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Data Structures

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Data Structures

This book is about the creation and analysis of efficient data structures. To understand the material in this book you should be comfortable enough in a programming language to be capable of working with and writing your own variables, arithmetic expressions, if-else conditions, loops, subroutines (also known as functions), pointers (also known as references or object handles), structures (also known as records or classes), simple input and output, and simple recursion.

Computer ScienceEngineering
Author
Wikipedia
Publisher
LibreTexts
Source
LibreTexts
License
CC BY-SA
Language
EN
Category
Information Technology
Read online Download PDF (open licence)
Contents· 71 sections
  1. 01: Introduction
  2. 1.01: The Node
  3. 1.02: Building a Chain from Nodes
  4. 1.03: The Principle of Induction
  5. 1.04: Induction on a Summation
  6. 02: Asymptotic Notation
  7. 2.01: Introduction
  8. 2.02: The O Notation
  9. 2.03: Big-Omega Notation
  10. 2.04: Theta Notation
  11. 2.05: Little-O Notation
  12. 2.06: Little Omega Notation
  13. 2.07: How asymptotic notation relates to analyzing complexity
  14. 2.08: A few examples of asymptotic notation
  15. 03: Arrays
  16. 3.01: Type
  17. 3.02: Bounds
  18. 3.03: Bounds check
  19. 3.04: Declaring Array Types
  20. 3.05: Array Access
  21. 04: List Structures and Iterators
  22. 4.01: Syntactic Sugar
  23. 4.02: Implementations
  24. 4.03: Bidirectional Lists
  25. 4.04: Vector Implementation
  26. 4.05: Tradeoffs
  27. 4.06: Advantages Disadvantages
  28. 05: Stacks and Queues
  29. 5.01: Stacks
  30. 5.02: Applications of Stacks
  31. 5.03: Queues
  32. 5.04: Deques
  33. 5.05: References
  34. 06: Trees
  35. 6.01: Traversal
  36. 6.02: Sample implementations for Tree Traversal
  37. 6.03: Examples of Tree Traversals
  38. 6.04: Balancing
  39. 6.05: Binary Search Trees
  40. 6.06: Example extract of Java code for binary tree delete operation
  41. 6.07: Red-Black trees
  42. 6.08: B Trees
  43. 6.09: Treaps
  44. 6.10: References
  45. 07: Min and Max Heaps
  46. 7.01: Compute the extreme value
  47. 7.02: Removing the Extreme Value
  48. 7.03: Inserting a value into the heap
  49. 7.04: TODO
  50. 7.05: Applications of Priority Heaps
  51. 08: Graphs
  52. 8.01: Directed Graphs
  53. 8.02: Undirected Graphs
  54. 8.03: Weighted Graphs
  55. 8.04: Graph Representations
  56. 8.05: Graph Traversals
  57. 09: Hash Tables
  58. 9.01: Time complexity and common uses of hash tables
  59. 9.02: Choosing a good hash function
  60. 9.03: Collision resolution
  61. 9.04: Table resizing
  62. 9.05: Ordered retrieval issue
  63. 9.06: Problems with hash tables
  64. 9.07: Other hash table algorithms
  65. 9.08: Implementations
  66. 9.09: References
  67. 10: Sets
  68. 10.01: List implementation
  69. 10.02: Bit array implementation
  70. 10.03: Associative array implementation
  71. 11: Tradeoffs