CS
583 Spring 2015
Analysis of Algorithms I
Lecture time: Tuesday 7:20 pm  10:00 pm
Location: Planetary Hall 206
Course webpage: http://www.cs.gmu.edu/~lifei/teaching/cs583spring15
Credit: 3
Instructor: Fei Li, Room 5326, Engineering Building, email: lifei@cs.gmu.edu
Office hours: Tuesday
1:00pm – 3:00pm
Teaching assistant: Indranil Banerjee, email: ibanerje@masonlive.gmu.edu
Office hours: Monday 2:00pm – 4:00pm
News:

January 20:
Assignment 1 is released. The due date is January 27.
Course
overview:
In this course, a thorough
examination of several wellknown 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
NPcompleteness. 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.
Prerequisites:
CS 310 and CS 330 Calculus (MATH 113,
114, 213) and MATH 125. Please contact with the instructor if
you are not sure.
Textbook:
Introduction
to Algorithms by T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C.
Stein, 3rd Edition (2009)
Course
materials:
Lectures 
Dates 
Topics 
Lecture
notes 
Scopes 
Assignments 
Note 
1 
January 20 
Introduction 
Chapters 1, 2 
Assignment 1: page 11, Exercise 1.14, page 22, Exercise
2.13, page 29, Exercise 2.23, page 41, Problem 23 

2 
January 27 


Appendix A Chapters 3, 4 

Assignment 1 is due 
3 
February 2 


Appendix C Chapter 5 


4 
February 9 


Chapters 6, 7 


5 
February 16 


Chapters 8, 9 


6 
February 23 


Appendix B Chapters 10, 11, 22 


7 
March 3 


Chapters 12, 13, 14 


Spring break 
March 10 





8 Midterm exam 
March 17 


Chapter 15 


9 
March 24 


Chapter 16 


10 
March 31 


Chapter 17 


11 
April 7 


Chapters 18, 19, 20 


12 
April 7 


Chapters 21, 23 


13 
April 7 


Chapters 24, 25 


14 
April 28 


Chapter 26 


15 Final exam 
May 12 (7:30pm – 10:15pm) 





Topics:
In this course, we will consider the algorithm design
and analysis techniques of various problems coming from the following
areas:
Function growth: O, theta, omega notation (CLRS 3)
Recurrence relations (CLRS 4)
Probabilistic analysis; randomized algorithms (CLRS 5)
Amortized analysis (CLRS 17)
Dynamic programming (CLRS 15)
Greedy algorithms (CLRS 16.13)
Sorting: heapsort, quicksort, mergesort (CLRS 2, 6, 7)
Noncomparisonbased (CLRS 8)
Selection/order statistics (CLRS 9)
Data structures balanced binary search trees (CLRS 12,
13)
Graph algorithms: BFS/DFS (CLRS 22)
Minimum spanning tree (CLRS 23)
Shortest paths (CLRS 24, 25)
Maximum flow (CLRS 26.13)
Time complexity, NPComplete (CLRS 34)
Course
outcomes:
An understanding of classical problems in Computer
Science
An understanding of classical algorithm design and
analysis strategies
An ability to analyze the computability of a problem
Be able to design and analyze new algorithms to solve a
computational problem
An ability to reason algorithmically
Grading
policy:
Midterm exam (30%)
Final exam (40%)
Assignments and quizzes (30%)
[100; 95] : A+; (95; 90] : A;
(90; 85] : A; (85; 80] : B+; (80; 75] : B; (75; 70] : B; (70; 65] : C+; (65;
60] : C; (60; 0] : F
No makeup exams for missed tests.
No late assignments graded.
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.