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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

Recursion aids immutability

Instead of writing a loop using a mutable loop variable, functional languages advocate recursion as an alternative. Recursion is a widely used technique in imperative programming languages, too. For example, quicksort and binary tree traversal algorithms are expressed recursively. Divide and conquer algorithms naturally translate into recursion.

When we start writing recursive code, we don't need mutable loop variables:

scala> import scala.annotation.tailrec 
import scala.annotation.tailrec 
scala> def factorial(k: Int): Int = { 
     |   @tailrec 
     |   def fact(n: Int, acc: Int): Int = n match { 
     |     case 1 => acc 
     |     case _ => fact(n-1, n*acc) 
     |   } 
     |   fact(k, 1) 
     | } 
factorial: (k: Int)Int 
 
scala> factorial(5) 
res0: Int = 120  

Note the @tailrec annotation. Scala gives us an option to ensure that tail call optimization (TCO) is applied. TCO rewrites a recursive tail call as a loop. So in reality, no stack frames are used; this eliminates the possibility of a stack overflow error.

Here is the equivalent Clojure code:

user=> (defn factorial [n] 
  #_=>   (loop [cur n fac 1] 
  #_=>     (if (= cur 1) 
  #_=>      fac 
  #_=>       (recur (dec cur) (* fac cur) )))) 
#'user/factorial 
user=> (factorial 5) 
120 

The following diagram shows how recursive calls use stack frames:

Recursion aids immutability

Clojure's special form, recur, ensures that the TCO kicks in.

Note how these versions are starkly different than the one we would write in an imperative paradigm.

Instead of explicit looping, we use recursion so we wouldn't need to change any state, that is, we wouldn't need any mutable variables; this aids immutability.

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