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Data Structures & Algorithm Analysis in Java

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Data Structures & Algorithm Analysis in Java (1st Edition).md

Data Structures & Algorithm Analysis in Java (1st Edition)

Information

Author: Mark Allen Weiss
Publisher: Addison-Wesley, 1999
ISBN-10: 0-201-35754-2 (0201357542)
ISBN-13: 978-0-201-35754-7 (9780201357547)

Links

Publisher Link:
- https://www.pearson.com/us/higher-education/product/Weiss-Data-Structures-and-Algorithm-Analysis-in-Java/9780201357547.html
Amazon Link:
- https://amzn.com/0201357542
Google Books Link:
- https://books.google.com.hk/books?id=xAzDQgAACAAJ

Chapter 1 Introduction
- 1.1. What's the Book About?
- 1.2. Mathematics Review
  - 1.2.1. Exponents
  - 1.2.2. Logarithms
  - 1.2.3. Series
  - 1.2.4. Modular Arithmetic
  - 1.2.5. The P Word
- 1.3. A Brief Introduction to Recursion
- 1.4. Generic Objects in Java ➖
  - 1.4.1. The IntCell Class ➖
  - 1.4.2. The MemoryCell Class ➖
  - 1.4.3. Implementing Generic findMax ➖
- 1.5. Exceptions ➖
- 1.6. Input and Output ➖
  - 1.6.1. Basic Stream Operations ➖
  - 1.6.2. The StringTokenizer Object ➖
  - 1.6.3. Sequential Files ➖
- 1.7. Code Organization ➖
  - 1.7.1. Packages ➖
  - 1.7.2. The MyInteger Class ➖
  - 1.7.3. Efficiency Considerations ➖
  - Summary
  - Exercises
  - References
Chapter 2 Algorithm Analysis
- 2.1. Mathematical Background
- 2.2. Model
- 2.3. What to Analyze
- 2.4. Running Time Calculations
  - 2.4.1. A Simple Example
  - 2.4.2. General Rules
  - 2.4.3. Solutions for the Maximum Subsequence Sum Problem
  - 2.4.4. Logarithms in the Running Time
  - 2.4.5. Checking Your Analysis ➖
  - 2.4.6. A Grain of Salt
  - Summary
  - Exercises
  - References
Chapter 3 Lists, Stacks, and Queues
- 3.1. Abstract Data Types (ADTs)
- 3.2. The List ADT
  - 3.2.1. Simple Array Implementation of Lists
  - 3.2.2. Linked Lists ➗
  - 3.2.3. Programming Details ➖
  - 3.2.4. Doubly Linked Lists ➖
  - 3.2.5. Circular Linked Lists ➖
  - 3.2.6. Examples ➖
  - 3.2.7. Cursor Implementation of Linked Lists ➖
- 3.3. The Stack ADT
  - 3.3.1. Stack Model
  - 3.3.2. Implementation of Stacks
  - 3.3.3. Applications
- 3.4. The Queue ADT
  - 3.4.1. Queue Model
  - 3.4.2. Array Implementation of Queues
  - 3.4.3. Applications of Queues
  - Summary
  - Exercises
Chapter 4 Trees
- 4.1. Preliminaries
  - 4.1.1. Implementation of Trees
  - 4.1.2. Tree Traversals with an Application
- 4.2. Binary Trees
  - 4.2.1. Implementation
  - 4.2.2. An Example: Expression Trees
- 4.3. The Search Tree ADT --- Binary Search Trees
  - 4.3.1. find ➗
  - 4.3.2. findMin and findMax
  - 4.3.3. insert
  - 4.3.4. remove
  - 4.3.5. Average-Case Analysis
- 4.4. AVL Trees
  - 4.4.1. Single Rotation
  - 4.4.2. Double Rotation
- 4.5. Splay Trees
  - 4.5.1. A Simple Idea (That Does Not Work)
  - 4.5.2. Splaying
- 4.6. Tree Traversals (Revisited)
- 4.7. B-Trees
