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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 12. Binomial Heaps

In Chapter 8, Queues we looked at binary heaps. Now a binary min-heap takes the form of a complete binary tree. This means the key at each node is less than or equal to its children.

We will look at one more popular heap implementation, namely a binomial heap. A binomial heap is a collection of binomial trees, giving us a very efficient heap-merging operation.

We will begin with an introduction to binomial trees. Next, we will see how to link two binomial trees, the basics for growing a heap. The process of inserting into a binomial heap exhibits a surprising coincidence to the binary number addition process. This detour will help us understand the merge algorithm.

Next, we will look at how to merge two binomial heaps.

Finally, we will look at how to find and delete a minimum element. As we move on, we will reason the code and eventually exercise the various operations on REPL. We will do all this in good time, though. Let's review some basic terminologies...

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