Course Information


Time	3:00-4:30 TR 3:00-3:50 F
Location	VZN 297 (TR) and VZN 151 (F)

Instructor	Chuck Cusack
Email	cusack@hope.edu
Office	VWF 233
Phone	395-7271
Office Hours	by appointment


Textbooks	(IDAA) Introduction to the Design and Analysis of Algorithms, 3rd edition, Anany Levitin, Perason, 2012. (AIDMA) An Active Introduction to Discrete Mathematics and Algorithms, Version 2.5, Charles Cusack and David Santos, 2015. (PDF)

Description	An introduction to the design and analysis of algorithms along with some of the discrete mathematical structures that are fundamental to the field of Computer Science. This course builds on the data structures topics from CSCI235 by exploring efficient ways of using them to solve problems. Algorithm analysis topics include best, worst, and average case analysis of iterative and recursive algorithms; asymptotic notation; and solving recurrence relations. Algorithm design techniques include brute force, greedy, divide-and-conquer, transform-and-conquer, dynamic programming, and space/time tradeoff. Discrete structures topics include propositional logic, proof techniques (especially induction), sets, matrices, sequences and summations, and basic combinatorics.

Topics	Foundational Discrete Structures Propositional Logic, Equivalences, Truth Tables Sets Sequences and Summations Matrices Basic Counting Permutations/Combinations Binomial Coefficients and Identities, including the Binomial Theorem Pigeonhole Principle Proof Techniques Direct, Contraposition, Contradiction Proof by Induction Basic Algorithm Analysis Big-0, Omega, and Theta Notation Basic Algorithm Analysis (best/average/worst, time/space, wall-clock/CPU/operations) Complexity Classes Recursive Definitions/Recurrence Relations Solving Recurrence Relations Analyzing Recursive Algorithms/Master Theorem P/NP/NP-Complete Algorithm Design Techniques Brute Force Greedy Divide-and-conquer Decrease-and-Conquer Transform and Conquer Dynamic Programming Space/Time Tradeoff Backtracking Branch-and-bound