Course Information


Time	1:30-2:50pm Tuesday/Thursday 2:00-2:50pm Friday
Location	Graves 203

Instructor	Chuck Cusack
E-mail	cusack@hope.edu
Office	VWF 233
Phone	395-7271
Office Hours	2-3pm MW or by appointment


Textbook	The following two textbooks will be used: The Algorithm Design Manual, Second Edition (ADM), Steven Skiena, Springer, 2010. Introduction to Discrete Mathematics and Algorithms (IDMA), Charles Cusack and David Santos, 2013. (The bookstore has copies. You need a hard copy for use during class, but it is also available in PDF here) Note: Whenever the resources column on the schedule has an entry for ADM or IDMA, you are expected to read the given sections before class.

Important Links	Programming Challenges UVa Online Judge Submission Guidelines From the UVa site, but I think it applies to both. Of particular importance is the sample Java code. CSE 392 - Programming Challenges A webpage for a course based on the programming challenges. Linked mostly for the useful information he has about properly implementing solutions in Java so they work on the platforms—see the longest bullet item under the Course Documents heading).

Resources	Answers in the back of your book An Introduction to Discrete Mathematics and Algorithms has Exercise sections that contain problems with solutions given in the next section. Me See me during office hourse, before or after class, or make an appointment at another time. The Computer Science Help Center Check the signs in the lab and classroom for hours. The Help Center Assistante should be able to help you with the discrete mathematics topics. Depending on who is there, they may be able to help with some of the algorithms material.

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