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The publisher does not offer any warranties or representations, nor does it accept any liabilities with respect to the programs or applications. Credits and acknowledgments borrowed from other sources and reproduced, with permission, in this textbook appear on appropriate page within text. All rights reserved.
Manufactured in the United States of America. This publication is protected by Copyright, and permission should be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. To obtain permission s to use material from this work, please submit a written request to Pearson Education, Inc. Many of the designations by manufacturers and seller to distinguish their products are claimed as trademarks.
Where those designations appear in this book, and the publisher was aware of a trademark claim, the designations have been printed in initial caps or all caps. Includes index. ISBN pbk. Data structures Computer science 3. Object-oriented programming Computer science I. Savitch, Walter J. CM25 In addition, we cover a range of important programming techniques and provide self-contained coverage of abstraction techniques, object-oriented programming, big-O time analysis of algorithms, and sorting.
We assume that the student has already had an introductory computer science and programming class, but we do include coverage of those topics such as recursion and pointers that are not always covered completely in a first course.
As this indicates, there are several pathways through the text that can be tailored to different backgrounds, including some optional features for the student who comes to the class with a stronger than usual background. We have been able to introduce students to the STL here even before they have a full understanding of templates.
This is a good location for the material because the students have just seen how to implement their first collection class the bag , which is based on the multiset. At this point, the students have enough knowledge to understand typical vector and list implementations. Most chapters also include new programming projects, and you may also keep an eye on our project web site, www. There are also additional supplemental data types such as a priority queue.
Each of these data types is introduced following a consistent pattern: Step 1: Understand the data type abstractly. At this level, a student gains an understanding of the data type and its operations at the level of concepts and pictures. For example, a student can visualize a stack and its operations of pushing and popping elements.
Simple applications are understood and can be carried out by hand, such as using a stack to reverse the order of letters in a word. The specification includes prototypes for the constructors, public member functions, and sometimes other public features such as an underlying constant that determines the maximum size of a stack.
In fact, this same specification may be used several times for several different implementations of the same data type. Step 3: Use the data type. With the specification in place, students can write small applications or demonstration programs to show the data type in use.
Step 4: Select appropriate data structures, and proceed to design and implement the data type. With a good abstract understanding of the data type, we can select an appropriate data structure, such as a fixed-sized array, a dynamic array, a linked list of nodes, or a binary tree of nodes. For many of our data types, a first design and implementation will select a simple approach, such as a fixed-sized array. Later, we will redesign and reimplement the same data type with a more complicated underlying structure.
With each implemented class, we stress the necessity for a clear understanding of the rules that relate the private member variables to an abstract notion of the data type. We require each student to write these rules in clear English sentences that we call the invariant of the abstract data type.
Once the invariant is written, students can proceed to implementing various member functions. The invariant helps in writing correct functions because of two facts: a Each function except constructors knows that the invariant is true when the function begins its work; and b each function except the destructor is responsible for ensuring that the invariant is again true when the function finishes.
Step 5: Analyze the implementation. Each implementation can be analyzed for correctness, flexibility such as a fixed size versus dynamic size , and time analysis of the operations using big-O notation. Students have a particularly strong opportunity for these analyses when the same data type has been implemented in several different ways. At the end of our course, students understand the data types inside out.
They know how to use the data types, they know how to implement them several ways, and they know the practical effects of the different implementation choices. The students can reason about efficiency with a big-O analysis and v vi Preface argue for the correctness of their implementations by referring to the invariant of the class.
One of the important lasting effects of the course is the specification, design, and implementation experience. The improved ability to reason about programs is also important. But perhaps most important of all is the exposure to classes that are easily used in many situations.
The students no longer have to write everything from scratch. We tell our students that someday they will be thinking about a problem, and they will suddenly realize that a large chunk of the work can be done with a bag, or a stack, or a queue, or some such.
Instead, they will pull out the bag or stack or queue or some such that they wrote this semester—using it with no modifications. In fact, the behavior of the data types in this text is a cut-down version of the Standard Template Library, so when students take the step to the real STL, they will be on familiar ground.
And at that point of realization, knowing that a certain data type is the exact solution he or she needs, the student becomes a real programmer. The important aspects of classes are covered early: the notion of a member function, the separation into private and public members, the purpose of constructors, and a small exposure to operator overloading.
This is enough to get students going and excited about classes. Further major aspects of classes are introduced when the students first use dynamic memory Chapter 4. At this point, the need for three additional items is explained: the copy constructor, the overloaded assignment operator, and the destructor.
