Algorithm Analysis and Design

Student Learning Outcomes, Goals, Objectives:

Students successfully completing this course will be able to:

• understand how recursion works;

• know how to design divide-and-conquer algorithms using three steps and apply to merge sort, quick sort, Strassen’s matrix multiplication;

• understand asymptotic notation, and analyze common algorithms using them;

• Apply graph algorithms, including graph traversal, shortest paths, minimum spanning trees, and graph search techniques.

• Understand the fundamentals of algorithmic game theory and analyze basic game-theoretic algorithms and solution concepts.

• use a greedy strategy to solve some problems such as minimum spanning tree and shortest path;

• apply dynamic programming to problems such as matrix chain product, longest common subsequence, and graph algorithms;

• understand NP-completeness and why it is important;

Course Grading Information:

Activity/Performance Measure	Percentage/Points
Quiz 1–12 (lowest two dropped)	100%

Grade | Point/Percentage Total

Percentage	Letter Grade
93–100%	A
90–92%	A-
87–89%	B+
83–86%	B
80–82%	B-
77–79%	C+
73–76%	C
70–72%	C-
67–69%	D+
63–66%	D
60–62%	D-
Below 60%	F

Attendance/Participation:

Attendance is encouraged but will not be counted toward the final course grade.

Course Materials Purchased by the Students:

No purchase is required.

The primary reference is:

Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. Introduction to Algorithms (4th Edition, MIT Press, 2022).

An electronic version is available through the UNCG Library. All lecture slides, notes, and supplementary course materials will be provided to students through Canvas, so no additional textbook purchase is required.