  - Summary
  - Exercises
  - References
Chapter 5 Hashing
- 5.1. General Idea
- 5.2. Hash Function
- 5.3. Separate Chaining
- 5.4. Open Addressing ➗
  - 5.4.1. Linear Probing
  - 5.4.2. Quadratic Probing
  - 5.4.3. Double Hashing
- 5.5. Rehashing
- 5.6. Extendible Hashing
  - Summary
  - Exercises
  - References
Chapter 6 Priority Queues (Heaps)
- 6.1. Model
- 6.2. Simple Implementations
- 6.3. Binary Heap
  - 6.3.1. Structure Property
  - 6.3.2. Heap Order Property
  - 6.3.3. Basic Heap Operations
  - 6.3.4. Other Heap Operations
- 6.4. Applications of Priority Queues
  - 6.4.1. The Selection Problem
  - 6.4.2. Event Simulation
- 6.5. d-Heaps
- 6.6. Leftist Heaps
  - 6.6.1. Leftist Heap Property
  - 6.6.2. Leftist Heap Operations
- 6.7. Skew Heaps
- 6.8. Binomial Queues
  - 6.8.1. Binomial Queue Structure
  - 6.8.2. Binomial Queue Operations
  - 6.8.3. Implementation of Binomial Queues
  - Summary
  - Exercises
  - References
Chapter 7 Sorting
- 7.1. Preliminaries
- 7.2. Insertion Sort
  - 7.2.1. The Algorithm
  - 7.2.2. Analysis of Insertion Sort
- 7.3. A Lower Bound for Simple Sorting Algorithms
- 7.4. Shellsort
  - 7.4.1. Worst-Case Analysis of Shellsort
- 7.5. Heapsort
  - 7.5.1. Analysis of Heapsort
- 7.6. Mergesort
  - 7.6.1. Analysis of Mergesort
- 7.7. Quicksort
  - 7.7.1. Picking the Pivot
  - 7.7.2. Partitioning Strategy
  - 7.7.3. Small Arrays
  - 7.7.4. Actual Quicksort Routines
  - 7.7.5. Analysis of Quicksort
  - 7.7.6. A Linear-Expected-Time Algorithm for Selection
- 7.8. A General Lower Bound for Sorting
  - 7.8.1. Decision Trees
- 7.9. Bucket Sort
- 7.10. External Sorting
  - 7.10.1. Why We Need New Algorithms
  - 7.10.2. Model for External Sorting
  - 7.10.3. The Simple Algorithm
  - 7.10.4. Multiway Merge
  - 7.10.5. Polyphase Merge
  - 7.10.6. Replacement Selection
  - Summary
  - Exercises
  - References
Chapter 8 The Disjoint Set ADT ➗
- 8.1. Equivalence Relations
- 8.2. The Dynamic Equivalence Problem
- 8.3. Basic Data Structure
- 8.4. Smart Union Algorithms
- 8.5. Path Compression
- 8.6. Worst Case for Union-by-Rank and Path Compression
  - 8.6.1. Analysis of the Union/Find Algorithm
- 8.7. An Application
  - Summary
  - Exercises
  - References
Chapter 9 Graph Algorithms
- 9.1. Definitions
  - 9.1.1. Representation of Graphs
- 9.2. Topological Sort
- 9.3. Shortest-Path Algorithms
  - 9.3.1. Unweighted Shortest Paths
  - 9.3.2. Dijkstra's Algorithm
  - 9.3.3. Graphs with Negative Edge Costs
  - 9.3.4. Acyclic Graphs
  - 9.3.5. All-Pairs Shortest Path
- 9.4. Network Flow Problems
  - 9.4.1. A Simple Maximum-Flow Algorithm
- 9.5. Minimum Spanning Tree
  - 9.5.1. Prim's Algorithm
  - 9.5.2. Kruskal's Algorithm
- 9.6. Applications of Depth-First Search
  - 9.6.1. Undirected Graphs
  - 9.6.2. Biconnectivity
  - 9.6.3. Euler Circuits
  - 9.6.4. Directed Graphs
  - 9.6.5. Finding Strong Components
- 9.7. Introduction to NP-Completeness
  - 9.7.1. Easy vs. Hard
