Chapter 0 modules¶

0.1. Data Structures and Algorithms
- 0.1.1. Data Structures and Algorithms
- 0.1.2. Some Software Engineering Topics
0.2. Spotlight: Carl Friedrich Gauss
- 0.2.1. Spotlight: Carl Friedrich Gauss
0.3. Spotlight: Francis Bacon
- 0.3.1. Spotlight: Francis Bacon
0.4. Command Line Basics
- 0.4.1. What’s A CLI?
0.5. Parsing Command Line Parameters In Your Progam
- 0.5.1. Parameters In Programming
0.6. Using Parameters in Eclipse
- 0.6.1. Using Parameters in Eclipse
0.7. Installing the Web-CAT Submission Plug-in for Eclipse
- 0.7.1. Introduction
- 0.7.2. Installing the Plug-in
  - 0.7.2.1. Un-Installing an Old Plug-in
  - 0.7.2.2. Installing the Plug-in
- 0.7.3. Installing student.jar
- 0.7.4. Installing formatting support
0.8. Common Debugging Methods
- 0.8.1. Common Debugging Methods
0.9. Debugging In Eclipse
- 0.9.1. Debugging In Eclipse
0.10. Reading Input (from Files or Otherwise)
- 0.10.1. The Scanner Class
0.11. Random Access Files In Java
- 0.11.1. Understanding File I/O
  - 0.11.1.1. Using RandomAccessFile Class
0.12. JUnit Testing And You
- 0.12.1. Getting Started
0.13. Writing JUnit Tests
- 0.13.1. Writing JUnit Tests
0.14. Code Coverage In JUnit
- 0.14.1. Code Coverage In JUnit
  - 0.14.1.1. Using EclEmma
0.15. Abstract Data Types
- 0.15.1. Abstract Data Types
0.16. Introduction to Object Oriented Programming
- 0.16.1. Introduction to Object Oriented Programming
0.17. The Unified Modeling Language
- 0.17.1. The Unified Modeling Language
  - 0.17.1.1. Static and Dynamic Diagrams
  - 0.17.1.2. Class Diagrams
0.18. Software Development Processes
- 0.18.1. Software Development Processes
0.19. Pointers Chapter Introduction
0.20. Basic References Part 1
- 0.20.1. Pointers and References
  - 0.20.1.1. What is a Pointer?
  - 0.20.1.2. What is a Reference?
- 0.20.2. Data Types in Java
- 0.20.3. Referencing and Dereferencing
- 0.20.4. changePointeeDataDirect
- 0.20.5. The Employee Class
- 0.20.6. Reference Assignments
- 0.20.7. circularList1
0.21. Basic References Part 2
- 0.21.1. Sharing
- 0.21.2. Shallow and Deep Copying
  - 0.21.2.1. What does it mean to copy?
- 0.21.3. Shallow and Deep Comparing
- 0.21.4. Bad References
  - 0.21.4.1. Why Are Bad Reference Bugs So Common?
0.22. Syntax of the Lambda Calculus
- 0.22.1. Lambda Calculus
- 0.22.2. Practice with Lambda Calculus Syntax
- 0.22.3. More Practice with Lambda Calculus Syntax
0.23. Local Memory
- 0.23.1. Local Memory
0.24. Heap Memory
- 0.24.1. Heap Memory
0.25. Link Nodes
- 0.25.1. Link Nodes
0.26. Link Nodes Practice Exercises
- 0.26.1. createList
- 0.26.2. iterateOverList
- 0.26.3. changePointeeNext1
- 0.26.4. addNodeAtHead
0.27. Additional Practice Exercises
- 0.27.1. changeHeadPointer2
- 0.27.2. changeQPointer
- 0.27.3. changeRPointer
- 0.27.4. changePointeeDataInDirect
- 0.27.5. circularList2
- 0.27.6. circularList3
- 0.27.7. changePointeeNext2
- 0.27.8. findValueInList
- 0.27.9. addNodeAtTail
- 0.27.10. changeNodesOrder1
- 0.27.11. changeNodesOrder2
0.28. Chapter Introduction
0.29. Sets and Relations
- 0.29.1. Set Notation
  - 0.29.1.1. Relations
- 0.29.2. Equivalence Relations
- 0.29.3. Partial Orders
0.30. Miscellaneous Notation
0.31. Logarithms
- 0.31.1. Logarithms
0.32. Summations
- 0.32.1. Summations
0.33. Recurrence Relations
- 0.33.1. Recurrence Relations
0.34. Mathematical Proof Techniques
- 0.34.1. Mathematical Proof Techniques
0.35. Estimation
0.36. Chapter Summary Questions
- 0.36.1. Chapter Summary Questions
0.37. Searching in an Array
- 0.37.1. Searching in an Array
  - 0.37.1.1. Sequential Search
  - 0.37.1.2. Binary Search
0.38. Chapter Introduction
0.39. Problems, Algorithms, and Programs
- 0.39.1. Problems, Algorithms, and Programs
0.40. Comparing Algorithms
- 0.40.1. Comparing Algorithms
- 0.40.2. Growth Rates Ordering Exercise
0.41. Best, Worst, and Average Cases
- 0.41.1. Best, Worst, and Average Cases
0.42. Faster Computer, or Faster Algorithm?
- 0.42.1. Faster Computer, or Faster Algorithm?
