Book Image

Swift Data Structure and Algorithms

By : Mario Eguiluz Alebicto
Book Image

Swift Data Structure and Algorithms

By: Mario Eguiluz Alebicto

Overview of this book

Apple’s Swift language has expressive features that are familiar to those working with modern functional languages, but also provides backward support for Objective-C and Apple’s legacy frameworks. These features are attracting many new developers to start creating applications for OS X and iOS using Swift. Designing an application to scale while processing large amounts of data or provide fast and efficient searching can be complex, especially running on mobile devices with limited memory and bandwidth. Learning about best practices and knowing how to select the best data structure and algorithm in Swift is crucial to the success of your application and will help ensure your application is a success. That’s what this book will teach you. Starting at the beginning, this book will cover the basic data structures and Swift types, and introduce asymptotic analysis. You’ll learn about the standard library collections and bridging between Swift and Objective-C collections. You will see how to implement advanced data structures, sort algorithms, work with trees, advanced searching methods, use graphs, and performance and algorithm efficiency. You’ll also see how to choose the perfect algorithm for your problem.
Table of Contents (15 chapters)
Swift Data Structure and Algorithms
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface

Quick sort


Quick sort is another divide and conquer algorithm. It is a popular, fast sorting algorithm that can perform sorting in-place, so it is space efficient and has been used as the reference implementation in Java as well as the default library sort function in Unix. The algorithm works by dividing an initial array into two small subsequences, one with the lower sequences and another with the higher sequences, based on the pivot selected by a partitioning scheme. Its average running time is O(n lg n), mainly due to its tight inner loop. It can have a worst case running time of O(n2), but this can be minimized by ensuring the data is in a random order first. Additionally, ensuring that the correct pivot is selected will dramatically affect the algorithm's performance.

The algorithm – Lomuto's implementation

We'll begin our examination of the quick sort algorithm by looking at an implementation by Nico Lomuto, called the Lomuto Partitioning Scheme. This version of the algorithm is a little...