This book presents the data structures and algorithms that underpin much of today's computer programming. The basis of this book is the material contained in the first six chapters of our earlier work, The Design and Analysis of Computer Algorithms. We have expanded that coverage and have added material on algorithms for external storage and memory management. As a consequence, this book should be suitable as a text for a first course on data structures and algorithms. The only prerequisite we assume is familiarity with some high-level programming language such as Pascal.
We have attempted to cover data structures and algorithms in the broader context of solving problems using computers. We use abstract data types informally in the description and implementation of algorithms. Although abstract data types are only starting to appear in widely available programming languages, we feel they are a useful tool in designing programs, no matter what the language.
We also introduce the ideas of step counting and time complexity as an integral part of the problem solving process. This decision reflects our longheld belief that programmers are going to continue to tackle problems of progressively larger size as machines get faster, and that consequently the time complexity of algorithms will become of even greater importance, rather than of less importance, as new generations of hardware become available.
We have used the conventions of Pascal to describe our algorithms and data structures primarily because Pascal is so widely known. Initially we present several of our algorithms both abstractly and as Pascal programs, because we feel it is important to run the gamut of the problem solving process from problem formulation to a running program. The algorithms we present, however, can be readily implemented in any high-level programming language.
Chapter 1 contains introductory remarks, including an explanation of our view of the problem-to-program process and the role of abstract data types in that process. Also appearing is an introduction to step counting and "big-oh" and "big-omega" notation.
Chapter 2 introduces the traditional list, stack and queue structures, and the mapping, which is an abstract data type based on the mathematical notion of a function. The third chapter introduces trees and the basic data structures that can be used to support various operations on trees efficiently.
Chapters 4 and 5 introduce a number of important abstract data types that are based on the mathematical model of a set. Dictionaries and priority queues are covered in depth. Standard implementations for these concepts, including hash tables, binary search trees, partially ordered trees, tries, and 2-3 trees are covered, with the more advanced material clustered in Chapter 5.
Chapters 6 and 7 cover graphs, with directed graphs in Chapter 6 and undirected graphs in 7. These chapters begin a section of the book devoted more to issues of algorithms than data structures, although we do discuss the basics of data structures suitable for representing graphs. A number of important graph algorithms are presented, including depth-first search, finding minimal spanning trees, shortest paths, and maximal matchings.
Chapter 8 is devoted to the principal internal sorting algorithms: quicksort, heapsort, binsort, and the simpler, less efficient methods such as insertion sort. In this chapter we also cover the linear-time algorithms for finding medians and other order statistics.
Chapter 9 discusses the asymptotic analysis of recursive procedures, including, of course, recurrence relations and techniques for solving them.
Chapter 10 outlines the important techniques for designing algorithms, including divide-and-conquer, dynamic programming, local search algorithms, and various forms of organized tree searching.
The last two chapters are devoted to external storage organization and memory management. Chapter 11 covers external sorting and large-scale storage organization, including B-trees and index structures.
Chapter 12 contains material on memory management, divided into four subareas, depending on whether allocations involve fixed or varying sized blocks, and whether the freeing of blocks takes place by explicit program action or implicitly when garbage collection occurs.
Material from this book has been used by the authors in data structures and algorithms courses at Columbia, Cornell, and Stanford, at both undergraduate and graduate levels. For example, a preliminary version of this book was used at Stanford in a 10-week course on data structures, taught to a population consisting primarily of Juniors through first-year graduate students. The coverage was limited to Chapters 1-4, 9, 10, and 12, with parts of 5-7.
A number of exercises of varying degrees of difficulty are found at the end of each chapter. Many of these are fairly straightforward tests of the mastery of the material of the chapter. Some exercises require more thought, and these have been singly starred. Doubly starred exercises are harder still, and are suitable for more advanced courses. The bibliographic notes at the end of each chapter provide references for additional reading.
We wish to acknowledge Bell Laboratories for the use of its excellent UNIX™-based text preparation and data communication facilities that significantly eased the preparation of a manuscript by geographically separated authors. Many of our colleagues have read various portions of the manuscript and have given us valuable comments and advice. In particular, we would like to thank Ed Beckham, Jon Bentley, Kenneth Chu, Janet Coursey, Hank Cox, Neil Immerman, Brian Kernighan, Steve Mahaney, Craig McMurray, Alberto Mendelzon, Alistair Moffat, Jeff Naughton, Kerry Nemovicher, Paul Niamkey, Yoshio Ohno, Rob Pike, Chris Rouen, Maurice Schlumberger, Stanley Selkow, Chengya Shih, Bob Tarjan, W. Van Snyder, Peter Weinberger, and Anthony Yeracaris for helpful suggestions. Finally, we would like to give our warmest thanks to Mrs. Claire Metzger for her expert assistance in helping prepare the manuscript for typesetting.
A.V.A.
J.E.H.
J.D.U.