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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? FREE CHAPTER 2. Building Blocks 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

Lists are good for operations at the head. However, for randomly accessing an element by its index, the complexity is O(n).

We looked at an alternative list implementation, a list allowing fast random element access. The data structure was really a list of binary trees. The implementation mirrors binary number algorithms.

We saw how all the operations, such as insertion, update, lookup, head, and tail, perform at O(log(n)). We first locate the right tree quickly and then perform a binary search on it.

All these operations are immutable of course. We saw how the process of structural sharing and copying just enough help with the implementation.

Hopefully, this has made you hungrier for more functional data structures and algorithms. So let's look at some more exciting algorithms. Stay tuned!

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