CS61B 数据结构与算法

课程简介

关于本书

Contributors
DISCLAIMER

1. Introduction

1. Introduction
1.1 Your First Java Program
1.2 Java Workflow
1.3 Basic Java Features
1.4 Exercises

2. Defining and Using Classes

3. References, Recursion, and Lists

4. SLLists

5. DLLists

6. Arrays

7. Testing

8. ArrayList

9. Inheritance I: Interface and Implementation Inheritance

10. Inheritance II: Extends, Casting, Higher Order Functions

10. Inheritance II: Extends, Casting, Higher Order Functions
10.1 Implementation Inheritance: Extends
10.2 Encapsulation
10.3 Casting
10.4 Higher Order Functions in Java
10.5 Exercises

11. Inheritance III: Subtype Polymorphism, Comparators, Comparable

11. Inheritance III: Subtype Polymorphism, Comparators, Comparable
11.1 A Review of Dynamic Method Selection
11.2 Subtype Polymorphism vs Explicit Higher Order Functions
11.3 Comparables
11.4 Comparators
11.5 Chapter Summary
11.6 Exercises

12. Inheritance IV: Iterators, Object Methods

12. Inheritance IV: Iterators, Object Methods
12.1 Lists and Sets in Java
12.2 Exceptions
12.3 Iteration
12.4 Object Methods
12.5 Chapter Summary
12.6 Exercises

13. Asymptotics I

13. Asymptotics I
13.1 An Introduction to Asymptotic Analysis
13.2 Runtime Characterization
13.3 Checkpoint: An Exercise
13.4 Asymptotic Behavior
13.6 Simplified Analysis Process
13.7 Big-Theta
13.8 Big-O
13.9 Summary
13.10 Exercises

14. Disjoint Sets

14. Disjoint Sets
14.1 Introduction
14.2 Quick Find
14.3 Quick Union
14.4 Weighted Quick Union (WQU)
14.5 Weighted Quick Union with Path Compression
14.6 Exercises

15. Asymptotics II

15. Asymptotics II
15.1 For Loops
15.2 Recursion
15.3 Binary Search
15.4 Mergesort
15.5 Summary
15.6 Exercises

16. ADTs and BSTs

16. ADTs and BSTs
16.1 Abstract Data Types
16.2 Binary Search Trees
16.3 BST Definitions
16.4 BST Operations
16.5 BSTs as Sets and Maps
16.6 Summary
16.7 Exercises

17. B-Trees

17. B-Trees
17.1 BST Performance
17.2 Big O vs. Worst Case
17.3 B-Tree Operations
17.4 B-Tree Invariants
17.5 B-Tree Performance
17.6 Summary
17.7 Exercises

18. Red Black Trees

18. Red Black Trees
18.1 Rotating Trees
18.2 Creating LLRB Trees
18.3 Inserting LLRB Trees
18.4 Runtime Analysis
18.5 Summary
18.6 Exercises

19. Hashing I

19. Hashing I
19.1 Introduction to Hashing: Data Indexed Arrays
19.1.1 A first attempt: DataIndexedIntegerSet
19.1.2 A second attempt: DataIndexedWordSet
19.1.3 A third attempt: DataIndexedStringSet
19.2 Hash Code
19.3 "Valid" & "Good" Hashcodes
19.4 Handling Collisions: Linear Probing and External Chaining
19.5 Resizing & Hash Table Performance
19.6 Summary
19.7 Exercises

20. Hashing II

20. Hashing II
20.1 Hash Table Recap, Default Hash Function
20.2 Distribution By Other Hash Functions
20.3 Contains & Duplicate Items
20.4 Mutable vs. Immutable Types

