This course is about designing algorithms for computational problems, and how to think clearly about analyzing correctness and running time. The main goal of this course is to provide the intellectual tools needed for designing and analyzing your own algorithms for new problems you need to solve in the future. Algorithm design tools we will discuss include Dynamic Programming, Divide-and-Conquer, Data Structure design principles, Randomization, Network Flows, Linear Programming, and the Fast Fourier Transform. Some analytical tools we will discuss and use include Recurrences, Probabilistic Analysis, Amortized Analysis, and Potential Functions. We will also discuss a bit of Complexity Theory (which looks at the intrinsic difficulty of computational problems) as well as Cryptography and Algorithmic Game Theory.


Teaching Assistants:

Course Secretary:

ameliaw@cs.cmu.edu Wean 4114, x8-7897.


Tuesday/Thursday 12:00-1:20, Wean Hall 7500.


Everyone is expected to go to one of the recitation sections. Recitations are a chance to engage in more discussion than is usually possible in a large lecture, with a focus on the process of solving algorithmic problems. Recitations will often contain new material as well.


There are two bulletin boards for the course: academic.cs.15-451.discuss is for general discussion, and academic.cs.15-451 is for staff announcements. Please use them and read them frequently!


Important Dates:

The first quiz will be Tuesday February 19th. The midterm will be Tuesday March 4th. The second quiz will be Thursday April 10th. The Final Exam is on Cinco de May (May 5th) from 5:30 to 8:30pm. A detailed course schedule is available.


There will be a problem set every two weeks. These will alternate between ones that require written answers (homeworks 1, 3, 5, and 7) and ones that require an oral presentation (homeworks 2, 4, and 6). Here are guidelines for each type of assignment.

Written homeworks:


The course will closely follow Avrim Blum’s lecture notes, which will be handed out in class (or pick up from Amy Williams, the course secretary, in 4114 Wean).

The textbook for the course is Introduction to Algorithms (Second Edition) by Cormen, Leiserson, Rivest, and Stein (hereafter referred to as "CLRS"). If you have a (very) old version of CLRS, known as "CLR", you can use that too. While we will be providing lecture notes covering all the material in this course, we would like you to have a book to give you more detailed coverage (as well as an alternative perspective if you cannot understand what the instructor is saying!). Specific readings are listed on the course schedule. It is recommended that you skim the reading before lecture, with a more thorough read afterwards.

Other helpful material can be found in: Algorithm Design by J. Kleinberg and E. Tardos, Algorithms by S. Dasgupta, C.H. Papadimitriou, and U.V. Vazirani, Data Structures and Network Algorithms by R.E. Tarjan, Randomized Algorithms by Motwani and Raghavan, Programming Pearls by J. Bentley, Introduction to Algorithms: A Creative Approach by Manber, and the classic Abo-Hopcroft-Ullman book.