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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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Toc

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

Summary

We looked at some prominent reasons to adopt the FP paradigm.

Firstly, we saw what is imperative programming and the notion of state modification.

FP allows us to program at a higher level of abstraction. We looked at some common examples of applying such abstractions.

We saw how FP encourages us to compose systems from existing building blocks. These blocks themselves, in turn, could have been composed out of other smaller blocks. This is an incredibly powerful way to reuse code.

The declarative style of programming is easily seen in how SQL queries work. This allows us to work at a higher level of abstraction.

FP promotes this same declarative style. For example, we normally use implied loops. Implied loops in FP are similar to how Unix shell filters process data.

Controlling changes to a program's state is way too hard. We saw how important this is, given the multithreaded world we developers live in. We saw how FP makes it a breeze by dealing with mostly immutable data structures.

In the next chapter, we will look at some fundamental concepts in data structures and algorithms.

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