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.
Prerequisites:
CS 310 and CS 330 Calculus (MATH 113,
114, 213) and MATH 125 Familiarity with a high-level programming language
Required Textbook:
Jon Kleinberg and Eva Tardos: Algorithm Design
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 .
Grading:
Course Outcomes: Academic Integrity:
Quizes 20%
Homeworks 30%
Midterm 25%
Final 25%
Students will gain an understanding of classical
problems in Computer Science and practical knowledge and understadning
of commonly used algorithm design and analysis strategies.
They will gain an ability to analyze the computability of a problem
and design and analyze new algorithms to solve a computational
problem often encountered in practical applications.
The students will gain ability to reason algorithmically.
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.