Functional Data Structures and Algorithms [Video]

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Functional Data Structures and Algorithms [Video]

Atul S. Khot, Raju Kumar Mishra

Learn functional data structures and algorithms for your applications and bring their benefits to your work now
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Video Details

ISBN 139781788393256
Course Length2 hours

Video Description

Functional data structures have the power to improve the code base of an application and improve efficiency. With the advent of functional programming, and with powerful functional languages such as Scala, Clojure and Elixir becoming part of important enterprise applications, functional data structures have gained an important place in the developer toolkit. Immutability is a cornerstone of functional programming. Immutable and persistent data structures are thread-safe by definition and hence very appealing for writing robust concurrent programs. How do we express traditional algorithms in a functional setting? Won’t we end up copying too much? Do we trade performance for versioned data structures? This course attempts to answer these questions by looking at functional implementations of traditional algorithms.

It begins with a refresher and consolidates what functional programming is all about. Next, you’ll get to know about Lists, the work horse data type for most functional languages. We show what structural sharing means and how it helps to make immutable data structures efficient and practical. Moving on, you will learn about binary trees, where we will be building complete trees, greedy algorithms, and back tracking

Style and Approach

Step-by-step topics will help you get started with functional programming. Learn by doing with hands-on code snippets that give you practical experience of the subject.

Table of Contents

Why Functional Programming?
The Course Overview
The Imperative Way and a Higher Level of Abstraction
Functional Programming and Boilerplate
Higher Order Functions
Recursion Aids Immutability
Copy-On-Write, Laziness, and Deferred Execution
Composing Functions
Building Blocks
The Big O Notation
Space/Time Trade-Off
Referential Transparency
Vectors Versus Lists
Complexities and Collections
Lists
First Steps
List Head and Tail
Drop Elements
Concatenating Lists
Persistent Data Structures and Tail Call Optimization
List Append and Prepend
Getting the Value at Index
Modifying a List Value
Binary Trees
Node Definitions
Building the Tree
Comparing Trees
The Accumulator Idiom
Binary Search Trees
More List Algorithms
Binary Numbers
Greedy Algorithms and Backtracking

What You Will Learn

  • Learn to think in the functional paradigm
  • Learn about the O notation
  • Take a look at runtime and space complexities
  • Explore the basic themes of immutability and persistent data structures
  • Learn to drop and concatenate lists
  • Learn to append and prepend lists
  • Take a look at building trees
  • Learn about the backtracking algorithm.
  • Master Scala best practices and idioms

Authors

Table of Contents

Why Functional Programming?
The Course Overview
The Imperative Way and a Higher Level of Abstraction
Functional Programming and Boilerplate
Higher Order Functions
Recursion Aids Immutability
Copy-On-Write, Laziness, and Deferred Execution
Composing Functions
Building Blocks
The Big O Notation
Space/Time Trade-Off
Referential Transparency
Vectors Versus Lists
Complexities and Collections
Lists
First Steps
List Head and Tail
Drop Elements
Concatenating Lists
Persistent Data Structures and Tail Call Optimization
List Append and Prepend
Getting the Value at Index
Modifying a List Value
Binary Trees
Node Definitions
Building the Tree
Comparing Trees
The Accumulator Idiom
Binary Search Trees
More List Algorithms
Binary Numbers
Greedy Algorithms and Backtracking

Video Details

ISBN 139781788393256
Course Length2 hours
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