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The descriptions here are intended to give readers an understanding of the basic properties of as broad a range of fundamental algorithms as possible.
Ingenious methods ranging from binomial queues to patricia tries are described, all related to basic paradigms at the heart of computer science.
The second volume consists of four additional parts that cover strings, geometry, graphs, and advanced topics. My primary goal in developing these books has been to bring together the fundamental methods from these diverse areas, to provide access to the best methods known for solving problems by computer.
This book is thus intended for anyone conversant with a modern programming language and with the basic features of modern computer systems.
References that might help to fill in gaps in your background are suggested in the text. Most of the mathematical material supporting the analytic results is self-contained or is labeled as beyond the scope of this book , so little specific preparation in mathematics is required for the bulk of the book, although mathematical maturity is definitely helpful.
Use in the Curriculum There is a great deal of flexibility in how the material here can be taught, depending on the taste of the instructor and the preparation of the students.
The algorithms described here have found widespread use for years, and represent an essential body of knowledge for both the practicing programmer and the computer-science student. There is sufficient coverage of basic material for the book to be used for a course on data structures, and there is sufficient detail and coverage of advanced material for the book to be used for a course on algorithms.
Some instructors may wish to emphasize implementations and practical concerns; others may wish to emphasize analysis and theoretical concepts. A complete set of slide masters for use in lectures, sample programming assignments, interactive exercises for students, and other course materials may be found via the book's home page. An elementary course on data structures and algorithms might emphasize the basic data structures in Part 2 and their use in the implementations in Parts 3 and 4.
A course on design and analysis of algorithms might emphasize the fundamental material in Part 1 and Chapter 5, then study the ways in which the algorithms in Parts 3 and 4 achieve good asymptotic performance. A course on software engineering might omit the mathematical and advanced algorithmic material, and emphasize how to integrate the implementations given here into large programs or systems.
A course on algorithms might take a survey approach and introduce concepts from all these areas. Earlier editions of this book have been used in recent years at scores of colleges and universities around the world as a text for the second or third course in computer science and as supplemental reading for other courses. At Princeton, our experience has been that the breadth of coverage of material in this book provides our majors with an introduction to computer science that can be expanded upon in later courses on analysis of algorithms, systems programming and theoretical computer science, while providing the growing group of students from other disciplines with a large set of techniques that these people can immediately put to good use.
The exercises-most of which are new to this edition-fall into several types. Some are intended to test understanding of material in the text, and simply ask readers to work through an example or to apply concepts described in the text.
Others involve implementing and putting together the algorithms, or running empirical studies to compare variants of the algorithms and to learn their properties.
Still others are a repository for important information at a level of detail that is not appropriate for the text. Reading and thinking about the exercises will pay dividends for every reader. Algorithms of Practical Use Anyone wanting to use a computer more effectively can use this book for reference or for self-study. People with programming experience can find information on specific topics throughout the book. To a large extent, you can read the individual chapters in the book independently of the others, although, in some cases, algorithms in one chapter make use of methods from a previous chapter.
The orientation of the book is to study algorithms likely to be of practical use. Lecture Notes.
Algorithms, Etc. Art Gallery Theorems and Algorithms. Average Case Analysis of Algorithms on Sequences.
Combinatorial Optimization: Exact and Approximate Algorithms. Competitive Programming: Increasing the Lower Bound of Programming Contests. CS Graduate Algorithms. Toggle navigation FreeTechBooks. Algorithms and Data Structures Data structure is a way of storing data in a computer so that it can be used efficiently.
All categories Follow Books under this sub-category 53 books. The programs you will read about in this book were all written from scratch to solve difficult problems. Creative Commons Attribution 3. However, the emphasis of class design is upon those elements that are required for data structure implementation and simple ADTs. No attempt has been made to turn this into an OOP primer.
With an understanding of classes, the next series of chapters explore single and double linked lists, stacks and queues in great detail with many examples. Hashing techniques are covered as they relate to direct file processing.
Trees are covered including binary trees and binary searchable trees. The programming example illustrates how to construct a binary search tree for an ISAM data base. A benchmark program is also presented along with methods for timing and random number generation. One appendix provides a review of single and multiple dimensioned array processing and structure processing.
All sample programs are designed to use the VC.