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Commit 57960e2

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fix(book): multiple broken links and bump epub version
fixes amejiarosario#60 
1 parent ca119f2 commit 57960e2

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+12
-17
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‎book/A-time-complexity-cheatsheet.asc

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[appendix]
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[[a-time-complexity-cheatsheet]]
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== Cheatsheet
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== Cheatsheet [[a-time-complexity-cheatsheet]]
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This section summerize what we are going to cover in the rest of this book.
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‎book/B-self-balancing-binary-search-trees.asc

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[appendix]
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[[b-self-balancing-binary-search-trees]]
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== Self-balancing Binary Search Trees
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== Self-balancing Binary Search Trees [[b-self-balancing-binary-search-trees]]
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Binary Search Trees (BST) are an excellent data structure to find elements very fast _O(log n)_.
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However, when the BST branches have different branch sizes, then the performance suffers.
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To be more specific we rotated node `1` to the left to balance the tree.
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Let's examine all the possible rotation we can do to balance a tree.
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[[tree-rotations]]
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=== Tree Rotations
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=== Tree Rotations [[tree-rotations]]
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(((Tree Rotations)))
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We can do single rotations left and right and also we can do double rotations.
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Let's go one by one.

‎book/C-AVL-tree.asc

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[appendix]
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[[c-avl-tree]]
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== AVL Tree
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== AVL Tree [[c-avl-tree]]
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(((AVL Tree)))
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(((Tree, AVL)))
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AVL Tree is named after their inventors (**A**delson-**V**elsky and **L**andis).
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The first thing we do is to see if one subtree is longer than the other.
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If so, then we check the children balance to determine if need a single or double rotation and in which direction.
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You can review <<b-self-balancing-binary-search-trees#tree-rotations>> in case you want a refresher.
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You can review <<tree-rotations>> in case you want a refresher.

‎book/config

Submodule config updated from f657e9b to 8d7eb9c

‎book/content/part02/array-vs-list-vs-queue-vs-stack.asc

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|===
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.2+.^s| Data Structure 2+^s| Searching By 3+^s| Inserting at the 3+^s| Deleting from .2+.^s| Space
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^|_Index/Key_ ^|_Value_ ^|_beginning_ ^|_middle_ ^|_end_ ^|_beginning_ ^|_middle_ ^|_end_
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| <<part02-linear-data-structures#array>> ^|O(1) ^|O(n) ^|O(n) ^|O(n) ^|O(1) ^|O(n) ^|O(n) ^|O(1) ^|O(n)
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| <<array-chap>> ^|O(1) ^|O(n) ^|O(n) ^|O(n) ^|O(1) ^|O(n) ^|O(n) ^|O(1) ^|O(n)
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| <<part02-linear-data-structures#singly-linked-list>> ^|O(n) ^|O(n) ^|O(1) ^|O(n) ^|*O(n)* ^|O(1) ^|O(n) ^|*O(n)* ^|O(n)
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| <<part02-linear-data-structures#doubly-linked-list>> ^|O(n) ^|O(n) ^|O(1) ^|O(n) ^|*O(1)* ^|O(1) ^|O(n) ^|*O(1)* ^|O(n)
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| <<part02-linear-data-structures#stack>> ^|- ^|- ^|- ^|- ^|O(1) ^|- ^|- ^|O(1) ^|O(n)

‎book/content/part03/map.asc

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The attractive part of Maps is that they are very performant usually *O(1)* or *O(log n)* depending on the implementation. We can implement the maps using two different underlying data structures:
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* *HashMap*: it’s a map implementation using an *array* and a *hash function*. The job of the hash function is to convert the `key` into an index that maps to the `value`. Optimized HashMap can have an average runtime of *O(1)*.
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* *TreeMap*: it’s a map implementation that uses a self-balanced Binary Search Tree (like <<c-avl-tree#>>). The BST nodes store the key, and the value and nodes are sorted by key guaranteeing an *O(log n)* look up.
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* *TreeMap*: it’s a map implementation that uses a self-balanced Binary Search Tree (like <<c-avl-tree>>). The BST nodes store the key, and the value and nodes are sorted by key guaranteeing an *O(log n)* look up.
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<<<
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include::hashmap.asc[]

‎book/content/part03/time-complexity-graph-data-structures.asc

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.2+.^s| Data Structure 2+^s| Searching By .2+^.^s| Insert .2+^.^s| Delete .2+^.^s| Space Complexity
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^|_Index/Key_ ^|_Value_
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| <<part03-graph-data-structures#bst, BST (unbalanced)>> ^|- ^|O(n) ^|O(n) ^|O(n) ^|O(n)
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| <<b-self-balancing-binary-search-trees#, BST (balanced)>> ^|- ^|O(log n) ^|O(log n) ^|O(log n) ^|O(n)
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| <<b-self-balancing-binary-search-trees, BST (balanced)>> ^|- ^|O(log n) ^|O(log n) ^|O(log n) ^|O(n)
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| Hash Map (naïve) ^|O(n) ^|O(n) ^|O(n) ^|O(n) ^|O(n)
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| <<part03-graph-data-structures#hashmap, HashMap>> (optimized) ^|O(1) ^|O(n) ^|O(1)* ^|O(1) ^|O(n)
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| <<part03-graph-data-structures#treemap, TreeMap>> (Red-Black Tree) ^|O(log n) ^|O(n) ^|O(log n) ^|O(log n) ^|O(n)

‎book/content/preface.asc

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=== What is in this book?
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_{doctitle}_ is a book that can be read from cover to cover, where each section builds on top of the previous one. Also, it can be used as a reference manual where developers can refresh specific topics before an interview or look for ideas to solve a problem optimally. (Check out the <<a-time-complexity-cheatsheet#,Time Complexity Cheatsheet>> and <<index#, topical index>>)
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_{doctitle}_ is a book that can be read from cover to cover, where each section builds on top of the previous one. Also, it can be used as a reference manual where developers can refresh specific topics before an interview or look for ideas to solve a problem optimally. (Check out the <<a-time-complexity-cheatsheet,Time Complexity Cheatsheet>> and <<index, topical index>>)
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This publication is designed to be concise, intending to serve software developers looking to get a firm conceptual understanding of data structures in a quick yet in-depth fashion. After reading this book, the reader should have a fundamental knowledge of algorithms, including when and where to apply it, what are the trade-offs of using one data structure over the other. The reader will then be able to make intelligent decisions about algorithms and data structures in their projects.
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‎book/index.asc

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[index]
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[[index]]
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== Index
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== Index [[index]]
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ifndef::backend-pdf[Topical index only available on the PDF version.]

‎book/part02-linear-data-structures.asc

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Even though in your day-to-day, you might not need to re-implementing them, knowing how they work internally would help you know when to use one over the other or even tweak them to create a new one. We are going to explore the most common data structures' time and space complexity.
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.In this part we are going to learn about the following linear data structures:
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- <<part02-linear-data-structures#array>>
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- <<array-chap>>
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- <<part02-linear-data-structures#linked-list>>
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- <<part02-linear-data-structures#stack>>
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- <<part02-linear-data-structures#queue>>

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