|Time ||1:30-2:50pm Tuesday/Thursday|
|Office Hours ||2-3pm MW or by appointment|
The following two textbooks will be used:
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.
- 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)
- 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.
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.
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
This course builds on the data structures topics from CSCI235 by exploring efficient ways of using them to
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
Discrete structures topics
include propositional logic, proof techniques (especially induction), sets,
matrices, sequences and summations, and basic combinatorics.
- Propositional Logic, Equivalences, Truth Tables
- Sequences and Summations
- Basic Counting
- Binomial Coefficients and Identities, including the Binomial Theorem
- Pigeonhole Principle
- 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
Algorithm Design Techniques
- Brute Force
- Transform and Conquer
- Dynamic Programming
- Space/Time Tradeoff