Design & Analysis of Algorithm

Catalog description

Design and analysis of algorithms for solving computational problems. Topics include asymptotic analysis of algorithm time and space complexity, comparison of sorting and searching algorithms, and algorithms for processing strings, trees, graphs, and networks. Algorithm design paradigms include divide-and-conquer, dynamic programming, greedy methods, backtracking, and branch-and-bound. The course also introduces computational complexity and NP-completeness, emphasizing the limits of efficient computation. These techniques form the algorithmic foundations for modern applications including artificial intelligence, machine learning, and large-scale data processing. Coursework includes problem solving, algorithm analysis, and student presentations. Prerequisites: CS 310 and MATH 227 and either MATH 314 or MATH 330 (all three must be completed); and CS 301 (may be taken concurrently). All prerequisites must have a grade of C- or better. Offered every semester.