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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

Incrementing a binary number


Before we jump into list implementation, let's look at the related binary operations.

Here is how we would increment a binary number represented by a list of 0 and 1:

scala> def increment(numList: List[Int]): List[Int] = numList match { 
     |   case Nil => List(1) 
     |   case 0 :: xs => 1 :: xs 
     |   case 1 :: xs => 0 :: increment(xs) 
     |   case _ => sys.error("Not a binary number")  
     | } 
 
scala> increment(List(1,0,1)) 
res3: List[Int] = List(0, 1, 1) 
 
scala> increment(List(0, 1)) 
res4: List[Int] = List(1, 1) 
 
scala> increment(List(0, 0, 1)) 
res5: List[Int] = List(1, 0, 1) 

Note

Note that we need to write the numbers such that the least significant bit is on the left-hand side.

When we wrote the binary number algorithms, we saw the reason for it. We wanted the LSB to appear at the head of the list. Operating at the head of the list is an...

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