Data Structures Algorithms In Swift Fourth Edition

Learn Data Structures & Algorithms in Swift!Data structures and algorithms form the basis of computer programming and are the starting point for anyone looking to become a software engineer. Choosing the proper data structure and algorithm involves understanding the many details and trade-offs of using them, which can be time-consuming to learn - and confusing.This is where this book, Data Structures & Algorithms in Swift, comes to the rescue! In this book, you'll learn the nuts and bolts of how fundamental data structures and algorithms work by using easy-to-follow tutorials loaded with illustrations; you'll also learn by working in Swift playground code.Who This Book Is ForThis book is for developers who know the basics of Swift syntax and want a better theoretical understanding of what data structures and algorithms are to build more complex programs or ace a whiteboard interview.Topics Covered in Data Structures & Algorithms in Swift*Basic data structures and algorithms, including stacks, queues and linked lists. *How protocols can be used to generalize algorithms. *How to leverage the algorithms of the Swift standard library with your own data structures. *Trees, tries and graphs. *Building algorithms on top of other primitives. *A complete spectrum of sorting algorithms from simple to advanced. *How to think about algorithmic complexity. *Finding shortest paths, traversals, subgraphs and much more.After reading this book, you'll have a solid foundation on data structures and algorithms and be ready to solve more complex problems in your apps elegantly.

The book focuses initially on linked lists. Discussion of trees escalates from from binary search trees to culminate in dynamically, self-balancing AVL trees where search, insertion or removal are all generally ‎O(log n). Where the time complexity serves as a natural transition, the book then turns to search such as binary search being O(log n), as covered in Chapter 12, or other searching such as breadth or depth first searching in Chapter 20 and Chapter 21 and sorting algorithms such as comparison based sorting (i.e., bubble, selection, or insertion in Chapter 14) or other types of sorting such as merge in Chapter 15, radix in Chapter 16, or heap in Chapter 17. The book covers heap in Chapter 12, stack in Chapter 4, queues in Chapter 5 & Chapter 13, graphs in Chapter 19, Dijkstra's algorithm in Chapter 22 and prim's in Chapter 23--Book review by Eric Giannini.

Master the most common algorithms and data structures, and learn how to implement them efficiently using the most up-to-date features of Swift 3 About This Book Develop a deep understanding of the collections in the Swift Standard Library with this step-by-step guide Develop native Swift data structures and algorithms for use in mobile, desktop, and server-based applications Learn about performance efficiency between different data structures and algorithms Who This Book Is For This book is for developers who want to learn how to implement and use common data structures and algorithms natively in Swift. Whether you are a self-taught developer without a formal technical background or you have a degree in Computer Science, this book will provide with the knowledge you need to develop advanced data structures and algorithms in Swift using the latest language features. What You Will Learn Get to know about the basic data structures and how to use the Swift REPL Use the Swift Standard Library collections bridging to Objective-C collections, and find out about protocol-oriented programming Find out about Swift generators and sequences, and see how to use them to implement advanced data structures such as Stack, StackList, Queue, and LinkedList Implement sorting algorithms such as Insertion Sort, Merge Sort, and Quick Sort and understand the performance trade-offs between them See how to implement various binary trees, B-Tree, and Splay Trees Perform advanced searching methods using Red-Black trees, AVL trees, and Trie trees, and take a look at several substring search algorithms Get to know about the data structures used in graphs and how to implement graphs such as depth-first search, breadth-first search, directed graphs, spanning tree, and shortest path Explore algorithm efficiency and see how to measure it In Detail 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. Style and approach This easy-to-follow yet comprehensive guide can either be read from beginning to end, or depending on your current knowledge level, you can jump to the specific chapter that interests you. Each chapter topic starts with an introduction to the topic and algorithm before moving on to the hands-on implementation and analysis.

