Basic Concepts in Data Structures
Published on 5. October 2016
978-1-316-88371-6 (ISBN)
Description
Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions will allow students to test their understanding.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Publishing group
Cambridge University Press
Target group
College/higher education
File size
4880,22 MB
ISBN-13
978-1-316-88371-6 (9781316883716)
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Schweitzer Classification
Other editions
Additional editions
Shmuel Tomi Klein
Basic Concepts in Data Structures
Book
10/2016
Cambridge University Press
€98.00
Shipment within 15-20 days
Shmuel Tomi Klein
Basic Concepts in Data Structures
Book
10/2016
Cambridge University Press
€50.50
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Person
Shmuel Tomi Klein is Professor of Computer Science at Bar-Ilan University, Israel. His research focuses on data compression, text processing algorithms, lossless image compression, and improvements of deduplication techniques for large scale storage systems. He is a former chief scientist of Bar-Ilan University's Responsa Project, which won the Israel Prize in 2007. He is also a co-author of more than 100 academic publications and 10 patents.
Content
1. Why data structures? A motivating example; 2. Linear lists; 3. Graphs; 4. Trees; 5. AVL trees; 6. B-trees; 7. Heaps; 8. Sets; 9. Hash tables; 10. Sorting; 11. Codes.
