Richard Wiener

Generic Data Structures and Algorithms in Go

An Applied Approach Using Concurrency, Genericity and Heuristics

• Broschiertes Buch

Produktbeschreibung

Advance your understanding of generic data structures and algorithms and their applications using Go and the effective use of concurrency. You are invited on a journey that aims to improve your programming and problem-solving skills. This book takes you to the next step by showing how to get your programs to work efficiently as well as correctly.
As you explore many data structures and the algorithms and applications associated with them, you'll focus on the trade-offs between speed and storage and the benefits of deploying concurrency when appropriate. This book will demonstrate the huge increases in application performance that are possible. The presentation of classic data structures and techniques of algorithm design (greedy, divide and conquer, branch-and-bound to name a few) provides an essential foundation and toolkit for problem solving. But this book goes further by presenting heuristic algorithms and their implementations forsolving computationally intractable combinatoric optimization problems such as the travelling salesperson problem. Simulated annealing and genetic algorithms are among the techniques used.
The consistent style of coding used throughout this book exploits Go's ability to implement abstract, generic and constrained generic data types without the use of classes. Although some familiarity with Go is assumed, this book should advance your ability to use Go to tackle server-side applications, games, machine learning, information retrieval and other application domains where speed and storage efficiency is essential.
What You'll LearnExplore classical data structures and algorithms aimed at making your applications run faster or require less storageUse the new generic features of Go to build reusable data structuresUtilize concurrency for maximizing application performanceSee the power of heuristic algorithms for computationally intractable problemsEnhance and improve your Go programming skillsWho This Book Is For
Practicing Go software developers and students who wish to advance their programming and problem-solving skills and experience the excitement and see the benefits of using generic data structures and algorithms that utilize concurrency whenever possible.

Produktdetails

• Verlag: Apress / Springer, Berlin
• Artikelnr. des Verlages: 978-1-4842-8190-1
• 1st ed.
• Seitenzahl: 579
• Erscheinungstermin: 13. Juli 2022
• Englisch
• Abmessung: 254mm x 178mm x 32mm
• Gewicht: 1127g
• ISBN-13: 9781484281901
• ISBN-10: 148428190X
• Artikelnr.: 63578490

Autorenporträt

Richard Wiener, Ph.D. authored or co-authored 22 professional, software development and computer-science textbooks published by Wiley, Addison-Wesley, Prentice-Hall, Cambridge University Press and Thompson.  Served as founding Editor-in-Chief of the Journal of Object-Oriented Programming for 12 years and later, founding Editor-in-Chief of the Journal of Object Technology for 9 years.  Worked as Associate Professor of Computer Science at the University of Colorado, Colorado Springs (UCCS) from 1977-2012.  Served as Department Chair during last four years at UCCS. Served as consultant and software developer for IBM, HP, Boeing, Textronix, DEC and many other companies.  Presented industry short-courses all over the world from 1980 to 2006. Earned BS and MS in Electrical Engineering from City University of New York and Ph.D. from Polytechnic Institute of New York.

Inhaltsangabe

1. A Tour Of Generics and Concurrency In Go.- 2. Algorithm Efficiency - Sorting and Searching.- 3. Abstract Data Types: OOP Without Classes in Go.- 4. ADT In Action: Game Of Life.- 5. Stacks.- 6. Queues and Lists.- 7. Hash Tables.- 8. Binary Trees.- 9. Binary Search Tree.- 10. AVL Trees.- 11. Heap Trees.- 12. Red Black Trees.- 13. Expression Trees.- 14. Ecological Simulation With Concurrency.- 15. Dynamic Programming.- 16. Graph Structures.- 17. Travelling Salesperson Problem.- 18. Branch and Bound Solution to TSP.- 19. Simulated Annealing Heuristic Solution to TSP.- 20. Genetic Algorithm for TSP.- 21. Neural Networks and Machine Learning.