演算法是比電腦程式更高階的抽象化。
+
+* **暴力法** - 尋遍所有的可能解然後選取最好的解
+  * [最大子序列](src/algorithms/sets/maximum-subarray)
+  * [旅行推銷員問題](src/algorithms/graph/travelling-salesman) - shortest possible route that visits each city and returns to the origin city
+* **貪婪法** - choose the best option at the current time, without any consideration for the future
+  * [未定背包問題](src/algorithms/sets/knapsack-problem)
+  * [Dijkstra 演算法](src/algorithms/graph/dijkstra) - 找到所有圖頂點的最短路徑
+  * [Prim’s 演算法](src/algorithms/graph/prim) - finding Minimum Spanning Tree (MST) for weighted undirected graph
+  * [Kruskal’s 演算法](src/algorithms/graph/kruskal) - finding Minimum Spanning Tree (MST) for weighted undirected graph
+* **分治法** - divide the problem into smaller parts and then solve those parts
+  * [二元搜尋](src/algorithms/search/binary-search)
+  * [河內塔](src/algorithms/uncategorized/hanoi-tower)
+  * [歐幾里得演算法](src/algorithms/math/euclidean-algorithm) - calculate the Greatest Common Divisor (GCD)
+  * [排列](src/algorithms/sets/permutations) (有/無重複)
+  * [组合](src/algorithms/sets/combinations) (有/無重複)
+  * [合併排序](src/algorithms/sorting/merge-sort)
+  * [快速排序](src/algorithms/sorting/quick-sort)
+  * [樹深度優先搜尋](src/algorithms/tree/depth-first-search) (DFS)
+  * [圖深度優先搜尋](src/algorithms/graph/depth-first-search) (DFS)
+* **動態編程** - build up to a solution using previously found sub-solutions
+  * [費伯納西數列](src/algorithms/math/fibonacci)
+  * [萊溫斯坦距離](src/algorithms/string/levenshtein-distance) - minimum edit distance between two sequences
+  * [最長共同子序列](src/algorithms/sets/longest-common-subsequence) (LCS)
+  * [最長共同子字串](src/algorithms/string/longest-common-substring)
+  * [最長遞增子序列](src/algorithms/sets/longest-increasing-subsequence)
+  * [最短共同子序列](src/algorithms/sets/shortest-common-supersequence)
+  * [0/1背包問題](src/algorithms/sets/knapsack-problem)
+  * [整數拆分](src/algorithms/math/integer-partition)
+  * [最大子序列](src/algorithms/sets/maximum-subarray)
+  * [Bellman-Ford 演算法](src/algorithms/graph/bellman-ford) - finding shortest path to all graph vertices
+* **回溯法** - 用類似暴力法來嘗試產生所有可能解，但每次只在能滿足所有測試條件，且只有繼續產生子序列方案來產生的解決方案。否則回溯並尋找不同路徑的解決方案。
+  * [漢彌爾頓迴路](src/algorithms/graph/hamiltonian-cycle) - Visit every vertex exactly once
+  * [N-皇后問題](src/algorithms/uncategorized/n-queens)
+  * [騎士走棋盤](src/algorithms/uncategorized/knight-tour)
+* **Branch & Bound**
+
+## 如何使用本知識庫
+
+**安裝所有必須套件**
+
+```
+npm install
+```
+
+**執行所有測試**
+```
+npm test
+```
+
+**以名稱執行該測試**
+```
+npm test -- 'LinkedList'
+```
+**練習場**
+
+你可以透過在`./src/playground/playground.js`裡面的檔案練習資料結構以及演算法，並且撰寫在`./src/playground/__test__/playground.test.js`裡面的測試程式。
+
+接著直接執行下列的指令來測試你練習的 code 是否如預期運作：
+
+```
+npm test -- 'playground'
+```
+
+## 有用的資訊
+
+### 參考
+
+[▶ Data Structures and Algorithms on YouTube](https://www.youtube.com/playlist?list=PLLXdhg_r2hKA7DPDsunoDZ-Z769jWn4R8)
+
+### 大 O 標記
+
+特別用大 O 標記演算法增長度的排序。
+
+![Big O 表](./assets/big-o-graph.png)
+
+資料來源: [Big O Cheat Sheet](http://bigocheatsheet.com/).
