Book Image

Learning Functional Data Structures and Algorithms

By : S. Khot, Mishra
Book Image

Learning Functional Data Structures and Algorithms

By: S. Khot, 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 (14 chapters)

Summary


Sorting is used to solve many complex problems. Sorted data aids searching algorithms too. We discussed some very useful sorting algorithms, such as bubble sort, selection sort, insertion sort, merge sort, and quick sort. Every sorting algorithm has its own complexity.

We discussed bubble sort. Bubble sort is one of the earliest developed sorting algorithms. We implemented it in Scala.

After bubble sort, we moved on to selection sort, where in every pass, a small element is selected and put in a sorted list. Here, we found that in every pass, only one exchange is done, but the number of comparisons will be the number of unsorted elements.

The simplicity of insertion sort touched everyone. It uses two subsequences: one sorted and one unsorted. We take an element from the unsorted subsequence and put it in the sorted subsequence, while maintaining the order of the elements.

Divide and conquer is the most celebrated technique for problem solving. It has been used in sorting algorithms...