Book Image

Learning Functional Data Structures and Algorithms

By : Raju Kumar Mishra
Book Image

Learning Functional Data Structures and Algorithms

By: Raju Kumar Mishra

Overview of this book

Functional data structures have the power to improve the codebase 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 functional setting? Won’t we end up copying too much? Do we trade performance for versioned data structures? This book attempts to answer these questions by looking at functional implementations of traditional algorithms. It begins with a refresher and consolidation of 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. Scala is the primary implementation languages for most of the examples. At times, we also present Clojure snippets to illustrate the underlying fundamental theme. While writing code, we use ADTs (abstract data types). Stacks, Queues, Trees and Graphs are all familiar ADTs. You will see how these ADTs are implemented in a functional setting. We look at implementation techniques like amortization and lazy evaluation to ensure efficiency. By the end of the book, you will be able to write efficient functional data structures and algorithms for your applications.
Table of Contents (20 chapters)
Learning Functional Data Structures and Algorithms
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Understanding FIFO queues


FIFO queues are used for implementing the first come, first served strategy. For example, let's consider a queue for booking movie tickets (for now we'll pretend that there is no such thing as an online ticket booking system).

The person who comes first and joins the queue gets serviced before the person after him (who joined the queue a bit later). This enforces an order, which is also known as first come, first served or FIFO. According to this, the person who comes earlier is serviced first and moves out of the queue.

A new element queues up at the head and is removed/serviced at the tail, as shown in the following figure:

In the imperative world, it is pretty easy to see how we would implement a FIFO queue. We could maintain the FIFO queue as a singly linked list with two pointers: one at the head and another at the tail.

We will remove the tail node (pop the element off the queue)-an O(n) operation-as we need to traverse the entire list to reach the last element...