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Learning JavaScript Data  Structures and Algorithms

You're reading from   Learning JavaScript Data Structures and Algorithms Write complex and powerful JavaScript code using the latest ECMAScript

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788623872
Length 426 pages
Edition 3rd 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 (17) Chapters Close

Preface 1. JavaScript – A Quick Overview FREE CHAPTER 2. ECMAScript and TypeScript Overview 3. Arrays 4. Stacks 5. Queues and Deques 6. Linked Lists 7. Sets 8. Dictionaries and Hashes 9. Recursion 10. Trees 11. Binary Heap and Heap Sort 12. Graphs 13. Sorting and Searching Algorithms 14. Algorithm Designs and Techniques 15. Algorithm Complexity 16. Other Books You May Enjoy

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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