21. Heaps and Priority Queues

21. Heaps and Priority Queues
21.1 Priority Queues
21.2 Heaps
21.3 PQ Implementation
21.4 Summary
21.5 Exercises

22. Tree Traversals and Graphs

22. Tree Traversals and Graphs
22.1 Tree Recap
22.2 Tree Traversals
22.3 Graphs
22.4 Graph Problems

23. Graph Traversals and Implementations

23. Graph Traversals and Implementations
23.1 BFS & DFS
23.2 Representing Graphs
23.3 Summary
23.4 Exercises

24. Shortest Paths

24. Shortest Paths
24.1 Introduction
24.2 Dijkstra's Algorithm
24.3 A* Algorithm
24.4 Summary
24.5 Exercises

25. Minimum Spanning Trees

25. Minimum Spanning Trees
25.1 MSTs and Cut Property
25.2 Prim's Algorithm
25.3 Kruskal's Algorithm
25.4 Chapter Summary
25.5 MST Exercises

26. Prefix Operations and Tries

26. Prefix Operations and Tries
26.1 Introduction to Tries
26.2 Trie Implementation
26.3 Trie String Operations
26.4 Summary
26.5 Exercises

27. Software Engineering I

27. Software Engineering I
27.1 Introduction to Software Engineering
27.2 Complexity
27.3 Strategic vs Tactical Programming
27.4 Real World Examples
27.5 Summary, Exercises

28. Reductions and Decomposition

28. Reductions and Decomposition
28.1 Topological Sorts and DAGs
28.2 Shortest Paths on DAGs
28.3 Longest Path
28.4 Reductions and Decomposition
28.5 Exercises

29. Basic Sorts

29. Basic Sorts
29.1 The Sorting Problem
29.2 Selection Sort & Heapsort
29.3 Mergesort
29.4 Insertion Sort
29.5 Summary
29.6 Exercises

30. Quicksort

30. Quicksort
30.1 Partitioning
30.2 Quicksort Algorithm
30.3 Quicksort Performance Caveats
30.4 Summary
30.5 Exercises

31. Software Engineering II

31. Software Engineering II
31.1 Complexity II
31.2 Sources of Complexity
31.3 Modular Design
31.4 Teamwork
31.5 Exerises

32. More Quick Sort, Sorting Summary

32. More Quick Sort, Sorting Summary
32.1 Quicksort Flavors vs. MergeSort
32.2 Quick Select
32.3 Stability, Adaptiveness, and Optimization
32.4 Summary
32.5 Exercises

33. Software Engineering III

33. Software Engineering III
33.1 Candy Crush, SnapChat, and Friends
33.2 The Ledger of Harms
33.3 Your Life
33.4 Summary
33.5 Exercises

34. Sorting and Algorithmic Bounds

34. Sorting and Algorithmic Bounds
34.1 Sorting Summary
34.2 Math Problems Out of Nowhere
34.3 Theoretical Bounds on Sorting
34.4 Summary
34.5 Exercises

35. Radix Sorts

35. Radix Sorts
35.1 Counting Sort
35.2 LSD Radix Sort
35.3 MSD Radix Sort
35.4 Summary
35.5 Exercises

36. Sorting and Data Structures Conclusion

36. Sorting and Data Structures Conclusion
36.1 Radix vs. Comparison Sorting
36.2 The Just-In-Time Compiler
36.3 Radix Sorting Integers
36.4 Summary
36.5 Exercises

37. Software Engineering IV

37. Software Engineering IV
37.1 The end is near

38. Compression and Complexity

38. Compression and Complexity
38.1 Introduction to Compression
38.2 Prefix-free Codes
38.3 Shannon-Fano Codes
38.4 Huffman Coding Conceptuals
38.5 Compression Theory
38.6 LZW Compression
38.7 Summary
38.8 Exercises

39. Compression, Complexity, P = NP

39. Compression, Complexity, P = NP
39.1 Models of Compression
39.2 Optimal Compression, Kolmogorov Complexity
39.3 Space/Time-Bounded Compression
39.4 P = NP
39.5 Exercises

