Bowdoin Algorithms Csci 231

Csci 231: The Design and Analysis of Algorithms

Fall 2008: Tue, Thu 2:30 - 3:55 in Searles 126

This course is an introduction to the design and analysis of algorithms, building on the concepts from Data Structures (csci 210).

It introduces a variety of fundamental problems like searching, sorting and selection, graphs and optimization.
It discusses a variery of solutions to these problems, while illustrating design techniques such as divide-and-conquer, dynamic programming, greedy approach.
It discusses methods for proving correctness and analysing the efficiency of these solutions.

It is a theoretical class, and involves no programming.

Prerequisites: Csci 210 and (Csci 189 or Math 200 or permission of instructor)

Instructor: Laura Toma
Office: 219 Searles Hall
Email: ltoma at bowdoin

Office hours: Tue, Wed, Thu 4-5pm (after class).

In addition to the official office hours, you can drop by for a quick question any time I am in the office. Or, just send me an email to setup a (different) time.

I often work late evenings and I may be in the office the evening before homework is due, but do not take it for granted and do not rely on it. When I work late, you are very welcome to drop by and ask questions or chat.

Class webpage: http://www.bowdoin.edu/~ltoma/teaching/cs231/fall08/. Note that this is a link from my personal website at Bowdoin. This site will contain all class-related material along the semester. The class does not have a Blackboard site.

Main Topics:

Mathematical foundation (growth of functions, summations, recurrences)
Sorting algorithms (insertion sort, mergesort, quicksort, heapsort, bucket sort, radix sort)
Searching and data structures (binary search trees, red-black trees, augmented search trees, skip lists)
Priority queues (binary heap)
Amortized Analysis (splay trees)
Paradigms (divide-and-conquer, greedy, dynamic programming)
Graph Algorithms (traversal, minimum spanning tree, shortest paths)

Textbook:

Cormen, Leiserson, Rivest and Stein, Introduction to Algorithms, 2nd Edition, McGraw Hill, New York, 1990. (bugs).

Other good reference books include:

Kleinberg and Tardos, Algorithms.
Skienna, The algorithm design manual.

Grading policy

Homework assignments (approx. 30%).
Two in-class exams (20% each) and a final exam (30%).

I find that 'class participation' has become too much of a cliche, so I am not including it in the list above. Have you seen a class where participation is not encouraged, and does not count? This class is not an exception.

Homework

Homework assignments will be made available online as the semester progresses. They will usualy be due one week after they are assigned, and solutions will be handed out the day the homework is due. Because of this no credit is given for homework received late. For special situations contact me in advance.

Homework policy:

Write your name on each sheet.
Write the solutions in the space provided.
Collaboration is allowed, even encouraged, provided that it helps you study better. Don't overdo it, and remember that exams are individual! Even if you collaborate with others, you must write up the solutions individually, and list the names of the collaborators.
Homework should be submitted at the beginning of class on the due date.
It is a good experience to try typing the solutions, at least to some problems, given that it will motivate you to be concise and clear. If it does not, I prefer handwriting.