Summer 2008

Instructor: Dr. John Youssefi

Course Hours: Tuesday,Thursday 6:30-9:30PM, SM 203

Office: St. Mary Room #205

Contact: (650) 508 - 3450 / jyoussefi@ndnu.edu

Office Hours: Tuesday, Thursday 5:30 - 6:30 pm or by appointment

Text: An Foundations of Algorithms Using C++ Pseudocode (Third Edition), by Richard Neapolitan and Kummars Naimipour, Jones and Bartlett Computer Science, ISBN: 0-7637-2387-8

DESCRIPTION:

Designing algorithms to address classical problems, including Searching, Sorting, Scheduling, Minimum Spanning Tree, Graph Coloring, 0-1 Knapsack, Traveling Salesperson Problem, and more
Methodologies of designing algorithms, including Divide-and-Conquer, Greedy approach, and Dynamic programming
Techniques to analyze and compare the complexity of algorithms

Course Objectives:

To acquire a broad base of technical and theoretical skills in the field of algorithmic complexity
To develop analytical skills in determining the best algorithm to solve a class of data processing problems.
Familiarity with algorithm implementation for soving various problems.
Understanding various classes of algorithms and the type of problems they provide solutions for.

Grades:

Programs&Homework . . . . . . . 50%

Midterm test . . . . . . . . . . . . . . 25%

Final test . . . . . . . . . . . . . . . . . 25%

93-100 A 90-93 A-

87-90 B+ 84-87 B

80-84 B- 77-80 C+

74-77 B 70-74 C-

67-70 D+ 64-67 D

60-64 D- 0 -60 F

I do not give make-up tests; for an excused absence I count the other grades proportionately higher. 10% off for each weekday on programs.

Complete academic integrity is expected, according to the Code of Student Conduct.

Incompletes will not be assigned except for documented compelling reasons, according to the university Grading Systems. Check the Academic Calandar for Add/Drop dates.

Tentative Scheduale:

Week 1 Review of Math Appendix A

Week 1 Algorithms: Efficiency, Analysis and Order Ch 1

Week 2 Recurrence Equations and Recursive Algorithms Appendix B

Week 2 Divide-and-Conquer Ch.2

Week 3 Dynamic Programming Ch 3

Week 3 Greedy Approach Ch 4

Week 4 Problem Solving, Review Ch 1-4

Week 4 Midterm

Week 5 Backtracking Ch 5

Week 5 Branch-and-Bound Ch 6

Week 6 Computational Complexity: Sorting Ch 7

Week 6 Computational Complexity: Searching Ch 8

Week 7 NP Ch 9

Week 7 Review

Week 8 Final