  - 9.7.2. The Class NP
  - 9.7.3. NP-Complete Problems
  - Summary
  - Exercises
  - References
Chapter 10 Algorithm Design Techniques
- 10.1. Greedy Algorithms
  - 10.1.1. A Simple Scheduling Problem
  - 10.1.2. Huffman Codes
  - 10.1.3. Approximate Bin Packing
- 10.2. Divide and Conquer
  - 10.2.1. Running Time of Divide and Conquer Algorithms
  - 10.2.2. Closest-Points Problem
  - 10.2.3. The Selection Problem
  - 10.2.4. Theoretical Improvements for Arithmetic Problems
- 10.3. Dynamic Programming
  - 10.3.1. Using a Table Instead of Recursion
  - 10.3.2. Ordering Matrix Multiplications
  - 10.3.3. Optimal Binary Search Tree
  - 10.3.4. All-Pairs Shortest Path
- 10.4. Randomized Algorithms
  - 10.4.1. Random Number Generators
  - 10.4.2. Skip Lists
  - 10.4.3. Primality Testing
- 10.5. Backtracking Algorithms
  - 10.5.1. The Turnpike Reconstruction Problem
  - 10.5.2. Games
  - Summary
  - Exercises
  - References
Chapter 11 Amortized Analysis
- 11.1. An Unrelated Puzzle
- 11.2. Binomial Queues
- 11.3. Skew Heaps
- 11.4. Fibonacci Heaps
  - 11.4.1. Cutting Nodes in Leftist Heaps
  - 11.4.2. Lazy Merging for Binomial Queues
  - 11.4.3. The Fibonacci Heap Operations
  - 11.4.4. Proof of the Time Bound
- 11.5. Splay Trees
  - Summary
  - Exercises
  - References
Chapter 12 Advanced Data Structures and Implementation
- 12.1. Top-Down Splay Trees
- 12.2. Red-Black Trees
  - 12.2.1. Bottom-Up Insertion
  - 12.2.2. Top-Down Red-Black Trees
  - 12.2.3. Top-Down Deletion
- 12.3. Deterministic Skip Lists
- 12.4. AA-Trees
- 12.5. Treaps
- 12.6. k-d Trees
- 12.7. Pairing Heaps
  - Summary
  - Exercises
  - References
Appendix A Some Library Routines ➖
- A.1. Classes in Package java.lang ➖
  - A.1.1. Character ➖
  - A.1.2. Integer ➖
  - A.1.3. Object ➖
  - A.1.4. String ➖
  - A.1.5. StringBuffer ➖
  - A.1.6. System ➖
  - A.1.7. Throwable ➖
- A.2. Classes in Package java.io ➖
  - A.2.1. BufferedReader ➖
  - A.2.2. BufferedWriter ➖
  - A.2.3. File ➖
  - A.2.4. FileReader ➖
  - A.2.5. FileWriter ➖
  - A.2.6. InputStreamReader ➖
  - A.2.7. PrintWriter ➖
  - A.2.8. PushbackReader ➖
- A.3. Classes in Package java.util ➖
  - A.3.1. Random ➖
  - A.3.2. StringTokenizer ➖
Appendix B The Collections Library ➖
- B.1. Introduction ➖
- B.2. Basic Classes ➖
  - B.2.1. Collection ➖
  - B.2.2. Iterator ➖
  - B.2.3. Comparable ➖
  - B.2.4. Comparator ➖
- B.3. Lists ➖
  - B.3.1. ArrayList vs. LinkedList ➖
  - B.3.2. Stacks and Queues ➖
  - B.3.3. ListIterator ➖
- B.4. Sets ➖
- B.5. Maps ➖
  - B.5.1. put, get, remove, and contains ➖
  - B.5.2. Getting a Collection from the Map ➖
  - B.5.3. Map.Entry Pairs ➖
- B.6. Example: Generating a Concordance ➖
  - B.6.1. Collections API Version ➖
  - B.6.2. Version Using Package DataStructures ➖
- B.7. Example: Shortest-Path Calculation ➖
  - B.7.1. Collections API Implementation ➖
  - B.7.2. Version Using Package DataStructures ➖
- B.8. Priority Queues ➖
  - Summary ➖
Index

