CS 583
Analysis of Algorithms

Time/Location: Thursday 4:30-7:10,   Arts and Design Building 2026
Instructor: Dr. Jana Kosecka
Office: 4444, Research II
email: kosecka@cs.gmu.edu
Course website http://cs.gmu.edu/~kosecka/cs583/
Teaching Assitant: Wang, Haoliang hwang17@gmu.edu

Course Scope: 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 and algorithms, as well as calculus and discrete mathematics. Programming skills are also a prerequisite.

CS 310 and CS 330 Calculus (MATH 113, 114, 213) and MATH 125 Familiarity with a high-level programming language

Required Textbook:
Cormen, Leiserson & Rivest, Introduction to Algorithms, McGraw Hill, 1990

Recommended Textbook:
S. Dasgupta, C.H.Papadimitriou and U.V. Vazirani: Algorithms

Course Requirements:
There will be a midterm examination, several practice homework assignments, one programming projects and a comprehensive final examination. All required assignments must be completed by the stated due date and time. Late coursework will not be accepted and make-up tests will not be given for missed examinations. Please note that all coursework is to be done independently- see the GMU Honor Code System and Policies at http://www.gmu.edu/catalog/acadpol.html .

Homeworks/Quizes 30%
Midterm 35%
Final/Project 35%

Academic Integrity:

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.

CS department Honor Code can be found here.

Tentative List of Topics:
Topic  Chapter(s) 
Growth of Functions  2
Summations and Recurrences  3,4
Counting and Probability  6
Sorting and Order Statistics  7 - 10
Red-Black Trees  14
Dynamic Programming  16
Greedy Algorithms  17
Graph Algorithms  23 - 26
NP-Completeness and Approximation Algorithms  36 - 37

Please Note: You are expected to be familiar with the material in Chapters 1, 11 - 13, 19.