0.43. Asymptotic Analysis and Upper Bounds
- 0.43.1. Asymptotic Analysis and Upper Bounds
0.44. Lower Bounds and \(\Theta\) Notation
- 0.44.1. Lower Bounds and Theta Notation
0.45. Analyzing Problems
- 0.45.1. Analyzing Problems
0.46. Common Misunderstandings
- 0.46.1. Common Misunderstandings
0.47. Multiple Parameters
0.48. Space Bounds
0.49. Code Tuning and Empirical Analysis
- 0.49.1. Code Tuning and Empirical Analysis
  - 0.49.1.1. Empirical Analysis
0.50. Algorithm Analysis Summary Exercises
- 0.50.1. Summary Exercise: CS2
0.51. Algorithm Analysis Summary Exercises
- 0.51.1. Summary Exercise: CS3
0.52. Chapter Introduction: Lists
0.53. The List ADT
- 0.53.1. The List ADT
  - 0.53.1.1. Defining the ADT
- 0.53.2. List ADT Programming Exercise
0.54. Array-Based List Implementation
- 0.54.1. Array-Based List Implementation
  - 0.54.1.1. Insert
  - 0.54.1.2. Insert Practice Exericse
- 0.54.2. Append and Remove
  - 0.54.2.1. Remove Practice Exericise
- 0.54.3. Array-based List Practice Questions
0.55. Linked Lists
- 0.55.1. Linked Lists
- 0.55.2. Linked List Remove
0.56. Comparison of List Implementations
- 0.56.1. Space Comparison
- 0.56.2. Time Comparison
  - 0.56.2.1. Practice Questions
0.57. Doubly Linked Lists
- 0.57.1. Doubly Linked Lists
0.58. List Element Implementations
- 0.58.1. List Element Implementations
0.59. Stacks
- 0.59.1. Stack Terminology and Implementation
  - 0.59.1.1. Array-Based Stacks
- 0.59.2. Pop
0.60. Linked Stacks
- 0.60.1. Linked Stack Implementation
  - 0.60.1.1. Linked Stack Push
- 0.60.2. Linked Stack Pop
  - 0.60.2.1. Comparison of Array-Based and Linked Stacks
0.61. Freelists
- 0.61.1. Freelists
0.62. Implementing Recursion
0.63. Queues
- 0.63.1. Queue Terminology and Implementation
- 0.63.2. Array-based Dequeue Practice
0.64. Linked Queues
- 0.64.1. Linked Queues
- 0.64.2. Linked Dequeue
- 0.64.3. Comparison of Array-Based and Linked Queues
  - 0.64.3.1. Stack and Queue Summary Questions
0.65. Linear Structure Summary Exercises
- 0.65.1. Practice Questions
- 0.65.2. Chapter Review Questions
0.66. Introduction
- 0.66.1. Introduction
0.67. Writing a recursive function
- 0.67.1. Writing a recursive function
0.68. Code Completion Practice Exercises
- 0.68.1. Introduction
- 0.68.2. Recursion Programming Exercise: Largest
- 0.68.3. Recursion Programming Exercise: Multiply
- 0.68.4. Recursion Programming Exercise: GCD
- 0.68.5. Recursion Programming Exercise: log
- 0.68.6. Recursion Programming Exercise: Cummulative Sum
- 0.68.7. Recursion Programming Exercise: Add odd values
- 0.68.8. Recursion Programming Exercise: Sum Of the Digits
- 0.68.9. Recursion Programming Exercise: Count Characters
0.69. Writing More Sophisticated Recursive Functions
0.70. Harder Code Completion Practice Exercises
- 0.70.1. Recursion Programming Exercise: Minimum of array
- 0.70.2. Recursion Programming Exercise: Is Reverse
- 0.70.3. Recursion Programming Exercise: Decimal to Binary
0.71. Writing Practice Exercises
- 0.71.1. Recursion Programming Exercise: Cannonballs
- 0.71.2. Recursion Programming Exercise: Check Palindrome
- 0.71.3. Recursion Programming Exercise: Subset Sum
- 0.71.4. Recursion Programming Exercise: Pascal Triangle
0.72. Tracing Recursive Code
- 0.72.1. Tracing Recursive Code
  - 0.72.1.1. A Domino Analogy
  - 0.72.1.2. Towers of Hanoi
0.73. Tracing Practice Exercises
- 0.73.1. Forward Flow Tracing Exercises
- 0.73.2. Backward Flow Tracing Exercises
- 0.73.3. Find Error Tracing Exercises
- 0.73.4. Two Recursive Calls Tracing Exercises
- 0.73.5. How Many Times Tracing Exercises
- 0.73.6. Harder Tracing Exercises
0.74. Summary Exercises
- 0.74.1. Summary Questions
0.75. Design Patterns
- 0.75.1. Design Patterns
0.76. Alternative List ADT Designs
0.77. Comparing Records
- 0.77.1. Comparing Records
0.78. The Dictionary ADT
- 0.78.1. The Dictionary ADT
0.79. Binary Trees Chapter Introduction
0.80. Binary Trees
- 0.80.1. Definitions and Properties