Raw

Data Structures & Algorithm Analysis in Java (2nd Edition).md

Data Structures & Algorithm Analysis in Java (2nd Edition)

Information

Author: Mark Allen Weiss
Publisher: Pearson Addison-Wesley, 2007
ISBN-10: 0-321-37013-9 (0321370139)
ISBN-13: 978-0-321-37013-6 (9780321370136)

Data Structures & Algorithm Analysis in Java (3rd Edition)

Information

Author: Mark Allen Weiss
Publisher: Pearson Education, 2012
ISBN-10: 0-13-257627-9 (0132576279)
ISBN-13: 978-0-13-257627-7 (9780132576277)

Links

Publisher Link:
- https://www.pearson.com/us/higher-education/program/Weiss-Data-Structures-and-Algorithm-Analysis-in-Java-3rd-Edition/PGM324443.html
Amazon Link:
- https://amzn.com/0132576279
Google Books Link:
- https://books.google.com.hk/books?id=yCMrvgAACAAJ

Chapter 1 Introduction
- 1.1. What's the Book About?
- 1.2. Mathematics Review
  - 1.2.1. Exponents
  - 1.2.2. Logarithms
  - 1.2.3. Series
  - 1.2.4. Modular Arithmetic
  - 1.2.5. The P Word
- 1.3. A Brief Introduction to Recursion
- 1.4. Implementing Generic Components Pre Java 5
  - 1.4.1. Using Object for Genericity
  - 1.4.2. Wrappers for Primitive Types
  - 1.4.3. Using Interface Types for Genericity
  - 1.4.4. Compatibility of Array Types
- 1.5. Implementing Generic Components Using Java 5 Generics
  - 1.5.1. Simple Generic Classes and Interfaces
  - 1.5.2. Autoboxing/Unboxing
  - 1.5.3. The Diamond Operator
  - 1.5.4. Wildcards with Bounds
  - 1.5.5. Generic Static Methods
  - 1.5.6. Type Bounds
  - 1.5.7. Type Erasure
  - 1.5.8. Restrictions on Generics
- 1.6. Function Objects
  - Summary
  - Exercises
  - References
Chapter 2 Algorithm Analysis
- 2.1. Mathematical Background
- 2.2. Model
- 2.3. What to Analyze
- 2.4. Running Time Calculations
  - 2.4.1. A Simple Example
  - 2.4.2. General Rules
  - 2.4.3. Solutions for the Maximum Subsequence Sum Problem
  - 2.4.4. Logarithms in the Running Time
  - 2.4.5. A Grain of Salt
  - Summary
  - Exercises
  - References
Chapter 3 Lists, Stacks, and Queues
- 3.1. Abstract Data Types (ADTs)
- 3.2. The List ADT
  - 3.2.1. Simple Array Implementation of Lists
  - 3.2.2. Simple Linked Lists ✖️
- 3.3. Lists in the Java Collections API
  - 3.3.1. Collection Interface
  - 3.3.2. Iterators
  - 3.3.3. The List Interface, ArrayList, and LinkedList
  - 3.3.4. Example: Using remove on a LinkedList
  - 3.3.5. ListIterators
- 3.4. Implementation of ArrayList
  - 3.4.1. The Basic Class
  - 3.4.2. The Iterator and Java Nested and Inner Classes
- 3.5. Implementation of LinkedList
- 3.6. The Stack ADT
  - 3.6.1. Stack Model
  - 3.6.2. Implementation of Stacks
  - 3.6.3. Applications
- 3.7. The Queue ADT
  - 3.7.1. Queue Model
  - 3.7.2. Array Implementation of Queues
  - 3.7.3. Applications of Queues
  - Summary
  - Exercises
Chapter 4 Trees
- 4.1. Preliminaries
  - 4.1.1. Implementation of Trees
  - 4.1.2. Tree Traversals with an Application
- 4.2. Binary Trees
  - 4.2.1. Implementation
  - 4.2.2. An Example: Expression Trees