Control the performance and stability of the apps you develop in Swift by working with and understanding advanced concepts in data structures and algorithms. All professional developers have to know which data structure and algorithms to use in their development process. Your choice directly affects the performance of your application. With this book, you’ll increase the performance of your software, become a better developer, and even pass tricky interview questions better when looking at professional development opportunities. Guided by compact and practical chapters, you'll learn the nature and proper use of data structures such as arrays, dictionaries, sets, stacks, queues, lists, hash tables, trie, heaps, binary trees, red black trees, and R-trees. Use the main differences among them to determine which will make your applications efficient and faster. Then tackle algorithms. Work with Big O notation; sorting algorithms such as Insertion, Merge, and Quick; Naive and Rabin Karp algorithms; and Graph Algorithms. Data Structures and Algorithms in Swift encourages you to further and understand how to best choose the perfect algorithm for your application’s needs. What You'll Learn Retrieve, add, and remove elements in arraysImplement stacks, queues, and lists in your appsSort algorithms and choose the best ones for your apps Who This Book Is For Developers who have intermediate knowledge in Swift and want to improve their code performance and pass more complex interviews

An updated, innovative approach to data structures and algorithms Written by an author team of experts in their fields, this authoritative guide demystifies even the most difficult mathematical concepts so that you can gain a clear understanding of data structures and algorithms in C++. The unparalleled author team incorporates the object-oriented design paradigm using C++ as the implementation language, while also providing intuition and analysis of fundamental algorithms. Offers a unique multimedia format for learning the fundamentals of data structures and algorithms Allows you to visualize key analytic concepts, learn about the most recent insights in the field, and do data structure design Provides clear approaches for developing programs Features a clear, easy-to-understand writing style that breaks down even the most difficult mathematical concepts Building on the success of the first edition, this new version offers you an innovative approach to fundamental data structures and algorithms.

The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich, Tomassia and Goldwasser's approach to this classic topic is based on the object-oriented paradigm as the framework of choice for the design of data structures. For each ADT presented in the text, the authors provide an associated Java interface. Concrete data structures realizing the ADTs are provided as Java classes implementing the interfaces. The Java code implementing fundamental data structures in this book is organized in a single Java package, net.datastructures. This package forms a coherent library of data structures and algorithms in Java specifically designed for educational purposes in a way that is complimentary with the Java Collections Framework.

A comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algorithms in pseudocode. Since the publication of the first edition, Introduction to Algorithms has become the leading algorithms text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout. New for the fourth edition New chapters on matchings in bipartite graphs, online algorithms, and machine learning New material on topics including solving recurrence equations, hash tables, potential functions, and suffix arrays 140 new exercises and 22 new problems Reader feedback–informed improvements to old problems Clearer, more personal, and gender-neutral writing style Color added to improve visual presentation Notes, bibliography, and index updated to reflect developments in the field Website with new supplementary material Warning: Avoid counterfeit copies of Introduction to Algorithms by buying only from reputable retailers. Counterfeit and pirated copies are incomplete and contain errors.

Continuing the success of the popular second edition, the updated and revised Object-Oriented Data Structures Using Java, Third Edition is sure to be an essential resource for students learning data structures using the Java programming language. It presents traditional data structures and object-oriented topics with an emphasis on problem-solving, theory, and software engineering principles. Beginning early and continuing throughout the text, the authors introduce and expand upon the use of many Java features including packages, interfaces, abstract classes, inheritance, and exceptions. Numerous case studies provide readers with real-world examples and demonstrate possible solutions to interesting problems. The authors' lucid writing style guides readers through the rigor of standard data structures and presents essential concepts from logical, applications, and implementation levels. Key concepts throughout the Third Edition have been clarified to increase student comprehension and retention, and end-of-chapter exercises have been updated and modified. New and Key Features to the Third Edition: -Includes the use of generics throughout the text, providing the dual benefits of allowing for a type safe use of data structures plus exposing students to modern approaches. -This text is among the first data structures textbooks to address the topic of concurrency and synchonization, which are growing in the importance as computer systems move to using more cores and threads to obtain additional performance with each new generation. Concurrency and synchonization are introduced in the new Section 5.7, where it begins with the basics of Java threads. -Provides numerous case studies and examples of the problem solving process. Each case study includes problem description, an analysis of the problem input and required output, and a discussion of the appropriate data structures to use. -Expanded chapter exercises allow you as the instructor to reinforce topics for your students using both theoretical and practical questions. -Chapters conclude with a chapter summary that highlights the most important topics of the chapter and ties together related topics.