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

Dijkstra algorithm


Edsger W. Dijkstra conceived his algorithm to solve the shortest path for graphs between 1956-1959.

His algorithm finds the shortest path between two nodes, but other variants exist to find the shortest paths between an origin and all other nodes; this is called a shortest path tree. Let's see how it works, and then we will implement it in Swift. We are going to explain it with the following example graph. We want the shortest path between node A and node E:

Shortest path example

The steps are as follows:

  1. The algorithm starts by marking the first node as the current node. It puts all the nodes as unvisited inside a set. It also initializes every node with a temporary distance, infinitum or a maximum number:

    Shortest path step 1

  2. Then, for each unvisited neighbor of the current node, calculate the temporary distance from our current node to all its neighbors as the sum of the current node distance and edge weight to the neighbor for each case. If the result is smaller than...