- 4.3. The Search Tree ADT --- Binary Search Trees
  - 4.3.1. contains ✖️
  - 4.3.2. findMin and findMax
  - 4.3.3. insert
  - 4.3.4. remove
  - 4.3.5. Average-Case Analysis
- 4.4. AVL Trees
  - 4.4.1. Single Rotation
  - 4.4.2. Double Rotation
- 4.5. Splay Trees
  - 4.5.1. A Simple Idea (That Does Not Work)
  - 4.5.2. Splaying
- 4.6. Tree Traversals (Revisited)
- 4.7. B-Trees
- 4.8. Sets and Maps in the Standard Library
  - 4.8.1. Sets
  - 4.8.2. Maps
  - 4.8.3. Implementation of TreeSet and TreeMap
  - 4.8.4. An Example That Uses Several Maps
  - Summary
  - Exercises
  - References
Chapter 5 Hashing
- 5.1. General Idea
- 5.2. Hash Function
- 5.3. Separate Chaining
- 5.4. Hash Tables Without Linked Lists ✖️
  - 5.4.1. Linear Probing
  - 5.4.2. Quadratic Probing
  - 5.4.3. Double Hashing
- 5.5. Rehashing
- 5.6. Hash Tables in the Standard Library
- 5.7. Hash Tables with Worst-Case O(1) Access
  - 5.7.1 Perfect Hashing
  - 5.7.2 Cuckoo Hashing
  - 5.7.3 Hopscotch Hashing
- 5.8 Universal Hashing
- 5.9 Extendible Hashing
  - Summary
  - Exercises
  - References
Chapter 6 Priority Queues (Heaps)
- 6.1. Model
- 6.2. Simple Implementations
- 6.3. Binary Heap
  - 6.3.1. Structure Property
  - 6.3.2. Heap-Order Property
  - 6.3.3. Basic Heap Operations
  - 6.3.4. Other Heap Operations
- 6.4. Applications of Priority Queues
  - 6.4.1. The Selection Problem
  - 6.4.2. Event Simulation
- 6.5. d-Heaps
- 6.6. Leftist Heaps
  - 6.6.1. Leftist Heap Property
  - 6.6.2. Leftist Heap Operations
- 6.7. Skew Heaps
- 6.8. Binomial Queues
  - 6.8.1. Binomial Queue Structure
  - 6.8.2. Binomial Queue Operations
  - 6.8.3. Implementation of Binomial Queues
- 6.9. Priority Queues in the Standard Library ➕
  - Summary
  - Exercises
  - References
Chapter 7 Sorting
- 7.1. Preliminaries
- 7.2. Insertion Sort
  - 7.2.1. The Algorithm
  - 7.2.2. Analysis of Insertion Sort
- 7.3. A Lower Bound for Simple Sorting Algorithms
- 7.4. Shellsort
  - 7.4.1. Worst-Case Analysis of Shellsort
- 7.5. Heapsort
  - 7.5.1. Analysis of Heapsort
- 7.6. Mergesort
  - 7.6.1. Analysis of Mergesort
- 7.7. Quicksort
  - 7.7.1. Picking the Pivot
  - 7.7.2. Partitioning Strategy
  - 7.7.3. Small Arrays
  - 7.7.4. Actual Quicksort Routines
  - 7.7.5. Analysis of Quicksort
  - 7.7.6. A Linear-Expected-Time Algorithm for Selection
- 7.8. A General Lower Bound for Sorting
  - 7.8.1. Decision Trees
- 7.9 Decision-Tree Lower Bounds for Selection Problems ➕
- 7.10 Adversary Lower Bounds ➕
- 7.11 Linear-Time Sorts: Bucket Sort and Radix Sort ✖️
- 7.12 External Sorting
  - 7.12.1. Why We Need New Algorithms
  - 7.12.2. Model for External Sorting
  - 7.12.3. The Simple Algorithm
  - 7.12.4. Multiway Merge
  - 7.12.5. Polyphase Merge
  - 7.12.6. Replacement Selection
  - Summary
  - Exercises
  - References
Chapter 8 The Disjoint Set Class ✖️
- 8.1. Equivalence Relations
- 8.2. The Dynamic Equivalence Problem
- 8.3. Basic Data Structure
- 8.4. Smart Union Algorithms