Teaching these OOP aspects with the first use of dynamic memory has the effect of giving the students a concrete picture of dynamic memory as a resource that can be taken and must later be returned. Conceptually, the largest innovation of OOP is the software reuse that occurs via inheritance. And there are certainly opportunities for introducing inheritance right from the start of a data structures course such as implementing a set class as a descendant of a bag class.
However, an early introduction may also result in juggling too many new concepts at once, resulting in a weaker understanding of the fundamental data structures. Therefore, in our own course we introduce inheritance at the end as a vision of things to come. But the introduction to inheritance Sections With this in mind, some instructors may wish to cover Chapter 14 earlier, just before stacks and queues. Another alternative is to identify students who already know the basics of classes. These students can carry out an inheritance project such as the ecosystem of Section Template functions and template classes are an important part of the proposed Standard Template Library, allowing a programmer to easily change the type of the underlying item in a container class.
Template classes also allow the use of several different instantiations of a class in a single program. Iterators are another important part of the proposed Standard Template Library, allowing a programmer to easily step through the items in a container object such as the elements of a set or bag.
Such iterators may be internal implemented with member functions of the container class or external implemented by a separate class that is a friend of the container class. We introduce internal iterators with one of the first container classes a sequential list in Section 3.
An internal iterator is added to the bag class when it is needed in Chapter 6. At that point, the more complex external iterators also are discussed, and students should be aware of the advantages of an external iterator. Throughout the text, iterators provide a good opportunity for programming projects, such as implementing an external bag iterator Chapter 6 or using a stack to implement an internal iterator of a binary search tree Chapter First-semester courses sometimes introduce students to recursion.
But many of the first-semester examples are tail recursion, where the final act of the function is the recursive call. This may have given students a misleading impression that recursion is nothing more than a loop. Because of this, we prefer to avoid early use of tail recursion in a second-semester course. For example, list traversal and other operations on linked lists can be implemented with tail recursion, but the effect may reinforce wrong impressions about recursion and the tail recursive list operations may need to be unlearned when the students work with lists of thousands of items, running into potential run-time stack overflow.
So, in our second-semester course, we emphasize recursive solutions that use more than tail recursion. The recursion chapter provides three examples along these lines. Two of the examples—generating random fractals and traversing a maze—are big hits with the students.
In our class, we teach recursion Chapter 9 just before trees Chapter 10 , since it is in recursive tree algorithms that recursion becomes vital. However, instructors who desire more emphasis on recursion can move that topic forward, even before Chapter 2. Searching and sorting. Chapters 12 and 13 provide fundamental coverage of searching and sorting algorithms. The searching chapter reviews binary search of an ordered array, which many students will have seen before.
Hash tables also are introduced in the search chapter. Advanced Projects The text offers good opportunities for optional projects that can be undertaken by a more advanced class or by students with a stronger background in a large class. We have made a particular effort on this project to provide information that is sufficient for students to implement the class without need of another text. In our courses, we have successfully directed advanced students to do this project as independent work.
This is another case where advanced students may do work on their own. But we endeavor to provide complete coverage for those features that we do touch. The requirements for using static member constants were changed in the Standard, and we have incorporated this change into the text the constant must now be declared both inside and outside the class definition.
View larger. Request a copy. Download instructor resources. Additional order info. Buy this product. K educators : This link is for individuals purchasing with credit cards or PayPal only. Flexible by design, professors have the option of emphasizing object-oriented programming, covering recursion and sorting early, or accelerating the pace of the course.
All rights reserved. No part of the material protected by this copyright may be reproduced or utilized in any form, electronic or mechani-cal, including photocopying, recording, or by any information storage and retrieval system, without written permission from the copyright owner. All trademarks displayed are the trademarks of the parties noted herein. Object-Oriented Data Structures Using Java, Fourth Edition is an independent publication and has not been authorized, sponsored, or otherwise approved by the owners of the trademarks or service marks referenced in this product. D35 DDC This book pres-ents the algorithmic, programming, and structuring techniques of a traditional data structures course in an object-oriented context. We stress software engineering principles throughout, including modularization, information hiding, data abstraction, stepwise refinement, the use of visual aids, the analysis of algorithms, and software verification methods.
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Flexible by design, professors have the option of emphasizing objectoriented. Finally, a solid foundation in building and using abstract data types is also provided, along. Choose the book you like when you register4. You can also cancel your membership if you are bored5.
We are Test Bank For You. Solution Manual and Test Bank Test bank for you hey everybody especially students, do not worry about exams, quizes,homeworks. A container class is a data type that is capable of holding a collection of items. View solution-manual-data-structures-and-other-objects-using-java-4th-edition-michael-main from ECON at Harvard University.
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Preface DATA STRUCTURES & OTHER OBJECTS Using C++. 4TH EDITION MICHAEL MAIN Department of Computer Science University of.