Preface¶
Introduction for Data Structures and Algorithms Courses¶
Design I¶
Introduction to Pointers in Java¶
- 3.1. Pointers Chapter Introduction
- 3.2. Basic References Part 1
- 3.3. Basic References Part 2
- 3.4. Pointers Syntax
- 3.5. Local Memory
- 3.6. Heap Memory
- 3.7. Link Nodes
- 3.8. Link Nodes Practice Exercises
- 3.9. Additional Practice Exercises
Mathematical Background¶
Searching I¶
Algorithm Analysis¶
- 6.1. Chapter Introduction
- 6.2. Problems, Algorithms, and Programs
- 6.3. Comparing Algorithms
- 6.4. Best, Worst, and Average Cases
- 6.5. Faster Computer, or Faster Algorithm?
- 6.6. Asymptotic Analysis and Upper Bounds
- 6.7. Lower Bounds and \(\Theta\) Notation
- 6.8. Calculating Program Running Time
- 6.9. Analyzing Problems
- 6.10. Common Misunderstandings
- 6.11. Multiple Parameters
- 6.12. Space Bounds
- 6.13. Code Tuning and Empirical Analysis
- 6.14. Algorithm Analysis Summary Exercises
- 6.15. Algorithm Analysis Summary Exercises
Linear Structures¶
- 7.1. Chapter Introduction: Lists
- 7.2. The List ADT
- 7.3. Array-Based List Implementation
- 7.4. Linked Lists
- 7.5. Comparison of List Implementations
- 7.6. Doubly Linked Lists
- 7.7. List Element Implementations
- 7.8. Stacks
- 7.9. Linked Stacks
- 7.10. Freelists
- 7.11. Implementing Recursion
- 7.12. Queues
- 7.13. Linked Queues
- 7.14. Linear Structure Summary Exercises
Recursion¶
- 8.1. Introduction
- 8.2. Writing a recursive function
- 8.3. Code Completion Practice Exercises
- 8.3.1. Introduction
- 8.3.2. Recursion Programming Exercise: Largest
- 8.3.3. Recursion Programming Exercise: Multiply
- 8.3.4. Recursion Programming Exercise: GCD
- 8.3.5. Recursion Programming Exercise: log
- 8.3.6. Recursion Programming Exercise: Cummulative Sum
- 8.3.7. Recursion Programming Exercise: Add odd values
- 8.3.8. Recursion Programming Exercise: Sum Of the Digits
- 8.3.9. Recursion Programming Exercise: Count Characters
- 8.4. Writing More Sophisticated Recursive Functions
- 8.5. Harder Code Completion Practice Exercises
- 8.6. Writing Practice Exercises
- 8.7. Tracing Recursive Code
- 8.8. Tracing Practice Exercises
- 8.9. Summary Exercises
Design II¶
Binary Trees¶
- 10.1. Binary Trees Chapter Introduction
- 10.2. Binary Trees
- 10.3. Binary Tree as a Recursive Data Structure
- 10.4. The Full Binary Tree Theorem
- 10.5. Binary Tree Traversals
- 10.6. Implementing Tree Traversals
- 10.7. Information Flow in Recursive Functions
- 10.7.1. Information Flow in Recursive Functions
- 10.7.2. Binary Tree Set Depth Exercise
- 10.7.3. Collect-and-return
- 10.7.4. Binary Tree Check Sum Exercise
- 10.7.5. Binary Tree Leaf Nodes Count Exercise
- 10.7.6. Binary Tree Sum Nodes Exercise
- 10.7.7. Combining Information Flows
- 10.7.8. Binary Tree Check Value Exercise
- 10.7.9. Combination Problems
- 10.7.10. Binary Tree Height Exercise
- 10.7.11. Binary Tree Get Difference Exercise
- 10.7.12. Binary Tree Has Path Sum Exercise
- 10.8. Binary Tree Node Implementations
- 10.9. Composite-based Expression Tree
- 10.10. Binary Tree Space Requirements
- 10.11. Binary Search Trees
- 10.12. Dictionary Implementation Using a BST
- 10.13. Binary Tree Guided Information Flow
- 10.14. Multiple Binary Trees
- 10.15. A Hard Information Flow Problem
- 10.16. Array Implementation for Complete Binary Trees
- 10.17. Heaps and Priority Queues
- 10.18. Huffman Coding Trees
- 10.19. Trees versus Tries
- 10.20. Proof of Optimality for Huffman Coding
- 10.21. Binary Tree Chapter Summary
Sorting¶
- 11.1. Chapter Introduction: Sorting
- 11.2. Sorting Terminology and Notation
- 11.3. Insertion Sort
- 11.4. Bubble Sort
- 11.5. Selection Sort
- 11.6. The Cost of Exchange Sorting
- 11.7. Optimizing Sort Algorithms with Code Tuning
- 11.8. Shellsort
- 11.9. Mergesort Concepts
- 11.10. Implementing Mergesort
- 11.11. Quicksort
- 11.12. Heapsort
- 11.13. Binsort
- 11.14. Radix Sort
- 11.15. An Empirical Comparison of Sorting Algorithms
- 11.16. Lower Bounds for Sorting
- 11.17. Sorting Summary Exercises
