Lecture Notes

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