Persistent Data Structures
Persistent structures preserve all historical versions. Learn to make arrays and trees persistent.
Lessons
1. Intro
Why persistence matters
2. Types of Persistence
Partial vs full vs confluent
3. The Path Copying Technique
Core method for trees
4. Sharing Unchanged Subtrees
Why it's efficient
5. Persistent Array
Version-controlled array
6. Persistent Array Implementation
Code structure
7. Query and Update Functions
Traversing versions
8. Persistent Segment Tree
Version history for ranges
9. Range Query on Version
Standard segment tree query
10. Problem - Kth Number in Range
Classic persistence application
11. Kth Number: The Idea
Difference between versions
12. Kth Number: Implementation
Walk two trees together
13. Kth Number: Building
Create versions incrementally
14. Problem - Count in Range
Count values in bounds
15. Count in Range Solution
Range query on two trees
16. The Fat Node Method
Alternative to path copying
17. Persistent Union-Find
Version-controlled components
18. Persistent UF Applications
When you need it
19. Persistent Treap
Balanced BST with history
20. Persistent Treap Operations
Split and merge
21. Problem - Version Queries
Query past states
22. Version Queries Solution
Persistent segment tree
23. Copy-on-Write Semantics
Delayed copying
24. Functional Data Structures
Immutability by default
25. Persistent Rope
Efficient string operations
26. Space Optimization
Reducing memory usage
27. Memory Analysis
How much space?
28. Full Persistence
Branching version history
29. Version Trees
Tracking version relationships
30. Application: Undo/Redo
Editor history
31. Application: Git-like VCS
Branching and merging
32. Application: Database Snapshots
Point-in-time queries
33. Implementation Tips
Practical advice
34. Common Bugs
Debugging persistent structures
35. Persistence vs Rollback
When to use what
36. Quiz: Persistent Data Structures
Test your understanding
37. Section Recap
What you learned