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Learning Functional Data Structures and Algorithms

You're reading from   Learning Functional Data Structures and Algorithms Learn functional data structures and algorithms for your applications and bring their benefits to your work now

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781785888731
Length 318 pages
Edition 1st Edition
Languages
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Authors (2):
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Raju Kumar Mishra Raju Kumar Mishra
Author Profile Icon Raju Kumar Mishra
Raju Kumar Mishra
Atul S. Khot Atul S. Khot
Author Profile Icon Atul S. Khot
Atul S. Khot
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Table of Contents (14) Chapters Close

Preface 1. Why Functional Programming? 2. Building Blocks FREE CHAPTER 3. Lists 4. Binary Trees 5. More List Algorithms 6. Graph Algorithms 7. Random Access Lists 8. Queues 9. Streams, Laziness, and Algorithms 10. Being Lazy - Queues and Deques 11. Red-Black Trees 12. Binomial Heaps 13. Sorting

Chapter 6.  Graph Algorithms

How does immutability affect algorithm design? How are typical algorithms implemented without resorting to in-place mutation?

This chapter will give you a taste of functional algorithms. List prepending will be one dominating theme here. We will start by looking at list reversal and how prepending helps in dealing with algorithms.. We will then look at an efficient algorithm for list reversal using list prepending.

Graphs are a very important data structure; they are used to model related entities. We will be looking at directed graphs, also known as digraphs. We will implement functional versions of common digraph algorithms, for example, traversing a graph and visiting each node to do something useful.

Topological sorting is a digraph algorithm used to compute nodes' order of precedence. Build tools, such as Make, need to order tasks based on precedence. Topological sorting is the algorithm used by such tools to process a task's dependencies...

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