DATA STRUCTURES AND ALGORITHMS WITH OBJECT- ORIENTED DESIGN PATTERNS IN C++

DATA STRUCTURES AND ALGORITHMS WITH OBJECT- ORIENTED DESIGN PATTERNS IN C++
Author: Bruno R. Preiss
Publisher: John Wiley & Sons
Total Pages: 684
Release: 2008-05
Genre:
ISBN: 9788126516438

About The Book: Bruno Preiss presents readers with a modern, object-oriented perspective for looking at data structures and algorithms, clearly showing how to use polymorphism and inheritance, and including fragments from working and tested programs. The book uses a single class hierarchy as a framework to present all of the data structures. This framework clearly shows the relationships between data structures and illustrates how polymorphism and inheritance can be used effectively.

Data Structures and Algorithms

Data Structures and Algorithms
Author: John Beidler
Publisher: Springer Science & Business Media
Total Pages: 375
Release: 2012-12-06
Genre: Computers
ISBN: 1461218543

This textbook provides an in depth course on data structures in the context of object oriented development. Its main themes are abstraction, implementation, encapsulation, and measurement: that is, that the software process begins with abstraction of data types, which then lead to alternate representations and encapsulation, and finally to resource measurement. A clear object oriented approach, making use of Booch components, will provide readers with a useful library of data structure components and experience in software reuse. Students using this book are expected to have a reasonable understanding of the basic logical structures such as stacks and queues. Throughout, Ada 95 is used and the author takes full advantage of Ada's encapsulation features and the ability to present specifications without implementational details. Ada code is supported by two suites available over the World Wide Web.

Data Structures and Algorithms Using Python and C++

Data Structures and Algorithms Using Python and C++
Author: David M. Reed
Publisher: Franklin Beedle & Associates
Total Pages: 0
Release: 2009
Genre: Algorithms
ISBN: 9781590282335

This book is intended for use in a traditional college- level data structures course (commonly known as CS2). This book assumes that students have learned the basic syntax of Python and been exposed to the use of existing classes. Most traditional CS1 courses that use Python will have covered all the necessary topics, and some may have covered a few of the topics covered in this book. We have found that most students successfully completing a CS1 course know how to use classes, but many of them need more experience to learn how to design and write their own classes. We address this issue by including a number of examples of class design in the first few chapters of this book.

Data Structures, Algorithms, and Software Principles in C

Data Structures, Algorithms, and Software Principles in C
Author: Thomas A. Standish
Publisher: Pearson
Total Pages: 778
Release: 1995
Genre: Computers
ISBN:

Using C, this book develops the concepts and theory of data structures and algorithm analysis in a gradual, step-by-step manner, proceeding from concrete examples to abstract principles. Standish covers a wide range of both traditional and contemporary software engineering topics. The text also includes an introduction to object-oriented programming using C++. By introducing recurring themes such as levels of abstraction, recursion, efficiency, representation and trade-offs, the author unifies the material throughout. Mathematical foundations can be incorporated at a variety of depths, allowing the appropriate amount of math for each user.

Data Structures and Algorithms in Java

Data Structures and Algorithms in Java
Author: Michael T. Goodrich
Publisher: Wiley Global Education
Total Pages: 738
Release: 2014-03-27
Genre: Computers
ISBN: 1118803167

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.

Data Structures and Algorithms in Python

Data Structures and Algorithms in Python
Author: Michael T. Goodrich
Publisher: Wiley Global Education
Total Pages: 770
Release: 2013-06-17
Genre: Computers
ISBN: 1118476735

Based on the authors' market leading data structures books in Java and C++, this book offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Structures and Algorithms in Python is the first authoritative object-oriented book available for Python data structures. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++. Begins by discussing Python's conceptually simple syntax, which allows for a greater focus on concepts. Employs a consistent object-oriented viewpoint throughout the text. Presents each data structure using ADTs and their respective implementations and introduces important design patterns as a means to organize those implementations into classes, methods, and objects. Provides a thorough discussion on the analysis and design of fundamental data structures. Includes many helpful Python code examples, with source code provided on the website. Uses illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Provides hundreds of exercises that promote creativity, help readers learn how to think like programmers, and reinforce important concepts. Contains many Python-code and pseudo-code fragments, and hundreds of exercises, which are divided into roughly 40% reinforcement exercises, 40% creativity exercises, and 20% programming projects.

Java Methods

Java Methods
Author: Maria Litvin
Publisher:
Total Pages: 530
Release: 2001
Genre: Computers
ISBN: 9780965485371

Problem Solving with Algorithms and Data Structures Using Python

Problem Solving with Algorithms and Data Structures Using Python
Author: Bradley N. Miller
Publisher: Franklin Beedle & Associates
Total Pages: 0
Release: 2011
Genre: Algorithms
ISBN: 9781590282571

Thes book has three key features : fundamental data structures and algorithms; algorithm analysis in terms of Big-O running time in introducied early and applied throught; pytohn is used to facilitates the success in using and mastering data strucutes and algorithms.

Learning Functional Data Structures and Algorithms

Learning Functional Data Structures and Algorithms
Author: Atul S. Khot
Publisher: Packt Publishing Ltd
Total Pages: 312
Release: 2017-02-23
Genre: Computers
ISBN: 178588588X

Learn functional data structures and algorithms for your applications and bring their benefits to your work now About This Book Moving from object-oriented programming to functional programming? This book will help you get started with functional programming. Easy-to-understand explanations of practical topics will help you get started with functional data structures. Illustrative diagrams to explain the algorithms in detail. Get hands-on practice of Scala to get the most out of functional programming. Who This Book Is For This book is for those who have some experience in functional programming languages. The data structures in this book are primarily written in Scala, however implementing the algorithms in other functional languages should be straight forward. What You Will Learn Learn to think in the functional paradigm Understand common data structures and the associated algorithms, as well as the context in which they are commonly used Take a look at the runtime and space complexities with the O notation See how ADTs are implemented in a functional setting Explore the basic theme of immutability and persistent data structures Find out how the internal algorithms are redesigned to exploit structural sharing, so that the persistent data structures perform well, avoiding needless copying. Get to know functional features like lazy evaluation and recursion used to implement efficient algorithms Gain Scala best practices and idioms In Detail Functional data structures have the power to improve the codebase of an application and improve efficiency. With the advent of functional programming and with powerful functional languages such as Scala, Clojure and Elixir becoming part of important enterprise applications, functional data structures have gained an important place in the developer toolkit. Immutability is a cornerstone of functional programming. Immutable and persistent data structures are thread safe by definition and hence very appealing for writing robust concurrent programs. How do we express traditional algorithms in functional setting? Won't we end up copying too much? Do we trade performance for versioned data structures? This book attempts to answer these questions by looking at functional implementations of traditional algorithms. It begins with a refresher and consolidation of what functional programming is all about. Next, you'll get to know about Lists, the work horse data type for most functional languages. We show what structural sharing means and how it helps to make immutable data structures efficient and practical. Scala is the primary implementation languages for most of the examples. At times, we also present Clojure snippets to illustrate the underlying fundamental theme. While writing code, we use ADTs (abstract data types). Stacks, Queues, Trees and Graphs are all familiar ADTs. You will see how these ADTs are implemented in a functional setting. We look at implementation techniques like amortization and lazy evaluation to ensure efficiency. By the end of the book, you will be able to write efficient functional data structures and algorithms for your applications. Style and approach Step-by-step topics will help you get started with functional programming. Learn by doing with hands-on code snippets that give you practical experience of the subject.