Functional Data Structures and Algorithms

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 important place in the developer toolkit. Immutability is a cornerstone of functional programming. Immutable and persistent data structures are thread-safe by definition and therefore very appealing for writing robust concurrent programs. How do we express the traditional algorithms in a functional setting? Will not we end up copying too much? Do we trade performance for versioned data structures? This course attempts to answer these questions by looking at the 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 the Lists, the work horse data type for most functional languages. We show what structural sharing means and how it helps to make unmatched 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