JALEE // ASTRO

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CS61B 数据结构与算法

课程简介

关于本书

Contributors
DISCLAIMER

1. Introduction

1. Introduction
1.1 Your First Java Program
1.2 Java Workflow
1.3 Basic Java Features
1.4 Exercises

2. Defining and Using Classes

3. References, Recursion, and Lists

4. SLLists

5. DLLists

6. Arrays

7. Testing

8. ArrayList

9. Inheritance I: Interface and Implementation Inheritance

10. Inheritance II: Extends, Casting, Higher Order Functions

10. Inheritance II: Extends, Casting, Higher Order Functions
10.1 Implementation Inheritance: Extends
10.2 Encapsulation
10.3 Casting
10.4 Higher Order Functions in Java
10.5 Exercises

11. Inheritance III: Subtype Polymorphism, Comparators, Comparable

11. Inheritance III: Subtype Polymorphism, Comparators, Comparable
11.1 A Review of Dynamic Method Selection
11.2 Subtype Polymorphism vs Explicit Higher Order Functions
11.3 Comparables
11.4 Comparators
11.5 Chapter Summary
11.6 Exercises

12. Inheritance IV: Iterators, Object Methods

12. Inheritance IV: Iterators, Object Methods
12.1 Lists and Sets in Java
12.2 Exceptions
12.3 Iteration
12.4 Object Methods
12.5 Chapter Summary
12.6 Exercises

13. Asymptotics I

13. Asymptotics I
13.1 An Introduction to Asymptotic Analysis
13.2 Runtime Characterization
13.3 Checkpoint: An Exercise
13.4 Asymptotic Behavior
13.6 Simplified Analysis Process
13.7 Big-Theta
13.8 Big-O
13.9 Summary
13.10 Exercises

14. Disjoint Sets

14. Disjoint Sets
14.1 Introduction
14.2 Quick Find
14.3 Quick Union
14.4 Weighted Quick Union (WQU)
14.5 Weighted Quick Union with Path Compression
14.6 Exercises

15. Asymptotics II

15. Asymptotics II
15.1 For Loops
15.2 Recursion
15.3 Binary Search
15.4 Mergesort
15.5 Summary
15.6 Exercises

16. ADTs and BSTs

16. ADTs and BSTs
16.1 Abstract Data Types
16.2 Binary Search Trees
16.3 BST Definitions
16.4 BST Operations
16.5 BSTs as Sets and Maps
16.6 Summary
16.7 Exercises

17. B-Trees

17. B-Trees
17.1 BST Performance
17.2 Big O vs. Worst Case
17.3 B-Tree Operations
17.4 B-Tree Invariants
17.5 B-Tree Performance
17.6 Summary
17.7 Exercises

18. Red Black Trees

18. Red Black Trees
18.1 Rotating Trees
18.2 Creating LLRB Trees
18.3 Inserting LLRB Trees
18.4 Runtime Analysis
18.5 Summary
18.6 Exercises

19. Hashing I

19. Hashing I
19.1 Introduction to Hashing: Data Indexed Arrays
19.1.1 A first attempt: DataIndexedIntegerSet
19.1.2 A second attempt: DataIndexedWordSet
19.1.3 A third attempt: DataIndexedStringSet
19.2 Hash Code
19.3 "Valid" & "Good" Hashcodes
19.4 Handling Collisions: Linear Probing and External Chaining
19.5 Resizing & Hash Table Performance
19.6 Summary
19.7 Exercises

20. Hashing II

20. Hashing II
20.1 Hash Table Recap, Default Hash Function
20.2 Distribution By Other Hash Functions
20.3 Contains & Duplicate Items
20.4 Mutable vs. Immutable Types

