Fundamental Algorithms, Fall 2004

MIDTERM INFORMATION


GENERAL:

	Basically, we cover every topic discussed in class,
	assigned in homework or reading, up till the last
	lecture before midterm.

	Emphasis will be given to the topics covered in homework.

	It is a closed book exam, but you are allowed to bring
	one 8"x11" sheet of notes (both sides), used in any way
	you like.
  
  	The recitation this Wednesday (Oct 27) will be used for
	Midterm Review.  Please bring your questions!


I have slightly updated the reading list (on webpage) associated with
the Lecture Notes to conform to the following midterm topics:

Lecture I: Introduction to Algorithmics

	Computational Models (especially comparison model)
	Information Theoretic Lower Bound
	Merging Problem
	Worst case and best case complexity
	Karatsuba Algorithm
	Asymptotic Notations (big-Oh, big-Omega, Theta, small-oh)

Lecture II: Recurrences

	Simple Series
	Basic properties of familiar functions
	Basic Summation
	Summation Techniques	
	Rote Method
	Real Induction
	Standard Form
	Master Recurrence and Theorem
	Transformation Methods (domain and range)

Lecture III: Balanced Search Trees

	Basic ADT's (dictionary, priority queues,
		merge and split of ordered sets)
	Rotation-based Algorithms
	Binary search trees
	AVL Trees
	(a,b)-trees
	You must know how to do hand-simulations for balanced trees
	Pre-emptive rebalancing and one-pass algorithms

	Topics you must know even though we only briefly touched on them:

		tree traversal (inorder, preorder, postorder) 

Lecture IV: Pure Graph Algorithms

	Basic concepts (paths, cycles, connectivity, components)
	Graph Representation and Size 
	BFS Algorithm
	Simple DFS Algorithm

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