- 0.80.2. Practice Questions
0.81. Binary Tree as a Recursive Data Structure
- 0.81.1. Binary Tree as a Recursive Data Structure
0.82. The Full Binary Tree Theorem
0.83. Binary Tree Traversals
- 0.83.1. Binary Tree Traversals
- 0.83.2. Postorder Traversal Practice
- 0.83.3. Inorder Traversal Practice
- 0.83.4. Summary Questions
0.84. Implementing Tree Traversals
- 0.84.1. Implementing Tree Traversals
  - 0.84.1.1. Base Case
  - 0.84.1.2. The Recursive Call
- 0.84.2. Binary Tree Increment By One Exercise
0.85. Information Flow in Recursive Functions
- 0.85.1. Information Flow in Recursive Functions
  - 0.85.1.1. Local
  - 0.85.1.2. Passing Down Information
- 0.85.2. Binary Tree Set Depth Exercise
- 0.85.3. Collect-and-return
- 0.85.4. Binary Tree Check Sum Exercise
- 0.85.5. Binary Tree Leaf Nodes Count Exercise
- 0.85.6. Binary Tree Sum Nodes Exercise
- 0.85.7. Combining Information Flows
- 0.85.8. Binary Tree Check Value Exercise
- 0.85.9. Combination Problems
- 0.85.10. Binary Tree Height Exercise
- 0.85.11. Binary Tree Get Difference Exercise
- 0.85.12. Binary Tree Has Path Sum Exercise
0.86. Binary Tree Node Implementations
- 0.86.1. Binary Tree Node Implementations
0.87. Composite-based Expression Tree
- 0.87.1. Composite-based Expression Tree
0.88. Binary Tree Space Requirements
- 0.88.1. Binary Tree Space Requirements
0.89. Binary Search Trees
- 0.89.1. Binary Search Tree Definition
  - 0.89.1.1. BST Search
- 0.89.2. BST Insert
- 0.89.3. BST Remove
- 0.89.4. BST Analysis
0.90. Dictionary Implementation Using a BST
0.91. Binary Tree Guided Information Flow
- 0.91.1. Binary Tree Guided Information Flow
- 0.91.2. Binary Search Tree Small Count Exercise
0.92. Multiple Binary Trees
- 0.92.1. Mirror Image Binary Trees Exercise
- 0.92.2. Same Binary Tree Exercise
- 0.92.3. Structurally Identical Binary Trees Exercise
0.93. A Hard Information Flow Problem
0.94. Array Implementation for Complete Binary Trees
- 0.94.1. Array Implementation for Complete Binary Trees
0.95. Heaps and Priority Queues
- 0.95.1. Heaps and Priority Queues
- 0.95.2. Building a Heap
- 0.95.3. Removing from the heap or updating an object’s priority
- 0.95.4. Priority Queues
0.96. Huffman Coding Trees
- 0.96.1. Huffman Coding Trees
0.97. Trees versus Tries
- 0.97.1. Trees versus Tries
0.98. Proof of Optimality for Huffman Coding
- 0.98.1. Proof of Optimality for Huffman Coding
0.99. Binary Tree Chapter Summary
- 0.99.1. Summary Questions
0.100. Chapter Introduction: Sorting
0.101. Sorting Terminology and Notation
- 0.101.1. Sorting Terminology and Notation
0.102. Insertion Sort
- 0.102.1. Insertion Sort
- 0.102.2. Insertion Sort Analysis
0.103. Bubble Sort
- 0.103.1. Bubble Sort
- 0.103.2. Bubble Sort Analysis
0.104. Selection Sort
- 0.104.1. Selection Sort
- 0.104.2. Selection Sort Analysis
0.105. The Cost of Exchange Sorting
- 0.105.1. The Cost of Exchange Sorting
- 0.105.2. Analysis
0.106. Optimizing Sort Algorithms with Code Tuning
- 0.106.1. Code Tuning for Simple Sorting Algorithms
0.107. Shellsort
- 0.107.1. Shellsort
- 0.107.2. Putting It Together
- 0.107.3. Shellsort Practice Exercise
- 0.107.4. Optimizing Shellsort
- 0.107.5. Shellsort Summary Questions
0.108. Mergesort Concepts
- 0.108.1. Mergesort Concepts
- 0.108.2. Mergesort Practice Exercise
0.109. Implementing Mergesort
- 0.109.1. Implementing Mergesort
0.110. Quicksort
- 0.110.1. Introduction
- 0.110.2. Partition
- 0.110.3. Putting It Together
- 0.110.4. Quicksort Analysis
0.111. Heapsort
- 0.111.1. Heapsort
- 0.111.2. Heapsort Proficiency Practice
- 0.111.3. Heapsort Analysis
0.112. Binsort
- 0.112.1. Binsort
0.113. Radix Sort
- 0.113.1. Radix Sort
- 0.113.2. Array-based Radix Sort
  - 0.113.2.1. Radix Sort Analysis
0.114. An Empirical Comparison of Sorting Algorithms
- 0.114.1. An Empirical Comparison of Sorting Algorithms
0.115. Lower Bounds for Sorting
- 0.115.1. Lower Bounds for Sorting
