Chapter 0 Preface¶
Chapter 1 Introduction¶
Chapter 2 Programming Tutorials¶
- 2.1. Command Line Basics
- 2.2. Parsing Command Line Parameters In Your Program
- 2.3. Using Command Line Parameters in Eclipse
- 2.4. Installing the Web-CAT Submission Plug-in for Eclipse
- 2.5. Common Debugging Methods
- 2.6. Debugging In Eclipse
- 2.7. Using the Java Scanner Class
- 2.8. Random Access Files In Java
- 2.9. JUnit Testing And You
- 2.10. Writing JUnit Tests
- 2.11. Code Coverage In JUnit
- 2.12. Testing
- 2.13. Testing for Code Coverage
- 2.14. Bowling Test Coverage Example
- 2.15. Bowling Example: Testing to Code
Chapter 3 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
Chapter 4 Mathematical Background¶
Chapter 5 Algorithm Analysis¶
- 5.1. Chapter Introduction
- 5.2. Problems, Algorithms, and Programs
- 5.3. Comparing Algorithms
- 5.4. Best, Worst, and Average Cases
- 5.5. Faster Computer, or Faster Algorithm?
- 5.6. Asymptotic Analysis and Upper Bounds
- 5.7. Lower Bounds and \(\Theta\) Notation
- 5.8. Calculating Program Running Time
- 5.9. Analyzing Problems
- 5.10. Common Misunderstandings
- 5.11. Multiple Parameters
- 5.12. Space Bounds
- 5.13. Code Tuning and Empirical Analysis
- 5.14. Algorithm Analysis Summary Exercises
Chapter 6 Linear Structures¶
- 6.1. Chapter Introduction: Lists
- 6.2. A List ADT
- 6.3. Array-Based List Implementation
- 6.4. Linked Lists
- 6.5. Comparison of List Implementations
- 6.6. Doubly Linked Lists
- 6.7. List Element Implementations
- 6.8. Stacks
- 6.9. Linked Stacks
- 6.10. Freelists
- 6.11. Implementing Recursion
- 6.12. Queues
- 6.13. Linked Queues
- 6.14. Linear Structure Summary Exercises
Chapter 7 Hashing¶
Chapter 8 Recursion¶
- 8.1. Introduction to Recursion
- 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. Intermediate Recursion Code Completion Exercises
- 8.6. Writing Practice Exercises
- 8.7. Tracing Recursive Code
- 8.8. Recursion Code Tracing Practice Exercises
- 8.9. Recursion Summary Questions
Chapter 9 Sorting¶
- 9.1. Chapter Introduction: Sorting
- 9.2. Sorting Terminology and Notation
- 9.3. Insertion Sort
- 9.4. Bubble Sort
- 9.5. Selection Sort
- 9.6. The Cost of Exchange Sorting
- 9.7. Optimizing Sort Algorithms with Code Tuning
- 9.8. Shellsort
- 9.9. Mergesort Concepts
- 9.10. Implementing Mergesort
- 9.11. Quicksort
- 9.12. Heapsort
- 9.13. Binsort
- 9.14. Radix Sort
- 9.15. An Empirical Comparison of Sorting Algorithms
- 9.16. Lower Bounds for Sorting
- 9.17. Sorting Summary Exercises
Chapter 10 Searching¶
Chapter 11 Binary Trees¶
- 11.1. Binary Trees Chapter Introduction
- 11.2. Binary Trees
- 11.3. Binary Tree as a Recursive Data Structure
- 11.4. The Full Binary Tree Theorem
- 11.5. Binary Tree Traversals
- 11.6. Implementing Tree Traversals
- 11.7. Information Flow in Recursive Functions
- 11.7.1. Information Flow in Recursive Functions
- 11.7.2. Binary Tree Set Depth Exercise
- 11.7.3. Collect-and-return
- 11.7.4. Binary Tree Check Sum Exercise
- 11.7.5. Binary Tree Leaf Nodes Count Exercise
- 11.7.6. Binary Tree Sum Nodes Exercise
- 11.7.7. Combining Information Flows
- 11.7.8. Binary Tree Check Value Exercise
- 11.7.9. Combination Problems
- 11.7.10. Binary Tree Height Exercise
- 11.7.11. Binary Tree Get Difference Exercise
- 11.7.12. Binary Tree Has Path Sum Exercise
- 11.8. Binary Tree Node Implementations
- 11.9. Composite-based Expression Tree
- 11.10. Binary Tree Space Requirements
- 11.11. Binary Search Trees
- 11.12. Dictionary Implementation Using a BST
- 11.13. Binary Tree Guided Information Flow
- 11.14. Multiple Binary Trees
- 11.15. A Hard Information Flow Problem
- 11.16. Array Implementation for Complete Binary Trees
- 11.17. Heaps and Priority Queues
- 11.18. Huffman Coding Trees
- 11.19. Trees versus Tries
- 11.20. Proof of Optimality for Huffman Coding
- 11.21. Binary Tree Chapter Summary
Chapter 12 Design¶
Chapter 13 File Processing¶
Chapter 14 Memory Management¶
- 14.1. Chapter Introduction: Memory Management
- 14.2. Dynamic Storage Allocation
- 14.3. Sequential-Fit Methods
- 14.4. First Fit Memory Allocation
- 14.5. Circular First Fit
- 14.6. Best Fit Memory Manager
- 14.7. Worst Fit Memory Manager
- 14.8. Sequential Fit Peformance
- 14.9. Buddy Method and Other Memory Allocation Methods
- 14.10. Failure Policies and Garbage Collection