+
+下列列出幾個常用的 Big O 標記以及其不同大小資料量輸入後的運算效能比較。
+
+| Big O 標記     | 10個資料量需花費的時間       | 100個資料量需花費的時間       | 1000個資料量需花費的時間        |
+| -------------- | ---------------------------- | ----------------------------- | ------------------------------- |
+| **O(1)**       | 1                            | 1                             | 1                               |
+| **O(log N)**   | 3                            | 6                             | 9                               |
+| **O(N)**       | 10                           | 100                           | 1000                            |
+| **O(N log N)** | 30                           | 600                           | 9000                            |
+| **O(N^2)**     | 100                          | 10000                         | 1000000                         |
+| **O(2^N)**     | 1024                         | 1.26e+29                      | 1.07e+301                       |
+| **O(N!)**      | 3628800                      | 9.3e+157                      | 4.02e+2567                      |
+
+### 資料結構運作複雜度
+
+| 資料結構                | 存取      | 搜尋      | 插入      | 刪除      |
+| ----------------------- | :-------: | :-------: | :-------: | :-------: |
+| **陣列**                | 1         | n         | n         | n         |
+| **堆疊**                | n         | n         | 1         | 1         |
+| **貯列**                | n         | n         | 1         | 1         |
+| **鏈結串列**            | n         | n         | 1         | 1         |
+| **雜湊表**              | -         | n         | n         | n         |
+| **二元搜尋樹**          | n         | n         | n         | n         |
+| **B-Tree**              | log(n)    | log(n)    | log(n)    | log(n)    |
+| **紅黑樹**              | log(n)    | log(n)    | log(n)    | log(n)    |
+| **AVL Tree**            | log(n)    | log(n)    | log(n)    | log(n)    |
+
+### 陣列排序演算法複雜度
+
+| 名稱                   | 最佳      | 平均      | 最差          | 記憶體    | 穩定      |
+| ---------------------- | :-------: | :-------: | :-----------: | :-------: | :-------: |
+| **氣派排序**           | n         | n^2       | n^2           | 1         | Yes       |
+| **插入排序**           | n         | n^2       | n^2           | 1         | Yes       |
+| **選擇排序**           | n^2       | n^2       | n^2           | 1         | No        |
+| **Heap 排序**          | n log(n)  | n log(n)  | n log(n)      | 1         | No        |
+| **合併排序**           | n log(n)  | n log(n)  | n log(n)      | n         | Yes       |
+| **快速排序**           | n log(n)  | n log(n)  | n^2           | log(n)    | No        |
+| **希爾排序**           | n log(n)  | 由gap sequence決定   | n (log(n))^2  | 1         | No        |

README.fr-FR.md

@@ -1,5 +1,28 @@
 module.exports = {
+  // The bail config option can be used here to have Jest stop running tests after
+  // the first failure.
+  bail: false,
+
+  // Indicates whether each individual test should be reported during the run.
   verbose: false,
+
+  // Indicates whether the coverage information should be collected while executing the test
   collectCoverage: false,
+
+  // The directory where Jest should output its coverage files.
   coverageDirectory: './coverage/',
+
+  // If the test path matches any of the patterns, it will be skipped.
+  testPathIgnorePatterns: ['<rootDir>/node_modules/'],
+
+  // If the file path matches any of the patterns, coverage information will be skipped.
+  coveragePathIgnorePatterns: ['<rootDir>/node_modules/'],
+
+  // The pattern Jest uses to detect test files.
+  testRegex: '(/__tests__/.*|(\\.|/)(test|spec))\\.jsx?$',
+
+  // This option sets the URL for the jsdom environment.
+  // It is reflected in properties such as location.href.
+  // @see: https://github.com/facebook/jest/issues/6769
+  testURL: 'http://localhost/',
 };