Introduction to Algorithms in Pascal
Title | Introduction to Algorithms in Pascal PDF eBook |
Author | Thomas W. Parsons |
Publisher | |
Pages | 447 |
Release | 1995 |
Genre | Computer algorithms |
ISBN | 9780471116004 |
Covering algorithms and data structure analysis using the PASCAL language, this text may be used to follow up an introductory course on PASCAL programming. It describes recent algorithms of note. Chapters on pattern matching, text compression and random numbers serve as case studies in which some of the algorithms seen earlier find application.
Introduction to Programming and Problem Solving with PASCAL
Title | Introduction to Programming and Problem Solving with PASCAL PDF eBook |
Author | Shane Caplin |
Publisher | John Wiley & Sons |
Pages | 202 |
Release | 1984 |
Genre | Computers |
ISBN | 9780471883470 |
Introduction to Algorithms, third edition
Title | Introduction to Algorithms, third edition PDF eBook |
Author | Thomas H. Cormen |
Publisher | MIT Press |
Pages | 1313 |
Release | 2009-07-31 |
Genre | Computers |
ISBN | 0262258102 |
The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.
Introduction To Algorithms
Title | Introduction To Algorithms PDF eBook |
Author | Thomas H Cormen |
Publisher | MIT Press |
Pages | 1216 |
Release | 2001 |
Genre | Computers |
ISBN | 9780262032933 |
An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms.
Data Structures Using Pascal
Title | Data Structures Using Pascal PDF eBook |
Author | Aaron M.. Tenenbaum |
Publisher | |
Pages | 297 |
Release | 1987 |
Genre | Data structures (Computer science) |
ISBN | 9780131966765 |
Algorithms, Part II
Title | Algorithms, Part II PDF eBook |
Author | Robert Sedgewick |
Publisher | Addison-Wesley Professional |
Pages | 973 |
Release | 2014-02-01 |
Genre | Computers |
ISBN | 0133847268 |
This book is Part II of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part II contains Chapters 4 through 6 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.
A Practical Introduction to Data Structures and Algorithm Analysis
Title | A Practical Introduction to Data Structures and Algorithm Analysis PDF eBook |
Author | Clifford A. Shaffer |
Publisher | |
Pages | 536 |
Release | 2001 |
Genre | Computers |
ISBN |
This practical text contains fairly "traditional" coverage of data structures with a clear and complete use of algorithm analysis, and some emphasis on file processing techniques as relevant to modern programmers. It fully integrates OO programming with these topics, as part of the detailed presentation of OO programming itself.Chapter topics include lists, stacks, and queues; binary and general trees; graphs; file processing and external sorting; searching; indexing; and limits to computation.For programmers who need a good reference on data structures.