CS 583 Fall 2009

Analysis of Algorithms (Graduate Course)

Lecture Time: Tuesday 7:20 pm - 10:00 pm
Location: Enterprise Hall 276
Course webpage: http://www.cs.gmu.edu/~lifei/teaching/cs583_fall09/
Credit: 3

Instructor: Fei Li, Room 5326, Engineering Building, email: lifei@cs.gmu.edu
Office hours: Thusday 4:30pm - 6:30pm
TA: Yanyan Lv, ylu4@gmu.edu
Office hours:
Room 4456, Wednesday 5:00pm - 7:00pm


08/30/09: Lecture notes will be posted on this website after each class.

Course Overview:

In this course, a thorough examination of several well-known techniques that are used for the design and analysis of algorithms will be covered. Topics to be covered include theoretical measures of algorithm complexity, sorting and selection algorithms, greedy algorithms, divide and conquer techniques, dynamic programming, graph algorithms, search strategies, and an introduction to the theory of NP-completeness. Additional topics may be covered if time permits. Students are expected to have taken prior undergraduate courses in data structures, as well as calculus and discrete mathematics.


CS 310 and CS 330 Calculus (MATH 113, 114, 213) and MATH 125. Please contact with the instructor if you are not sure.


Introduction to Algorithms by T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, The McGraw-Hill Companies, 2nd Edition (2001) , or 3rd Edition (2009)

Recommended Reference Books:

Algorithm Design by Jon Kleinberg and Eva Tardos, Pearson Education, Inc. (2006). (You can find the sample chapters on the webpage.)

Combinatorial Optimization: Algorithms and Complexity by C. H. Papadimitriou and K. Steiglitz, Englewood Cliffs, Prentice Hall, c1982, Reprinted by Dover Books, 1998

Course Materials (Tentative):
Lectures Dates Topics Lecture Notes Scopes Notes
1 September 1  


Appendix, CLRS 2, CLRS 3

2 September 8  



Assignment 1 released
3 September 15



CLRS 5, 11  
4 September 22  


CLRS 6, 7

Assignment 2 released

Assignment 1 due

5 September 29  


CLRS 8, 9


6 October 6  


CLRS 12, Review

Assignment 2 due
  October 13  



Cancelled due to Columbus Day

7 October 20       Midterm exam (7:30pm - 10:00pm)
8 October 27     CLRS 15, 16

Assignment 3 released

9 November 3     CLRS 17, 19  
10 November 10




Assignment 4 released

Assignment 3 due

11 November 17





12 November 24     CLRS 24, 25

Assignment 5 released

Assignment 4 due

13 December 1  



14 December 8



CLRS 34, Review

Assignment 5 due
15 December 15      

Final exam (7:30pm - 10:00pm)


Tentative Grading:

Midterm Exam (30%)

Final Exam (30%)

Assignments (40%)

Topics Covered:

Function growth: O, theta, omega notation
Recurrence relations
Probabilistic analysis; randomized algorithms
Amortized analysis
Dynamic programming
Greedy algorithms
CLRS 16.1-3
Sorting heapsort, quicksort, mergesort
CLRS 2, 6, 7
Selection/order statistics
Data structures balanced binary search trees
CLRS 12, 13
Hash tables
Heaps / priority queues
CLRS 6.5, 20
Graph algorithms: BFS/DFS
Minimum spanning tree
Shortest paths
CLRS 24, 25
Maximum flow
CLRS 26.1-3
Time Complexity, NP-Complete

Hand in hard copies of assignments in class. Please note that all coursework is to be done independently. Plagiarizing the homework will be penalized by maximum negative credit and cheating on the exam will earn you an F in the course. See the GMU Honor Code System and Policies at http://www.gmu.edu/catalog/acadpol.html and http://www.cs.gmu.edu/honor-code.html. You are encouraged to discuss the material BEFORE you do the assignment. As a part of the interaction you can discuss a meaning of the question or possible ways of approaching the solution. The homework should be written strictly by yourself. In case your solution is based on the important idea of someone else please acknowledge that in your solution, to avoid any accusations.
Academic Honesty:

The integrity of the University community is affected by the individual choices made by each of us. GMU has an Honor Code with clear guidelines regarding academic integrity. Three fundamental and rather simple principles to follow at all times are that: (1) all work submitted be your own; (2) when using the work or ideas of others, including fellow students, give full credit through accurate citations; and (3) if you are uncertain about the ground rules on a particular assignment, ask for clarification. No grade is important enough to justify academic misconduct.

Plagiarism means using the exact words, opinions, or factual information from another person without giving the person credit. Writers give credit through accepted documentation styles, such as parenthetical citation, footnotes, or endnotes. Paraphrased material must also be cited, using MLA or APA format. A simple listing of books or articles is not sufficient. Plagiarism is the equivalent of intellectual robbery and cannot be tolerated in the academic setting. If you have any doubts about what constitutes plagiarism, please see me.

Disability Statement:

If you have a learning or physical difference that may affect your academic work, you will need to furnish appropriate documentation to the Disability Resource Center. If you qualify for accommodation, the DRC staff will give you a form detailing appropriate accommodations for your instructor.

In addition to providing your professors with the appropriate form, please take the initiative to discuss accommodation with them at the beginning of the semester and as needed during the term. Because of the range of learning differences, faculty members need to learn from you the most effective ways to assist you. If you have contacted the Disability Resource Center and are waiting to hear from a counselor, please tell me.