Lecture Notes

1. Introduction and PRELIMINARIES
2. The Growth of Functions
3. Recurrences
4. Data Structures
5. Lists
6. Stacks and Queues
7. Graphs
8. Trees
9. Priority Queues
10. Divide and Conquer Technique
11. Transform and Conquer Technique
Heaps and Heap Sort
12. Bubble Sort
13. Other Sorting Algorithms
14. Space and Time Tradeoff
15. Decrease and Conquer Programming Technique
16. Topological Sort
17. Greedy Programming Technique
18. Fractional Knapsack
19. Huffman Encoding
20. Union of disjoint sets and finding the partition
21. Single Source Shortest Path
22. Minimum Spanning Trees
23. Dynamic Programming
24. Dynamic Programming -- Transitive closure and other Graph algorithms
25. Brute Force
26. Iterative Improvement
27. Backtracking and Branch and Bound
28. Limitations of Algorithm Power
29. P and NP
30. Cheat Sheet PS PDF