Algorithm Analysis

Catalog description

Algorithm analysis using formal and mathematical techniques and fundamental algorithm design strategies are studied. Topics include asymptotic analyses of complexity bounds using big-O, little-o, omega, and theta notations. The algorithmic strategies (brute-force, greedy, divide-and-conquer, recursive backtracking, dynamic programming, branch-and-bound, heuristics, and reduction) are covered. Also included are standard graph and tree algorithms. Additional topics include standard complexity classes, time-and-space tradeoffs in algorithms, and analyzing both recursive algorithms and non-recursive (iterative) algorithms.