0.116. Sorting Summary Exercises
- 0.116.1. Sorting Summary Exercises
0.117. Chapter Introduction: File Processing
0.118. Primary versus Secondary Storage
0.119. Disk Drives
- 0.119.1. Disk Drives
0.120. Buffer Pools
- 0.120.1. Buffer Pools
0.121. The Programmer’s View of Files
0.122. External Sorting
- 0.122.1. External Sorting
- 0.122.2. Multiway Merging
  - 0.122.2.1. Empirical Results
  - 0.122.2.2. Summary
0.123. Introduction
- 0.123.1. Introduction
0.124. Hash Function Principles
- 0.124.1. Hash Function Principles
0.125. Sample Hash Functions
- 0.125.1. Sample Hash Functions
- 0.125.2. A Simple Hash Function for Strings
- 0.125.3. String Folding
- 0.125.4. Hash Function Practice
- 0.125.5. Hash Function Review Questions
0.126. Open Hashing
- 0.126.1. Open Hashing
0.127. Bucket Hashing
- 0.127.1. Bucket Hashing
- 0.127.2. An Alternate Approach
0.128. Collision Resolution
- 0.128.1. Collision Resolution
  - 0.128.1.1. The Problem with Linear Probing
0.129. Improved Collision Resolution
- 0.129.1. Linear Probing by Steps
- 0.129.2. Pseudo-Random Probing
- 0.129.3. Quadratic Probing
- 0.129.4. Double Hashing
0.130. Analysis of Closed Hashing
- 0.130.1. Analysis of Closed Hashing
0.131. Deletion
- 0.131.1. Deletion
- 0.131.2. Hashing Deletion Summary Questions
0.132. Hashing Chapter Summary Exercises
- 0.132.1. Hashing Review
0.133. Chapter Introduction: Memory Management
0.134. Dynamic Storage Allocation
- 0.134.1. Dynamic Storage Allocation
0.135. Sequential-Fit Methods
- 0.135.1. Sequential-Fit Methods
0.136. First Fit
- 0.136.1. First Fit
0.137. Circular First Fit
- 0.137.1. Circular First Fit
0.138. Best Fit
- 0.138.1. Best Fit
0.139. Worst Fit
- 0.139.1. Worst Fit
0.140. Sequential Fit Peformance
- 0.140.1. Sequential Fit Peformance
0.141. Other Memory Allocation Methods
- 0.141.1. Other Memory Allocation Methods
  - 0.141.1.1. Buddy Methods
  - 0.141.1.2. Other Methods
0.142. Failure Policies and Garbage Collection
0.143. Indexing Chapter Introduction
0.144. Linear Indexing
- 0.144.1. Linear Indexing
0.145. ISAM
0.146. Tree-based Indexing
- 0.146.1. Tree-based Indexing
0.147. 2-3 Trees
- 0.147.1. 2-3 Trees
0.148. B-Trees
- 0.148.1. B-Trees
  - 0.148.1.1. B+ Trees
  - 0.148.1.2. B-Tree Analysis
0.149. Indexing Summary Exercises
- 0.149.1. Indexing Summary
0.150. General Trees
- 0.150.1. General Trees
0.151. Union/Find and the Parent Pointer Implementation
- 0.151.1. The Union/Find Problem
0.152. Sequential Tree Representations
- 0.152.1. Sequential Tree Representations
- 0.152.2. Alternative Sequential Representation
- 0.152.3. Bit Vector Representation
- 0.152.4. General Tree Sequential Representation
0.153. Graphs Chapter Introduction
- 0.153.1. Graph Terminology and Implementation
  - 0.153.1.1. Graph Representations
- 0.153.2. Graph Terminology Questions
0.154. Graph Implementations
0.155. Graph Traversals
- 0.155.1. Graph Traversals
  - 0.155.1.1. Depth-First Search
- 0.155.2. Breadth-First Search
0.156. Topological Sort
- 0.156.1. Topological Sort
  - 0.156.1.1. Depth-first solution
  - 0.156.1.2. Queue-based Solution
0.157. Shortest-Paths Problems
- 0.157.1. Shortest-Paths Problems
  - 0.157.1.1. Single-Source Shortest Paths
0.158. Minimal Cost Spanning Trees
- 0.158.1. Minimal Cost Spanning Trees
  - 0.158.1.1. Prim’s Algorithm
  - 0.158.1.2. Prim’s Algorithm Alternative Implementation
0.159. Kruskal’s Algorithm
- 0.159.1. Kruskal’s Algorithm
0.160. All-Pairs Shortest Paths
0.161. Spatial Data Structures
- 0.161.1. Spatial Data Structures
  - 0.161.1.1. Multdimensional Keys
0.162. The PR Quadtree
- 0.162.1. The PR Quadtree
0.163. KD Trees
- 0.163.1. KD Trees
0.164. The Bintree
- 0.164.1. The Bintree
  - 0.164.1.1. Implementation Concerns
0.165. Other Spatial Data Structures
0.166. Data and Algorithm Analysis
- 0.166.1. Introduction
0.167. An Introduction to Problem Solving
- 0.167.1. An Introduction to Problem Solving
0.168. Semester Overview
