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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? 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

Concatenating lists


In the imperative world, where we perform mutation as needed, concatenating two linked lists is easy.

Given the two lists a and b, we just traverse the first list a until we reach its last node. Then we change its next pointer to the head of list b:

Note what happened to the original list a. It changed. The original list simply does not exist anymore.

We destroyed list a when we connected its third node to list b. The preceding list mutation is also not thread-safe. As seen in the previous chapter, additional mechanism, such as locking, is needed to make sure the state is synchronized correctly.

We could do the concatenation by keeping the original list intact; we do this by copying list a into another list c and then changing the third node of the new list to point to list b.

Our list a and list b are not touched at all. We copy list a into a new list, namely list c, and change its third node to point to the head of list b.

Note that the new list, that is, list c, and...

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