21. Heaps and Priority Queues

21. Heaps and Priority Queues
21.1 Priority Queues
21.2 Heaps
21.3 PQ Implementation
21.4 Summary
21.5 Exercises

22. Tree Traversals and Graphs

22. Tree Traversals and Graphs
22.1 Tree Recap
22.2 Tree Traversals
22.3 Graphs
22.4 Graph Problems

23. Graph Traversals and Implementations

23. Graph Traversals and Implementations
23.1 BFS & DFS
23.2 Representing Graphs
23.3 Summary
23.4 Exercises

24. Shortest Paths

24. Shortest Paths
24.1 Introduction
24.2 Dijkstra's Algorithm
24.3 A* Algorithm
24.4 Summary
24.5 Exercises

25. Minimum Spanning Trees

25. Minimum Spanning Trees
25.1 MSTs and Cut Property
25.2 Prim's Algorithm
25.3 Kruskal's Algorithm
25.4 Chapter Summary
25.5 MST Exercises

26. Prefix Operations and Tries

26. Prefix Operations and Tries
26.1 Introduction to Tries
26.2 Trie Implementation
26.3 Trie String Operations
26.4 Summary
26.5 Exercises

27. Software Engineering I

27. Software Engineering I
27.1 Introduction to Software Engineering
27.2 Complexity
27.3 Strategic vs Tactical Programming
27.4 Real World Examples
27.5 Summary, Exercises

28. Reductions and Decomposition

28. Reductions and Decomposition
28.1 Topological Sorts and DAGs
28.2 Shortest Paths on DAGs
28.3 Longest Path
28.4 Reductions and Decomposition
28.5 Exercises

29. Basic Sorts

29. Basic Sorts
29.1 The Sorting Problem
29.2 Selection Sort & Heapsort
29.3 Mergesort
29.4 Insertion Sort
29.5 Summary
29.6 Exercises

30. Quicksort

30. Quicksort
30.1 Partitioning
30.2 Quicksort Algorithm
30.3 Quicksort Performance Caveats
30.4 Summary
30.5 Exercises

31. Software Engineering II

31. Software Engineering II
31.1 Complexity II
31.2 Sources of Complexity
31.3 Modular Design
31.4 Teamwork
31.5 Exerises

32. More Quick Sort, Sorting Summary

32. More Quick Sort, Sorting Summary
32.1 Quicksort Flavors vs. MergeSort
32.2 Quick Select
32.3 Stability, Adaptiveness, and Optimization
32.4 Summary
32.5 Exercises

33. Software Engineering III

33. Software Engineering III
33.1 Candy Crush, SnapChat, and Friends
33.2 The Ledger of Harms
33.3 Your Life
33.4 Summary
33.5 Exercises

34. Sorting and Algorithmic Bounds

34. Sorting and Algorithmic Bounds
34.1 Sorting Summary
34.2 Math Problems Out of Nowhere
34.3 Theoretical Bounds on Sorting
34.4 Summary
34.5 Exercises

35. Radix Sorts

35. Radix Sorts
35.1 Counting Sort
35.2 LSD Radix Sort
35.3 MSD Radix Sort
35.4 Summary
35.5 Exercises

36. Sorting and Data Structures Conclusion

36. Sorting and Data Structures Conclusion
36.1 Radix vs. Comparison Sorting
36.2 The Just-In-Time Compiler
36.3 Radix Sorting Integers
36.4 Summary
36.5 Exercises

37. Software Engineering IV

37. Software Engineering IV
37.1 The end is near

38. Compression and Complexity

38. Compression and Complexity
38.1 Introduction to Compression
38.2 Prefix-free Codes
38.3 Shannon-Fano Codes
38.4 Huffman Coding Conceptuals
38.5 Compression Theory
38.6 LZW Compression
38.7 Summary
38.8 Exercises

39. Compression, Complexity, P = NP

39. Compression, Complexity, P = NP
39.1 Models of Compression
39.2 Optimal Compression, Kolmogorov Complexity
39.3 Space/Time-Bounded Compression
39.4 P = NP
39.5 Exercises

CS61B

15. Asymptotics II

This chapter covers various asymptotic analysis examples, which provide useful insights on how to analyze the efficiency of algorithms.

← 14.6 Exercises 15.1 For Loops →

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