Ruby Data Structures and Algorithms

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248 pages
Language:
 English
Standard introduction to data structures and algorithms using the Ruby programming language covering stacks, queues, lists, trees, sets, maps, graphs, hashing, searching, and sorting.
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About the author

Christopher Fox is a Professor and Director of the Undergraduate Program in Computer Science at James Madison University. He holds a Ph.D. in Information Studies and an M.S. in Computer Science from Syracuse University, and M.A. and B.A. degrees in Philosophy from Michigan State University. Dr. Fox ha...

Description
Content

A concise introduction to data structures and algorithms in Ruby. Data structures are presented in a container hierarchy that includes stacks and queues as non-traversable dispensers, and lists, sets, and maps as traversable collections. Algorithm analysis is introduced and applied to linear and binary search, bubble sort, selection sort, insertion sort, merge sort and quicksort. The book also covers heaps and heapsort, unbalanced binary search trees, AVL trees, 2-3 trees, hashing, graph representations, and graph algorithms based on depth-and breadth-first search.

About the author

Christopher Fox is a Professor and Director of the Undergraduate Program in Computer Science at James Madison University. He holds a Ph.D. in Information Studies and an M.S. in Computer Science from Syracuse University, and M.A. and B.A. degrees in Philosophy from Michigan State University. Dr. Fox has over 20 years experience teaching Computer Science at JMU, Bowling Green State University, Villanova, Rutgers, and Colgate. Dr. Fox also spent a decade in software research and development at various companies, including AT&T Bell Laboratories. He has published numerous articles and several books, including Introduction to Software Engineering in the Unix/C Environment, and Introduction to Software Engineering Design.

  1.   Introduction 
  2.   Built-In Types 
  3.   Containers 
  4.   Assertions 
  5.   Stacks 
  6.   Queues 
  7.   Stacks and Recursion 
  8.   Collections and Iterators 
  9.   Lists 
  10.   Analyzing Algorithms 
  11.   Function Growth Rates 
  12.   Basic Sorting Algorithms 
  13.   Recurrences 
  14.   Merge Sort and Quicksort 
  15.   Trees, Heaps, and Heapsort 
  16.   Binary Trees 
  17.   Binary Search and Binary Search Trees 
  18.   AVL Trees 
  19.   2–3 Trees 
  20.   Sets 
  21.   Maps 
  22.   Hashing 
  23.   Hashed Collections 
  24.   Graphs 
  25.   Graph Algorithms