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Learning Functional Data Structures and Algorithms

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  • Learn to think in the functional paradigm
  • Understand common data structures and the associated algorithms, as well as the context in which they are commonly used
  • Take a look at the runtime and space complexities with the O notation
  • See how ADTs are implemented in a functional setting
  • Explore the basic theme of immutability and persistent data structures
  • Find out how the internal algorithms are redesigned to exploit structural sharing, so that the persistent data structures perform well, avoiding needless copying.
  • Get to know functional features like lazy evaluation and recursion used to implement efficient algorithms
  • Gain Scala best practices and idioms

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.

  • Moving from object-oriented programming to functional programming? This book will help you get started with functional programming.
  • Easy-to-understand explanations of practical topics will help you get started with functional data structures.
  • Illustrative diagrams to explain the algorithms in detail.
  • Get hands-on practice of Scala to get the most out of functional programming.
Page Count 318
Course Length 9 hours 32 minutes
ISBN 9781785888731
Date Of Publication 23 Feb 2017


Atul Khot

Atul Khot learned to program by reading C code and figuring out how it works. He wrote a lot of C++ code and then moved to Java and Scala. An avid open source advocate, he loves scripting languages, clean coding, and is always ready to learn a new command-line trick. He currently works at Webonise Labs, Pune. Atul was also a panelist of Dr. Dobb's Jolt Awards. Last but not least, he is a trekking enthusiast and also a big foodie.

Raju Kumar Mishra

Raju Kumar Mishra is a consultant and corporate trainer for big data and programming. After completing his B. Tech from the Indian Institute of Technology (ISM) Dhanbad, he worked for Tata Steel. His deep passion for mathematics, data science, and programming took him to the Institute of Science (IISc). After graduating from IISc in computational science, he worked for Oracle as a performance engineer and software developer.

He is an Oracle-certified associate for Java 7. He is a Hortonworks-certified Apache Hadoop Java developer, and holds a Developer Certification for Apache Spark (O'Reilly School of Technology and Databriks), and Revolution R Enterprise-certified Specialist Certifications. As well as this, he has also passed the Financial Risk Manager (FRM I) exam. His interest in mathematics helped him in clearing the CT3 (Actuarial Science) exam.