Analysis of Algorithm

	Introduction,   RAM model,     Worst-case complexity I Asymptotics		Note 1
	Asymptotics, Induction, Divide and conquer, Merge sort Recurrence, Recursion tree		Note 2
	Binary search, Powering, Matrix multiplication, Strassen's algorithm, Master theorem		Note 3
	Randomized algorithms, Quicksort and its analysis		Note 4
	Randomized Quicksort		Note 5
	Selection in linear time, and Lower bound on comparison sorts		Note 6
	Counting sort and Radix sort Hash tables and hash functions		Note 7.1 Note 7.2
	Universal hashing		Note 8
	Perfect hashing and Binary search trees		Note 9.1 Note 9.2
	Red-Black trees		Note 10
	Augmenting data structures Order statistics, Interval trees		Note 11
	Greedy algorithms Activity selection		Note 12
	Greedy: Huffman trees, Dynamic programming: Rod cutting		Note 13
	Dynamic programming: Longest common subsequence
	Midterm in class
	Dynamic programming: Optimal binary search tree; midterm problems		Note 14
	Amortized analysis		Note 15
	Graphs and Breadth-first search		Note 16
	Breadth-first search and its correctness		See Note 16
	Depth-first search and Topological sort		Note 17
	Strongly connected componentsMinimum spanning tree: the generic method		Note 18
	Minimum spanning trees: Kruskal and Prim		Note 19
	Single-source shortest path: Bellman-Ford and Dijkstra		Note 20
	All-pairs shortest paths		Note 21
	Maximum Flow: Ford-Fulkerson		Note 22
	Edmonds-Karp, and Maximum bipartite matching		Note 23
	NP-completeness		Note 24
	NP-completeness		Note 25