CS
583 Fall 2016
Analysis of Algorithms I
Lecture time: Tuesday 7:20 pm10:00 pm
Location: Art and Design Building L008
Course webpage: http://www.cs.gmu.edu/~lifei/teaching/cs583fall16
Credit: 3
Instructor: Fei Li, Room 5326, Engineering Building, email: lifei@cs.gmu.edu
Office hours: Wednesday 5:30pm7:30pm
Teaching assistant: TBD
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 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 
Topics 
Lecture notes 
Scopes 
Assignments 
Note 
1 
Introduction 
Chapters
1.1 



2 
Chapter
2.2 Chapter
3.1, 3.2 
Assignment
1: Page 39, Exercise 2.33, Page 62, Problem 34(a)(g) 


3 
Divide
and conquer 
Chapters
4 

Assignment 1 due 

4 

Probabilistic
analysis and randomized algorithms 
Appendix
C Chapter
5 


5 


Assignment
2: Page 117, Exercise 5.13, Page 122, Exercises 5.24, 5.25 


6 

Chapters
6, 7, 8 

Assignment
2 due 

7 


Appendix
B Chapters
9, 10, 11 


8 (Midterm
exam) 





9 

Chapter
15 
Assignment
3: Page 370, Exercise 15.13; Page 397, Exercise 15.45, Page 405, Problem
152 


10 

Interval
scheduling (pages 814) 
Chapter
16 

Assignment
3 due 
11 





12 

Chapter
17 



13 

Chapters
2225 



14 

Chapter
26 



15 Final
exam 




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)
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.