How does Mapquest find the best route between two locations? How do computers help to decode the human genome? At the heart of these and other complex computer applications are nontrivial algorithms. While algorithms must be specialized to an application, there are some standard ways of approaching algorithmic problems that tend to be useful in many applications. Among other topics, we will explore graph algorithms, greedy algorithms, divide-and-conquer, dynamic programming, and network flow.

Are there any limits to what computers can do? Does the answer to this question depend on whether you use a PC or a Mac? Is C more powerful than PASCAL? This seminar explores these questions by investigating several models of computation, illustrating the power and limitations of each of these models, and relating them to computational problems and applications. Topics include finite state automata, pushdown automata, grammars, Turing machines, the Universal Turing Machine, and computability.

This course is a discussion and practicum for students currently acting as mentors in the Computer Science Megas and Gigas Educate (MaGE) peer mentoring program. Through discussion, we will draw connections between the peer mentor experience and existing research and philosophies of peer mentoring and computer science education, to develop effective practical strategies.

This course looks at the inner workings of a computer and computer systems. It is an introduction to computer architecture. Specific topics include assembly language programming, memory, and parallelism. This course is programming intensive.

Building large software systems introduces new challenges to software development. Appropriate design decisions early in the development of large software can make a major difference in developing software that is correct and maintainable. In this course, students will learn techniques and tools to help them address these problems and develop larger software projects, improving their skills in designing, writing, debugging, and testing software. Topics include design patterns, UML, designing for maintainability, software architecture, and designing concurrent and fault tolerant systems.

Using Java. Solving problems with computers is accomplished by writing programs that operate on data to produce a desired result. The way data is organized and presented to the program can significantly affect its efficiency and simplicity and can sometimes determine whether or not a program can be written to solve the problem at all. This course presents ways of organizing data into 'data structures' and analyzes how structuring the data can improve program performance.This course is programming intensive.

Using Java. Solving problems with computers is accomplished by writing programs that operate on data to produce a desired result. The way data is organized and presented to the program can significantly affect its efficiency and simplicity and can sometimes determine whether or not a program can be written to solve the problem at all. This course presents ways of organizing data into 'data structures' and analyzes how structuring the data can improve program performance.This course is programming intensive.