CS 483 Fall 2012
Design and Analysis of Algorithms
Lecture
Time: Friday 10:30 am  1:10 pm
Location:
Robinson Hall B208
Course webpage:
http://www.cs.gmu.edu/~lifei/teaching/cs483_fall12
Credit:
3
Instructor:
Fei Li, Room 5326, Engineering
Building, email: lifei@cs.gmu.edu
Office hours: Monday
4:00pm  6:00pm
Teaching Assistant: TBD, Room TBD, Engineering Building, email:
Office hours: TBD
NEWS:
Course Overview:
In
this course, a thorough examination of several wellknown techniques that are
used for the design and analysis of efficient algorithms will be covered.
Topics to be covered include theoretical measures of algorithm complexity,
greedy algorithms, divide and conquer techniques, dynamic programming, graph
algorithms, search strategies, and an introduction to the theory of
NPcompleteness.
Prerequisites:
CS
310 and CS 330 Calculus (MATH 113, 114, 213) and MATH 125. Please contact with the instructor if
you are not sure.
Textbooks:
Algorithm
Design by Jon Kleinberg and Éva Tardos, Addison Wesley (2006).
Course Materials:
Lecture 
Date 
Topic 
Lecture
Notes 
Scope 
Assignments 
Note 
1 
August
31 
Introduction 




2 
September
7 





3 
September 14 





4 
September 21 





5 
September 28 





6 
October
5 





7 
October
12 





Midterm Exam 
October
19 





8 
October
26 





9 
October
5 





10 
November
2 





11 
November
9 





12 
November
16 





Thanksgiving
recess 
November
23 





13 
November
30 





14 
December
7 





Final exam 
December
14 10:30am
– 1:15pm 





Topics:
In this course, we will consider the algorithm design and alaysis techniques of various problems coming from the
following areas:
• Analysis of Algorithm Efficiency
(asymptotic notation, amortized analysis)
• Brute Force Techniques (sorting, search, traveling salesmen)
• Divide and Conquer (merge sort, quicksort, matrix multiplication, polynomial
multiplication)
• Graph decomposition and search (connected components, shortest path problem)
• Greedy Techniques (minimum spanning tree, Huffman trees)
• Dynamic Programming (edit distance,matrix chainmultiplication, knapsack, all pairs shortest paths)
• Linear Programming (network flows, matching, simplex, duality)
• Randomized Algorithms
Course
Outcomes:
1. An understanding of classical problems in Computer Science
2. An understanding of classical algorithm design and analysis strategies
3. An ability to analyze the computability of a problem
4. Be able to design and analyze new algorithms to solve a computational problem
5. An ability to reason algorithmically
Tentative
Grading:
Weekly assignments (45%)
Midterm Exam (20%)
Final Exam (35%)
Policies:
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/honorcode.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.