CSC 380 - Course Syllabus


	CSC 380 – Design and Analysis of Algorithms

Course Syllabus – Fall 2020 ß Note this is old

Section	Section Day	Section Time	Section Location
CSC 380-002	MWF	1:00pm - 1:50pm	Synchronous Online via Zoom

Schedule (Link Removed)

INSTRUCTOR

Curry Guinn
E-mail: mailto:guinnc@uncw.edu?subject=CSC%20380
Office hours: Via Zoom on MTF 11:00am-12:00pm and by appointment
Phone: (910) 962-7937

COURSE DESCRIPTION

Prerequisites: CSC 133, CSC 231, MAT 161. Algorithm design paradigms such as divide and conquer, greedy, and dynamic programming; techniques for algorithm analysis, such as asymptotic notations and estimates, as well as time/space trade-offs. Topics may include sorting, searching, scheduling, string matching, graph algorithms, amortized analysis, and computational geometry.

TEXTBOOK

Purchase an Electronic Copy Here: https://www.vitalsource.com/publisher/products/introduction-to-the-design-and-analysis-of-anany-levitin-v9780133001365

STUDENT LEARNING OUTCOMES

The Student Learning Outcomes (SLOs) for CSC 380 are:

1 Learn, and demonstrate their knowledge of, algorithm design paradigms and the language of algorithm analysis;

2 Choose data representations and identify, design, and implement multiple algorithms, based upon design paradigms (such as, divide-and-conquer, greedy algorithms, graph algorithms, randomized algorithms or dynamic programming);

3 Analyze the algorithmic complexity of algorithms and employ mathematical, analytical, and asymptotic notation to describe their relative merits; and

4 Develop an understanding of NP-completeness.

GRADING

Homework Assignments

Unless a group project is explicitly assigned, all homework must be YOUR OWN INDIVIDUAL WORK.
Some assignments may carry more weight than others.

Course Grade
A modified 10-point scale will be used to compute your course grade. Pluses and minuses ( + ) will be assigned solely at the discretion of the instructor. Factors that affect this judgment are the distribution of grades, improvement during the semester, and attendance.

90 - 100 A-, A

80 - 89.5 B-, B, B+

70 - 79.5 C-, C, C+

60 - 69.5 D-, D, D+

Ignore any grade calculations or totals in the Canvas gradebook. The following weighting of grades will be used; this weighting is not reflected in the Canvas gradebook.

Quizzes 10%
Homework Assignments: 25%
Test 1: 15%
Test 2: 15%
Final Exam: 35%

· Late Policy
There are no makeups for Quizzes. Quizzes administered on Canvas will have a clearly defined due date and time and will be posted with a minimum of 48 hours notice.

There are no makeups for missed midterms or final exams. The schedule for midterms and the final exam is already posted. In the event of a change, an announcement will be made in class and via email.

Homeworks will be submitted online. To receive full credit, the online submission must be made by the time and date specified in Canvas. Late assignments will be automatically docked 10 points per day, with Saturday/Sunday counting as one day.

Academic Integrity

University Policy on academic integrity will be followed for this course. Cheating will be taken very seriously, resulting in severe penalties. The academic integrity policy for each class varies. Please follow the policies below:

Appropriate Collaboration

· Sharing class notes with another student.

· Discussing anything that was covered in class.

· Helping a fellow student locate a bug in their program, provided the following are true:

1. You never type or dictate code for the student. You may help the student resolve a particular issue. You may not solve large parts of the programming problem for him/her.

Inappropriate Collaboration

· Showing another student (who has not completed the assignment) your code or answers to a problem.

· Copying problem solutions or code from another student.

· Verbally providing other students with the solution to the program. (This would be along the lines of giving them the key to solving the problem when they need to think it through themselves.)

· Helping other students during a test or quiz.

· Doing another student's work.

Any of these constitutes cheating and will be reported to the academic integrity council.

Help Problem Solving from Instructors

You may ask for problem solving help from your instructor or TA. However, problem solving is a skill that can be developed only by practice. It is vital for you to learn how to successfully struggle through problems on your own. If you are genuinely stuck, we will be willing to help you as far as your code matches the techniques described in class. If you come up with an approach that is a complete departure from the way described in class, you are responsible for fixing any resulting problems.

Students with Disabilities

Students with diagnosed disabilities should contact the Office of Disability Services (962-7555). Please give me a copy of the letter you receive from Office of Disability Services detailing class accommodations you may need. If you require accommodation for test-taking, please make sure I have the referral letter no fewer than three days before the test.

Notification of Illness

Students who experience COVID-19 symptoms should immediately contact the Abrons Student Health Center at (910) 962-3280.

Attendance Policy

There is no set attendance policy for this class. However, about 30%-40% of the material in this course is presented only in class. It is not in the textbook.

Learning Strategies

You are expected to take an active role in your learning in this course. This includes regular attendance, paying attention in class, reading the textbook, and completing all course requirements. You are encouraged to study with your classmates outside of class.

Policies