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Learning JavaScript Data Structures and Algorithms

You're reading from   Learning JavaScript Data Structures and Algorithms Hone your skills by learning classic data structures and algorithms in JavaScript

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Product type Paperback
Published in Jun 2016
Publisher Packt
ISBN-13 9781785285493
Length 314 pages
Edition 2nd Edition
Languages
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Author (1):
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Loiane Avancini Loiane Avancini
Author Profile Icon Loiane Avancini
Loiane Avancini
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Table of Contents (13) Chapters Close

Preface 1. JavaScript—A Quick Overview FREE CHAPTER 2. Arrays 3. Stacks 4. Queues 5. Linked Lists 6. Sets 7. Dictionaries and Hashes 8. Trees 9. Graphs 10. Sorting and Searching Algorithms 11. Patterns of Algorithm 12. Algorithm Complexity

Graph traversals


Similar to the tree data structure, we can also visit all the nodes of a graph. There are two algorithms that can be used to traverse a graph, called breadth-first search (BFS) and depth-first search (DFS). Traversing a graph can be used to find a specific vertex or a path between two vertices, to check whether the graph is connected, to check whether it contains cycles, and so on.

Before we implement the algorithms, let's try to better understand the idea of traversing a graph.

The idea of graph traversal algorithms is that we must track each vertex when we first visit it and keep track of which vertices have not yet been completely explored. For both traversal graph algorithms, we need to specify which will be the first vertex to be visited.

To completely explore a vertex, we need to look at each edge of this vertex. For each edge connected to a vertex that has not been visited yet, we will mark it as discovered and add it to the list of vertices to be visited.

In order to...

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