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

Chapter 8. Performance and Algorithm Efficiency

In this chapter, we are going to see algorithms in terms of performance and efficiency. We have been implementing different algorithms in previous chapters, and now we are going to explain how we can measure them, in theory and in practice. We are going to use the help of asymptotic analysis and Big-O notation to classify and compare algorithms.

The topics covered are as follows:

  • Algorithm efficiency

  • Measuring efficiency

  • Big-O notation

  • Orders of common functions

  • Evaluating runtime complexity