The Design and Analysis of Algorithms

Computer Science 681
Fall 2002

Instructor: Éva Tardos

4126 Upson
Office Hours: M and W after class, or Thursday 11-12
                     or by appointment.

TA: Chaitanya Swamy

5136 Upson
Regular Office Hours: 11-12 on Tuesdays. He also also happy to answer email, and set up special appointments.

Office hours for the week of the final:

Monday 1-2: Eva

Tuesday 11-12: Swamy

Wednesday 10:30-11:30 Eva

Thursday 11-12 Swamy and 3-4 Eva

Friday 10-11 Eva

Time: MWF 2:30-3:20 pm.

Place: Upson 111

Handouts and Announcements


Click here for old announcements.

Handouts from the upcoming Algorithms book by Kleinberg and Tardos can be picked up from Esha Mollette in 4119 Upson. Here is a list of the handouts we had.


CS 681 is an introductory graduate-level course on algorithms. Although we will be covering a number of current research topics in the design and analysis of algorithms, the primary focus will be on principles in algorithm design that are conceptually clean and broadly applicable. Our goal is to make the course both accessible and useful for graduate students in any area that makes use of algorithms.

Some of the broad areas we will be considering are: basic graph algorithms and data structures from a current perspective; the use of randomization; intractable problems and the design of approximation algorithms; and fundamental techniques from combinatorial optimization. We will be looking at algorithms as they appear in a variety of settings; some of these may include communication networks, on-line algorithm, computational geometry, computational biology, and the design of error-correcting codes.



There is no specific course pre-requisite, though knowledge of some material at the level of an undergraduate algorithms course, such as CS 482 will be assumed at various times. In particular: elementary data structures and elementary algorithms, such as basic sorting and searching, basic graph terminology, and basic graph algorithms, such as graph search, asymptotic order of growth notation, and basic recurrence relations for analyzing algorithms. It will also be helpful to have seen basic definitions of probability (e.g. random variables and their expectations), as well as some very basic linear algebra.


Homework will be assigned every 1-2 weeks; it should be handed in in lecture, at the end of class, on the day it is due.

Late homeworks will not receive credit. (If a genuine emergency situation prevents you from handing in an assignment on time, come talk to me and we can work something out.)

You are expected to support the answers to the homework with proofs. Much of the homework will consist of questions asking you to design algorithms for various problems. A complete answer consists of a clear description of an algorithm (an English description is fine), followed by an analysis of its running time and a proof that it works correctly; you do not need to implement the algorithm. You should try to make your algorithms as efficient as possible.

You may discuss the homework problems with other members of the class, but you must write up the assignment separately and list the names of the people with whom you discussed the assignment.


There will be an in-class mid-term and a take-home final at the end of the semester. Unlike the homework assignments, these must be done completely on your own.


The homework will count for 50% of the grade, the mid-term for 20%, and the final for 30%.


The textbook is

Some other useful books are