- 0.168.1. Semester Overview
  - 0.168.1.1. Modeling Algorithm Cost
  - 0.168.1.2. Big Issues
0.169. Introduction to Analyzing a Problem
- 0.169.1. Towers of Hanoi
0.170. Bounds Review
- 0.170.1. Bounds Review
  - 0.170.1.1. Analyzing Problems
  - 0.170.1.2. Modeling the Inputs
0.171. Growth Rates Review
- 0.171.1. Growth Rates Review
  - 0.171.1.1. Asymptotic Notation
0.172. Summation Techniques
0.173. Solving Recurrence Relations
- 0.173.1. Solving Recurrence Relations
0.174. Chapter Introduction: Search
0.175. Analyzing Search in Unsorted Lists
- 0.175.1. Analyzing Search in Unsorted Lists
  - 0.175.1.1. Lower Bounds Proofs
0.176. Search in Sorted Arrays
- 0.176.1. Analysis
0.177. Self-Organizing Lists
- 0.177.1. Introduction
  - 0.177.1.1. Frequency Count
- 0.177.2. Move to Front
- 0.177.3. Transpose
  - 0.177.3.1. An Example
0.178. Bit Vectors for Representing Sets
0.179. Perfect Hashing
- 0.179.1. Perfect Hashing
0.180. Finding the Maximum Value
- 0.180.1. Finding the Maximum Value
0.181. Adversarial Lower Bounds Proofs
0.182. State Space Lower Bounds Proofs
0.183. Finding the \(i\) th Best Element
0.184. Optimal Sorting
0.185. Number Problems
- 0.185.1. Number Problems
0.186. The Transformation Concept
- 0.186.1. The Transformation Concept: Integer Multiplication
- 0.186.2. Polynomial Multiplication
0.187. The Fast Fourier Transform
- 0.187.1. The Fast Fourier Transform
0.188. Introduction to Probabilistic Algorithms
- 0.188.1. Probabilistic Algorithms
0.189. Finding Prime Numbers
0.190. Random Numbers
- 0.190.1. Random Numbers
0.191. Skip Lists
- 0.191.1. Skip Lists
0.192. Balanced Trees
0.193. The AVL Tree
0.194. The Splay Tree
0.195. The Red-Black Tree
- 0.195.1. Exercise 1
- 0.195.2. Exercise 2
0.196. The Sparse Matrix
0.197. Dynamic Programming
- 0.197.1. Dynamic Programming
  - 0.197.1.1. Computing Fibonacci Numbers
  - 0.197.1.2. The Knapsack Problem
0.198. Amortized Analysis
0.199. 0/1 Knapsack Problem
- 0.199.1. 0/1 Knapsack Problem
  - 0.199.1.1. Exercise 1
- 0.199.2. Exercise 2
- 0.199.3. Exercise 3
- 0.199.4. Exercise 4
0.200. Edit Distance
- 0.200.1. Edit Distance
- 0.200.2. Exercise 1
- 0.200.3. Exercise 2
0.201. KMP String Search Algorithm
- 0.201.1. KMP String Search Algorithm
0.202. Boyer-Moore String Search Algorithm
- 0.202.1. Boyer-Moore String Search Algorithm
0.203. Rabin-Karp String Search Algorithm [Draft]
- 0.203.1. Rabin-Karp String Search Algorithm [Draft]
0.204. General Tree Implementations
- 0.204.1. General Tree Implementations
0.205. K-ary Tree Implementations
- 0.205.1. K-ary Tree Implementations
0.206. Limits to Computing
- 0.206.1. Limits to Computing
0.207. Reductions
- 0.207.1. Reductions
0.208. NP-Completeness
- 0.208.1. NP-Completeness
  - 0.208.1.1. Hard Problems
  - 0.208.1.2. The Theory of NP-Completeness
0.209. Circuit Satisfiability
- 0.209.1. Circuit Satisfiability
0.210. Formula Satisfiability
- 0.210.1. Formula Satisfiability
0.211. 3-CNF Satisfiability
- 0.211.1. 3-CNF Satisfiability
0.212. The Clique Problem
- 0.212.1. The Clique Problem
0.213. The Independent Set Problem
- 0.213.1. Independent Set
0.214. The Vertex Cover Problem
- 0.214.1. Vertex Cover
0.215. The Hamiltonian Cycle Problem
- 0.215.1. Hamiltonian Cycle
0.216. The Traveling Salesman Problem
- 0.216.1. Traveling Salesman
0.217. NP-Completeness Proofs
- 0.217.1. NP-Completeness Proofs
0.218. Reduction of Circuit SAT to SAT
- 0.218.1. Reduction of Circuit SAT to SAT
0.219. Reduction of SAT to 3-SAT
- 0.219.1. Reduction of SAT to 3-SAT
0.220. Reduction of 3-SAT to Clique
- 0.220.1. Reduction of 3-SAT to Clique
0.221. Reduction of Clique to Independent Set
- 0.221.1. Clique to Independent Set
0.222. Reduction of Independent Set to Vertex Cover
- 0.222.1. Independent Set to Vertex Cover
0.223. Reduction of 3-SAT to Hamiltonian Cycle
- 0.223.1. 3-SAT to Hamiltonian Cycle
0.224. Reduction of Hamiltonian Cycle to Traveling Salesman
