Nell Dale - Abstract data types: specifications, implementations, and applications
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Abstract data types: specifications, implementations, and applications
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This text expands the traditional course focus to examine not only the structure of a data object, but also its type. This broader focus requires a new paradigm for classifying data types. Within each classification, the different ADTs are presented using axiomatic specifications. Various implementation alternatives are discussed for each ADT and algorithms are written in a pseudo-code based on the Pascal-Modula- 2-Ada model. Next, the Big-O complexity of each implementation is discussed and each ADT is used in an application. Classic algorithms provide applications for some of the ADTs; implementation of a previously defined ADT is the application for others. The result is a clear, logical presentation that gives students a solid, practical foundation in current software engineering principles. Applications are included to demonstrate how the ADTs are used in problem-solving. Proven pedagogical features such as detailed examples, highlighted definitions, numerous illustrations, and exercises teach problem-solving skills.
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Abstract Data Types : Specifications, Implementations, and Applications
author
:
Dale, Nell.; Walker, Henry Mackay.
publisher
:
Jones & Bartlett Publishers, Inc.
isbn10 | asin
:
0669400009
print isbn13
:
9780669400007
ebook isbn13
:
9780585303956
language
:
English
subject
Abstract data types (Computer science) , Data structures (Computer science)
publication date
:
1996
lcc
:
QA76.73.D35 1996eb
ddc
:
005.7/3
subject
:
Abstract data types (Computer science) , Data structures (Computer science)
Page iii
Abstract Data Types
Specifications, Implementations, and Applications
Nell Dale The University of Texas at Austin Henry M. Walker Grinnell College
Page iv
Address editorial correspondence to D.C. Heath and Company 125 Spring Street Lexington, MA 02173
Acquisitions: Walter Cunningham Development: Rebecca Johnson, Karen H. Jolie Editorial Production: Heather Garrison, Anne Starr Design: Henry Rachlin Production Coordination: Charles Dutton
Copyright 1996 by D.C. Heath and Company.
All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage or retrieval system, without permission in writing from the publisher.
Published simultaneously in Canada.
Printed in the United States of America.
International Standard Book Number: 0-669-35444-9
Library of Congress Catalog Number: 95-68945
10 9 8 7 6 5 4 3 2 1
Page v
To Al, my husband and best friend N.D. To my family: my wife, Terry my daughters, Donna and Barbara my parents, Alice and Benjamin H.M.W.
Page vii
Preface
Fresh, Modern Approach
This book takes a fresh, modern approach to the organization and manipulation of data by computer systems. This approach is innovative in several important ways:
1. Abstract data types (ADTs) are organized following a top-down perspective, based upon a user's view of data.
2. As the book's title suggests, each ADT is explored from three perspectives: specification, implementation, and application.
3. ADTs are defined precisely and formally through the use of axiomatic specifications.
4. Several implementations of most ADTs are presented and the strengths and weaknesses of each are reviewed. Further, we regularly tie an implementation to the ADT's specifications, arguing why a particular implementation is correct.
5. Implementations include both single-processor algorithms and parallel algorithms.
6. The book includes a very broad range of applications, from standard coding algorithms (e.g., Huffman coding) to new contexts (e.g., the use of tables within Internet communication).
Data Types and Data Structures
Data structures have been a fundamental subject in computer science curricula beginning with the ACM's Curriculum '68. However, the focus has broadened considerably in the last few years. Data structures refers to the study of data and how to represent data objects within a program: the implementation of structured relationships. We are now interested in the study of the abstract properties of classes of objects in addition to how these objects might be represented in a program. Johannes J. Martin puts it very succinctly: "... depending on the point of view, a data object is characterized by its type (for the user) or by its structure (for the implementer)."1
1 Johannes J. Martin, Data Types and Data Structures, Prentice-Hall International Series in Computer Science, C.A.R. Hoare, Series Editor, 1986.
Page viii
The subjects of this broader topic are abstract data types (ADTs): classes of objects whose logical behavior is defined by a set of values and a set of operations. The object-oriented programming (OOP) approach to problem solving has contributed considerably to this change of focus. OOP is often described as the use of abstract data types in an environment with inheritance and polymorphism. However, this book is about abstract data types; we do not consider inheritance and polymorphism, but we do discuss generic data types.
Top-Down Organization of Abstract Data Types
In response to this new focus, the authors proposed a changed paradigm for classifying data types.2 This book follows the new paradigm. More specifically, we classify ADTs according to their logical operations, as shown in Figure 1. Beyond simple scalar types, ADTs may be viewed as being unstructured, semistructured, or structured. For example, unstructured ADTs include sets, keyed tables, and records in which data are stored and retrieved, but the user is unaware of any relationships among these data. Internally, of course, the data may be stored in a bit vector, hash table, or other data structure, but the external user does not care about such details.
Similarly a semistructured ADT provides the user with limited access to data; such ADTs include stacks, FIFO queues, and priority queues. Internally, data may be stored in an array or a linked list, but externally a user may access information with only a constrained collection of operations.
Structured ADTs organize data in particular ways, so that various relationships may exist among the data. Structured ADTs may be subdivided into nondimensional data types, linear data types, and multidimensional data types. Relationships among data in nondimensional data types are defined by a hierarchy of information or by explicit edge relationships. Data in multidimensional structures are accessed through two or more subscripts. Data in linear structures are organized through either explicit subscripts or an implicit ordering where each data item (except the last) has an explicit successor.
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