New User? Sign Up. Create your account now. Signup with Email. Gender Male Female. Create Account. Already Have an Account? Often it is regarded as a central course of the curriculum. It is fascinating and instructive to trace the history of how the subject matter for this course has changed.
Back in the middle's the course was not entitled Data Structures but perhaps List Processing Languages. Newell, C. Shaw, and H. Simon , LISP 1. Farber, R. Griswold, and I. Knuth appeared. His thesis was that list processing was not a magical thing that could only be accomplished within a specially designed system.
Instead, he argued that the same techniques could be carried out in almost any language and he shifted the emphasis to efficient algorithm design. The new strategy was to explicitly construct a representation such as linked lists within a set of consecutive storage locations and to describe the algorithms by using English plus assembly language.
Progress in the study of data structures and algorithm design has continued. Out of this recent work has come many good ideas which we believe should be presented to students of computer science. It is our purpose in writing this book to emphasize those trends which we see as especially valuable and long lasting.
The most important of these new concepts is the need to distinguish between the specification of a data structure and its realization within an available programming language. This distinction has been mostly blurred in previous books where the primary emphasis has either been on a programming language or on representational techniques. Our attempt here has been to separate out the specification of the data structure from its realization and to show how both of these processes can be successfully accomplished.
The specification stage requires one to concentrate on describing the functioning of the data structure without concern for its implementation. This can be done using English and mathematical notation, but here we introduce a programming notation called axioms. The resulting implementation independent specifications valuable in two ways: i to help prove that a program which uses this data structure is correct and ii to prove that a particular implementation of the data structure is correct.
To describe a data structure in a representation independent way one needs a syntax. This can be seen at the end of section 1. This book also seeks to teach the art of analyzing algorithms but not at the cost of undue mathematical sophistication. The value of an implementation ultimately relies on its resource utilization: time and space.
This implies that the student needs to be capable of analyzing these factors. A great many analyses have appeared in the literature, yet from our perspective most students don't attempt to rigorously analyze their programs.
The data structures course comes at an opportune time in their training to advance and promote these ideas. For every algorithm that is given here we supply a simple, yet rigorous worst case analysis of its behavior. The growth of data base systems has put a new requirement on data structures courses, namely to cover the organization of large files.
Also, many instructors like to treat sorting and searching because of the richness of its examples of data structures and its practical application. The choice of our later chapters reflects this growing interest. One especially important consideration is the choice of an algorithm description language. Such a choice is often complicated by the practical matters of student background and language availability.
Our decision was to use a syntax which is particularly close to ALGOL, but not to restrict ourselves to a specific language. This gives us the ability to write very readable programs but at the same time we are not tied to the idiosyncracies of a fixed language. Wherever it seemed advisable we interspersed English descriptions so as not to obscure the main pointof an algorithm. For those who have only FORTRAN available, the algorithms are directly translatable by the rules given in the appendix and a translator can be obtained see appendix A.
On the other hand, we have resisted the temptation to use language features which automatically provide sophisticated data structuring facilities. We have done so on several grounds. One reason is the need to commit oneself to a syntax which makes the book especially hard to read by those as yet uninitiated.
Even more importantly, these automatic featules cover up the implementation detail whose mastery remains a cornerstone of the course. The basic audience for this book is either the computer science major with at least one year of courses or a beginning graduate student with prior training in a field other than computer science. This book contains more than one semester's worth of material and several of its chapters may be skipped without harm. The following are two scenarios which may help in deciding what chapters should be covered.
He would cover chapters one through five skipping sections 2. Then, in whatever time was left chapter seven on sorting was covered. In the first quarter's data structure course, chapters one through three are lightly covered and chapters four through six are completely covered. The second quarter starts with chapter seven which provides an excellent survey of the techniques which were covered in the previous quarter.
Thanks are also due to A. The first is the notion of writing nicely structured programs. Finally, we would like to thank our institutions, the University of Southern California and the University of Minnesota, for encouraging in every way our efforts to produce this book. Otherwise, they are either historically significant or develop the material in the text somewhat further. Continue with Google Continue with Facebook.
The data structures course comes at an opportune time in their training to advance and promote these ideas. On the other hand, we have resisted the temptation to use language features which automatically provide sophisticated data structuring facilities. Progress in the study of data structures and algorithm design has continued. For every algorithm that is given here we supply a simple, yet rigorous ddata case analysis of its behavior.
In addition there are two underlying currents which, though not explicitly emphasized are covered throughout. Instead, he argued that the same techniques could be carried out in almost any language and he shifted the emphasis to efficient algorithm design. The second quarter starts with chapter seven which provides an excellent survey of the techniques which were covered in the previous quarter. This can be done using English and mathematical notation, but here fundamenrals introduce a programming notation called axioms.
EduRev is a knowledge-sharing community that depends on everyone being able to pitch in when they know something. Many people have contributed their time and energy to improve this book. For all of the programs contained herein we have tried our best to structure them appropriately. Note that the material in chapter 2 is largely mathematical and can be skipped without harm. By continuing, I agree that I am at least 13 years old and structurex read and agree to the terms of service and privacy policy.
It is fascinating and instructive to trace the history of how the subject matter for this course has changed. Implementations of the data structures are then given followed by an attempt at verifying file: We have done so on several grounds. Then the material on external sorting, symbol tables and files is sufficient for the remaining time. Once defined, a high level design of its solution is made and each data structure is axiomatically specified.
This distinction has been mostly blurred in previous books where the primary emphasis has either been on a programming language or on representational techniques. This implies that the student needs to be capable of analyzing these factors. The second current is the choice of examples. The resulting implementation independent specifications sxhni in two ways:.
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