- 0.224.1. Hamiltonian Cycle to Traveling Salesman
0.225. Coping with NP-Complete Problems
0.226. Unsolveable Problems
- 0.226.1. Unsolveable Problems
0.227. Turing Machines
- 0.227.1. Turing Machines
0.228. Derivations and Parse Trees
- 0.228.1. Parse Trees
  - 0.228.1.1. First Sample Grammar
- 0.228.2. Strings Generated by a Grammar
- 0.228.3. Characterizing a Language: Example 1
- 0.228.4. Characterizing a Language: Example 2
0.229. Ambiguous Grammars
- 0.229.1. Second Sample Grammar
- 0.229.2. Ambiguity in Grammars
- 0.229.3. Ambiguous Grammar - Part 1
- 0.229.4. Ambiguous Grammar - Part 2
- 0.229.5. Ambiguous Grammar - Part 3
- 0.229.6. Discovering Ambiguity
0.230. Enforcing Order of Operations
- 0.230.1. Evaluation of Expressions
  - 0.230.1.1. Third Sample Grammar
- 0.230.2. Expression Evaluation
- 0.230.3. Associativity
- 0.230.4. Precedence and Associativity
- 0.230.5. Characterizing a Language Given a BNF Grammar
- 0.230.6. Extended BNF
0.231. Parser Generators
- 0.231.1. Jison
- 0.231.2. More practice with Jison
0.232. Using Parser Generators to Interpret a Language
- 0.232.1. Annotating Jison Grammars
0.233. List Construction and Deconstruction
- 0.233.1. Constructing Lists with fp.cons
- 0.233.2. Deconstructing Lists with fp.hd and fp.tl
- 0.233.3. Practicing List Manipulations with the fp module
- 0.233.4. fp.isNull, fp.isEq, and fp.isZero
0.234. Developing Basic, Recursive List-processing Functions
- 0.234.1. Recursive List Processing Example: sum( list )
- 0.234.2. Recursive List Processing Example: isMember( num, list )
- 0.234.3. Recursive List Processing Example: subst( new, old, list )
0.235. Recurring On Lists That Aren’t Flat
- 0.235.1. Deep Recursion in FP
- 0.235.2. Deep Recursion on Binary Search Trees
- 0.235.3. Practice with Deep Recursion
- 0.235.4. More Practice with Deep Recursion
0.236. Using Helper Functions with Accumulators
- 0.236.1. Using Helpers to Write reverse and split Functions
- 0.236.2. Using the split Function to Develop a Sorting Function
- 0.236.3. Additional Practice with the Accumulator Pattern
0.237. Scope, Closures, Higher-order Functions, Static vs. Dynamic Binding
- 0.237.1. Scope, Closures, Higher-order Functions
- 0.237.2. Practice with Higher-order Functions and Anonymous Functions
- 0.237.3. More Practice with Higher-order Functions and Anonymous Functions
- 0.237.4. Practice with Static vs. Dynamic Binding Rules
0.238. Procedural Abstraction: Map, Curry, and Compose
- 0.238.1. The Mapping Pattern
- 0.238.2. Function Composition
- 0.238.3. Currying
- 0.238.4. More currying
0.239. Procedural Abstraction: The Filtering and Folding (or Reduce) Patterns
- 0.239.1. The Filtering Pattern
- 0.239.2. The Folding/Reduce Pattern
- 0.239.3. Practice with the Mapping and Reduce Patterns
- 0.239.4. More Practice with the Reduce Pattern
0.240. Combining Map and Reduce
- 0.240.1. The MapReduce Paradigm
0.241. Continuations and Continuation Passing
- 0.241.1. Tail recursive functions
- 0.241.2. Continuation-Passing Style
- 0.241.3. Continuation-Passing Style Practice Problem (Part 1)
- 0.241.4. Continuation-Passing Style Practice Problem (Part 2)
- 0.241.5. Continuation-Passing Style Practice Problem (Part 3)
- 0.241.6. More CPS Practice
0.22. Syntax of the Lambda Calculus
- 0.22.1. Lambda Calculus
- 0.22.2. Practice with Lambda Calculus Syntax
- 0.22.3. More Practice with Lambda Calculus Syntax
0.242. Semantics of the Lambda Calculus
- 0.242.1. Semantics of the Lambda Calculus
- 0.242.2. Practice with Lambda Calculus Semantics
0.243. Free and Bound Variables
- 0.243.1. Free and Bound Variables
- 0.243.2. Identifying Free Variables
- 0.243.3. Identifying Bound Variables
- 0.243.4. Formal Definition of Free Variables
0.244. Alpha-Conversion
- 0.244.1. Alpha-Conversion Rule
- 0.244.2. Practice with Alpha Conversion
0.245. The Substitution-Based Model of Evaluation
- 0.245.1. Substitution Algorithm
- 0.245.2. Identifying Substitution Subcases of Case 1
