1. Lecture 1

2. Lecture 2

3. Lecture 3

4. Lecture 4

5. Lecture 5

6. Lecture 6

7. Lecture 7

8. Lecture 8 Priority Queues and Heaps.

9. Lecture 9. Initializing Heaps and Leftist Trees.

10. Lecture 10. Binary Search Trees.

11. Lecture 11. Indexed BST, applications (bin packing, linear lists)

12. Lecture 12. Applications of indexed BST (crossing distribution)

13. Lecture 13. Balanced Search Trees: AVL trees.

14. Balancing examples.

15. Lecture 14. Intro to Graphs.

16. Lecture 15. Graph Representation.

17. Lecture 16. Graph Searching.

18. Lecture 17. Algorithm Design Methods. Greedy Method examples.

19. Lecture 18. Dijkstra's shortest path algorithm.

20. Lecture 19. Graph algorithms using Greedy method (min-cost spanning tree with Kruskal and Prim. Topological sorting, bipartite cover)..

21. Lecture 20. Divide and conquer technique. Tiling a defective chessboard. Finding min and max.

22. Lecture 21. Divide and conquer sorting. Merge sort, quick sort.

23. Lecture 22. Divide and conquer examples. Selection, closest points.

24. Lecture 23. Dynamic Programming Intro.

25. Lecture 24. Dynamic Programming for the Knapsack problem, iterative solution for DP, trace back.

Last Modified: 5 December 2001

THIS PAGE MAINTAINED BY: John Barr, Ithaca College