- 8.5. Path Compression
- 8.6. Worst Case for Union-by-Rank and Path Compression
  - 8.6.1. Slowly Growing Functions
  - 8.6.2. An Analysis By Recursive Decomposition
  - 8.6.3. An O(M log^* N) Bound
  - 8.6.4. An O(M α(M, N)) Bound
- 8.7. An Application
  - Summary
  - Exercises
  - References
Chapter 9 Graph Algorithms
- 9.1. Definitions
  - 9.1.1. Representation of Graphs
- 9.2. Topological Sort
- 9.3. Shortest-Path Algorithms
  - 9.3.1. Unweighted Shortest Paths
  - 9.3.2. Dijkstra's Algorithm
  - 9.3.3. Graphs with Negative Edge Costs
  - 9.3.4. Acyclic Graphs
  - 9.3.5. All-Pairs Shortest Path
  - 9.3.6. Shortest Path Example ➕
- 9.4. Network Flow Problems
  - 9.4.1. A Simple Maximum-Flow Algorithm
- 9.5. Minimum Spanning Tree
  - 9.5.1. Prim's Algorithm
  - 9.5.2. Kruskal's Algorithm
- 9.6. Applications of Depth-First Search
  - 9.6.1. Undirected Graphs
  - 9.6.2. Biconnectivity
  - 9.6.3. Euler Circuits
  - 9.6.4. Directed Graphs
  - 9.6.5. Finding Strong Components
- 9.7. Introduction to NP-Completeness
  - 9.7.1. Easy vs. Hard
  - 9.7.2. The Class NP
  - 9.7.3. NP-Complete Problems
  - Summary
  - Exercises
  - References
Chapter 10 Algorithm Design Techniques
- 10.1. Greedy Algorithms
  - 10.1.1. A Simple Scheduling Problem
  - 10.1.2. Huffman Codes
  - 10.1.3. Approximate Bin Packing
- 10.2. Divide and Conquer
  - 10.2.1. Running Time of Divide and Conquer Algorithms
  - 10.2.2. Closest-Points Problem
  - 10.2.3. The Selection Problem
  - 10.2.4. Theoretical Improvements for Arithmetic Problems
- 10.3. Dynamic Programming
  - 10.3.1. Using a Table Instead of Recursion
  - 10.3.2. Ordering Matrix Multiplications
  - 10.3.3. Optimal Binary Search Tree
  - 10.3.4. All-Pairs Shortest Path
- 10.4. Randomized Algorithms
  - 10.4.1. Random Number Generators
  - 10.4.2. Skip Lists
  - 10.4.3. Primality Testing
- 10.5. Backtracking Algorithms
  - 10.5.1. The Turnpike Reconstruction Problem
  - 10.5.2. Games
  - Summary
  - Exercises
  - References
Chapter 11 Amortized Analysis
- 11.1. An Unrelated Puzzle
- 11.2. Binomial Queues
- 11.3. Skew Heaps
- 11.4. Fibonacci Heaps
  - 11.4.1. Cutting Nodes in Leftist Heaps
  - 11.4.2. Lazy Merging for Binomial Queues
  - 11.4.3. The Fibonacci Heap Operations
  - 11.4.4. Proof of the Time Bound
- 11.5. Splay Trees
  - Summary
  - Exercises
  - References
Chapter 12 Advanced Data Structures and Implementation
- 12.1. Top-Down Splay Trees
- 12.2. Red-Black Trees
  - 12.2.1. Bottom-Up Insertion
  - 12.2.2. Top-Down Red-Black Trees
  - 12.2.3. Top-Down Deletion
- 12.3. Treaps
- 12.4 Suffix Arrays and Suffix Trees ➕
  - 12.4.1. Suffix Arrays ➕
  - 12.4.2. Suffix Trees ➕
  - 12.4.3. Linear-Time Construction of Suffix Arrays and Suffix Trees ➕
- 12.5. k-d Trees
- 12.6. Pairing Heaps
  - Summary
  - Exercises
  - References
Index

asukakenji/Data Structures & Algorithm Analysis in Java (1st Edition).md

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