- 0.245.3. Identifying Substitution Subcases of Case 2
- 0.245.4. Identifying Substitution Case 3
- 0.245.5. Identifying Substitution Cases and Subcases
- 0.245.6. Performing the Substitution Algorithm
0.246. Beta-Reduction
- 0.246.1. Beta-Redexes
- 0.246.2. Identifying Beta-Redexes
- 0.246.3. Beta-Reduction is a Substitution
- 0.246.4. Some Beta-Reductions Require Alpha-Conversion
- 0.246.5. Performing Beta-Reductions
0.247. Reduction Strategies
- 0.247.1. Applicative Order
- 0.247.2. Normal Order
- 0.247.3. Beta-Reduction Order (1)
- 0.247.4. Beta-Reduction Order (2)
- 0.247.5. Applicative Order Proficiency Exercise
- 0.247.6. Normal Order Proficiency Exercise
0.248. Church Numerals and Booleans
- 0.248.1. Church Booleans
- 0.248.2. Encoding If-Then-Else
- 0.248.3. Encoding OR
- 0.248.4. Church Numerals
- 0.248.5. Church Numerals with Addition and Multiplication
0.249. Recursive Functions
- 0.249.1. Fixed-points of Functions
- 0.249.2. The Y Fixed-point Combinator
- 0.249.3. Using Y to Implement Factorial
- 0.249.4. Identifying Fixed Point Combinators
0.250. Defining SLang 1
- 0.250.1. Syntax of SLang 1
- 0.250.2. Concrete Syntax of SLang 1
- 0.250.3. More Practice with the Concrete Syntax of SLang 1
- 0.250.4. Abstract Syntax of SLang 1
- 0.250.5. Curry in SLang 1
- 0.250.6. Semantics of SLang 1
0.251. Environment-based Model of Evaluation
- 0.251.1. Environment Data Structure
- 0.251.2. Determining Values Bound to a Variable
- 0.251.3. Evaluation of Expression Within an Environment
- 0.251.4. Determining Denoted Values in SLang 1
0.252. Let Expressions
- 0.252.1. Let Blocks
- 0.252.2. Let Blocks As Syntactic Sugar
- 0.252.3. Nested Lets
- 0.252.4. Nested Lets with Closures
0.253. Defining SLang 2
- 0.253.1. SLang 2: An Imperative Language
- 0.253.2. Output of SLang 2 Program
0.254. Tying The Knot
- 0.254.1. Implementing Recursion Efficiently
- 0.254.2. Practice TTK
0.255. Parameter-Passing Mechanisms
- 0.255.1. Call By Value vs. Call By Reference
- 0.255.2. Copy-Restore
- 0.255.3. Macro Expansion
- 0.255.4. Call By Name
- 0.255.5. Comprehensive Review of the Five Methods Studied So Far
0.256. Lazy Lists
- 0.256.1. Infinite Sequences
- 0.256.2. Practice With Infinite Sequences
- 0.256.3. Practice With Infinite Sequences (2)
- 0.256.4. Practice With Infinite Sequences (3)
0.257. Types in Programming Languages
- 0.257.1. Motivating Examples
- 0.257.2. Type System: Definition
- 0.257.3. Type System: Static Versus Dynamic
- 0.257.4. Type System: Safe Versus Unsafe
- 0.257.5. Type System: Strong Versus Weak
- 0.257.6. Type System: Typed Variables or Values
- 0.257.7. Type System: Explicit Versus Implicit typing
- 0.257.8. The Many Uses of Type Systems
0.258. Type Inference
- 0.258.1. Type Environments
- 0.258.2. Typing Rules Expressed as Post Systems
- 0.258.3. Typing in a Scaled-down ML
- 0.258.4. Using Post System Rules to Describe Type Inferencing in ML
- 0.258.5. Parametric Polymorphism in ML
- 0.258.6. Type inferencing in ML
- 0.258.7. Type Inferencing Problem 1
- 0.258.8. Type Inferencing Problem 2
- 0.258.9. Type Inferencing Problem 3
- 0.258.10. Type Inferencing Problem 4
- 0.258.11. Type Inferencing Problem 5
- 0.258.12. Type Inferencing Problem 6
0.259. GLOSSARY
0.260. Formal Languages
- 0.260.1. Introduction
- 0.260.2. Prerequisites
- 0.260.3. What we will do
- 0.260.4. Process
0.261. Overview
- 0.261.1. Languages, Grammars, and Machines
- 0.261.2. Language Hierarchy
- 0.261.3. Power of Machines
- 0.261.4. Application: Compilers
  - 0.261.4.1. Stages of a Compiler
- 0.261.5. Some Mindbending Ideas
0.262. Major Concepts
- 0.262.1. Introduction
- 0.262.2. Languages
- 0.262.3. Grammars
- 0.262.4. Automata
0.263. Deterministic Finite Acceptors
- 0.263.1. DFA: Deterministic Finite Acceptor
0.264. Non-Deterministic Finite Automata
- 0.264.1. NFA: Non-Deterministic Finite Automata
- 0.264.2. NFA vs. DFA: Which is more powerful?
