Search Constraints
Number of results to display per page
Results for:
Keywords
Data structures (Computer science)
Remove constraint Keywords: Data structures (Computer science)
1  8 of 8
Search Results

ebook
"This is a textbook for first year Computer Science. Algorithms and Data Structures With Applications to Graphics and Geometry."BCcampus website.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Data structures (Computer science) Textbooks Algorithms
 Resource Type:
 ebook

ebook
This textbook teaches introductory data structures.
 Subjects:
 Computing
 Keywords:
 Textbooks Data structures (Computer science) Java (Computer program language)
 Resource Type:
 ebook

Others
A data structure is a particular way of organizing data in a computer so that it can be used effectively.For example, we can store a list of items having the same datatype using the array data structure. This page contains detailed tutorials on different data structures (DS) with topicwise problems, including (1) Array, (2) Linked List, (3) Stack, (4) Queue, (5) Binary Tree, (6) Binary Search Tree, (7) Heap, (8) Hashing, (9) Graph, (10) Matrix, (11) Advanced Data Structure.
 Course related:
 COMP 2011 Data Structures
 Subjects:
 Computing
 Keywords:
 Data structures (Computer science)
 Resource Type:
 Others

ebook
Offered as an introduction to the field of data structures and algorithms, Open Data Structures covers the implementation and analysis of data structures for sequences (lists), queues, priority queues, unordered dictionaries, ordered dictionaries, and graphs. Focusing on a mathematically rigorous approach that is fast, practical, and efficient, Morin clearly and briskly presents instruction along with source code. Analyzed and implemented in Java, the data structures presented in the book include stacks, queues, deques, and lists implemented as arrays and linkedlists; spaceefficient implementations of lists; skip lists; hash tables and hash codes; binary search trees including treaps, scapegoat trees, and redblack trees; integer searching structures including binary tries, xfast tries, and yfast tries; heaps, including implicit binary heaps and randomized meldable heaps; graphs, including adjacency matrix and adjacency list representations; and Btrees. A modern treatment of an essential computer science topic, Open Data Structures is a measured balance between classical topics and stateofthe art structures that will serve the needs of all undergraduate students or selfdirected learners.
 Subjects:
 Computing
 Keywords:
 Data structures (Computer science) Computer algorithms Textbooks
 Resource Type:
 ebook

ebook
Data structures and algorithms are among the most important inventions of the last 50 years, and they are fundamental tools software engineers need to know. But in my opinion, most of the books on these topics are too theoretical, too big, and too bottomup: Too theoretical: Mathematical analysis of algorithms is based on simplifying assumptions that limit its usefulness in practice. Many presentations of this topic gloss over the simplifications and focus on the math. In this book I present the most practical subset of this material and eliminate the rest. Too big: Most books on these topics are at least 500 pages, and some are more than 1000. By focusing on the topics I think are most useful for software engineers, I kept this book under 250 pages. Too bottomup: Many data structures books focus on how data structures work (the implementations), with less about how to use them (the interfaces). In this book, I go “top down”, starting with the interfaces. Readers learn to use the structures in the Java Collections Framework before getting into the details of how they work. Finally, many present this material out of context and without motivation: it’s just one damn data structure after another! I try to alleviate the boredom by organizing the topics around an application—web search—that uses data structures extensively, and is an interesting and important topic in its own right. This application also motivates some topics that are not usually covered in an introductory data structures class, including persistent data structures, with Redis, and streaming algorithms. This book also presents basic aspects of software engineering practice, including version control and unit testing. Each chapter ends with an exercise that allows readers to apply what they have learned. Each exercise includes automated tests that check the solution. And for most exercises, I present my solution at the beginning of the next chapter. This book is intended for college students in computer science and related fields, as well as professional software engineers, people training in software engineering, and people preparing for technical interviews. I assume that the reader knows Java at an intermediate level, but I explain some Java features along the way, and provide pointers to supplementary material. People who have read Think Java or Head First Java are prepared for this book.
 Subjects:
 Computing
 Keywords:
 Java (Computer program language) Data structures (Computer science) Textbooks
 Resource Type:
 ebook

ebook
An introductory coverage of algorithms and data structures with application to graphics and geometry.
 Subjects:
 Computing
 Keywords:
 Algorithms Data structures (Computer science) Textbooks
 Resource Type:
 ebook

Others
A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and games.
 Subjects:
 Computing
 Keywords:
 Computer programming Computer science Data structures (Computer science) Programming languages (Electronic computers) Computer networks Computer algorithms
 Resource Type:
 Others

Courseware
This course treats various methods to design and analyze datastructures and algorithms for a wide range of problems. The most important new datastructure treated is the graph, and the general methods introduced are: greedy algorithms, divide and conquer, dynamic programming and network flow algorithms. These general methods are explained by a number of concrete examples, such as simple scheduling algorithms, Dijkstra, FordFulkerson, minimum spanning tree, closestpairofpoints, knapsack, and BellmanFord. Throughout this course there is significant attention to proving the correctness of the discussed algorithms. All material for this course is in English. The recorded lectures, however, are in Dutch.
 Subjects:
 Computing
 Keywords:
 Algorithms Data structures (Computer science)
 Resource Type:
 Courseware