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Java 9 Data Structures and Algorithms

You're reading from   Java 9 Data Structures and Algorithms A step-by-step guide to data structures and algorithms

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781785889349
Length 340 pages
Edition 1st Edition
Languages
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Author (1):
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Debasish Ray Chawdhuri Debasish Ray Chawdhuri
Author Profile Icon Debasish Ray Chawdhuri
Debasish Ray Chawdhuri
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Toc

Table of Contents (13) Chapters Close

Preface 1. Why Bother? – Basic FREE CHAPTER 2. Cogs and Pulleys – Building Blocks 3. Protocols – Abstract Data Types 4. Detour – Functional Programming 5. Efficient Searching – Binary Search and Sorting 6. Efficient Sorting – quicksort and mergesort 7. Concepts of Tree 8. More About Search – Search Trees and Hash Tables 9. Advanced General Purpose Data Structures 10. Concepts of Graph 11. Reactive Programming Index

Traversal of a graph


The traversal of a graph is the graph's equivalent of the traversal of a tree, as discussed in an earlier chapter. Just as in the case of a tree, we can traverse either breadth-first or depth-first. However, unlike a tree, a graph can reach all the vertices without going through the edges. This makes it necessary to consider the traversal of all the edges and vertices separately. Another thing is that a graph has no designated root, so we can start from any particular vertex. Finally, since a graph may not be connected, we may not be able to traverse all the vertices/edges, starting from one single vertex. This is achieved by performing the traversal repeatedly, starting each time from any vertex that has not been visited yet already. This is a simple extension of the basic breadth-first or depth-first traversal that we are going to discuss here.

First, let's discuss visiting vertices using both the breadth-first and depth-first search. It involves maintaining two collections...

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