Algorithm Analysis
Examines formal concepts of algorithm efficiency including Big O, Theta, and NP theory. Algorithmic techniques studied include brute force, simulation, divide and conquer, dynamic programming, greedy algorithms, backtracking, branch and bound, and parallel algorithms. Time and space efficiency is analyzed from a practical and theoretical viewpoint throughout this course. Advanced searching and sorting techniques are covered. Classic algorithms and their relevance to real problems are examined. Typical data structures used as examples include hash tables, trees, and graphs. Parallel programming is explored. Prerequisites: CPSC 211, MATH 250
Credit Hours:
3
Course Number:
CPSC 320