0.265. Minimizing the Number of States in a DFA
- 0.265.1. Minimizing the Number of States in a DFA
0.266. Regular Expressions
- 0.266.1. Regular Expressions
  - 0.266.1.1. Precedence Rules
  - 0.266.1.2. Examples of Regular Expressions
- 0.266.2. Regular Expressions vs. Regular Languages
- 0.266.3. Converting Regular Languages to Regular Expressions
0.267. Regular Grammars
- 0.267.1. Regular Grammars
0.268. Closure Properties of Regular Grammars
- 0.268.1. Closure Properties of Regular Grammars
0.269. Identifying Non-regular Languages
- 0.269.1. Identifying Non-regular Languages
0.270. Properties
- 0.270.1. Properties and Proving: Problem 1
- 0.270.2. Properties and Proving - Problem 2
0.271. Context-Free Languages
- 0.271.1. Context-Free Languages
- 0.271.2. Ambiguity
- 0.271.3. Eliminating Grammar Ambiguity
- 0.271.4. Extended BNF
0.272. Transforming Grammars
- 0.272.1. Transforming Grammars
0.273. Pushdown Automata
- 0.273.1. Pushdown Automata
  - 0.273.1.1. Example of transitions
  - 0.273.1.2. Equivalence of Acceptance Definitions
0.274. PDAs and Context Free Languages
- 0.274.1. PDAs and Context Free Languages
0.275. Deterministic Pushdown Automata
- 0.275.1. Deterministic Pushdown Automata
- 0.275.2. Grammars for Deterministic Context-free Languages
0.276. Properties of Context-Free Languages
- 0.276.1. Properties of Context-Free Languages
  - 0.276.1.1. (Chap 8.2) Closure Properties of CFLs
0.277. Models of Computation
- 0.277.1. Models of Computation
0.227. Turing Machines
- 0.227.1. Turing Machines
0.278. Parsing Introduction
- 0.278.1. Introduction
0.279. LL Parsing
- 0.279.1. LL Parsing
0.280. LR Parsing
- 0.280.1. LR Parsing
0.281. CYK Parsing
- 0.281.1. CYK Parsing
  - 0.281.1.1. CYK Parsing Algorithm
  - 0.281.1.2. Algorithm
0.282. Structure of a Compiler
- 0.282.1. What is a compiler?
  - 0.282.1.1. Translator
- 0.282.2. Language Processing System
  - 0.282.2.1. Compiler
- 0.282.3. Overview of General Compiler
- 0.282.4. Phases of Compilation
0.283. Recursively Enumerable Languages
- 0.283.1. Recursively Enumerable Languages
  - 0.283.1.1. Enumeration procedure for recursive languages
  - 0.283.1.2. Enumeration procedure for recursively enumerable languages
0.284. Sheet 1
- 0.284.1. Exercise 1
- 0.284.2. Exercise 2
- 0.284.3. Exercise 3
- 0.284.4. Exercise 4
- 0.284.5. Exercise 5
- 0.284.6. Exercise 6
- 0.284.7. Exercise 7
0.285. Sheet 2
- 0.285.1. Exercise 1
- 0.285.2. Exercise 2
- 0.285.3. Exercise 3
- 0.285.4. Exercise 4
0.286. Sheet 3
- 0.286.1. Exercise 1
- 0.286.2. Exercise 2
- 0.286.3. Exercise 3
- 0.286.4. Exercise 4
- 0.286.5. Exercise 5
- 0.286.6. Exercise 6
0.287. Sheet 5
- 0.287.1. Exercise 1
- 0.287.2. Exercise 2
0.288. Sheet 6
- 0.288.1. Exercise 1
- 0.288.2. Exercise 2
- 0.288.3. Exercise 3
- 0.288.4. Exercise 4
0.289. Sheet 7
- 0.289.1. Exercise 1
0.290. Sheet 1
- 0.290.1. Exercise 1
- 0.290.2. Exercise 2
- 0.290.3. Exercise 3
- 0.290.4. Exercise 4
- 0.290.5. Exercise 5
- 0.290.6. Exercise 6
- 0.290.7. Exercise 7
0.291. Sheet 2 Practice
- 0.291.1. Exercise 1
- 0.291.2. Exercise 2
- 0.291.3. Exercise 3
- 0.291.4. Exercise 4
0.292. Sheet 3 Practice
- 0.292.1. Exercise 1
- 0.292.2. Exercise 2
- 0.292.3. Exercise 3
- 0.292.4. Exercise 4
- 0.292.5. Exercise 5
- 0.292.6. Exercise 6
0.293. Sheet 5 Practice
- 0.293.1. Exercise 1
- 0.293.2. Exercise 2
0.294. List Iteration
- 0.294.1. List Iteration
0.295. List Iteration Visualizations
- 0.295.1. List Iteration Visualizations
0.296. Classwork 8
- 0.296.1. List Exercise 1
0.297. Homework 8
- 0.297.1. List Exercise 2

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