This course introduces students to the practice of software development. Students learn the fundamentals of programming, algorithm development, and object-orientated design principles.

The laboratory course complements CS110 by using programming exercises to reinforce concepts and practices covered in CS110 lectures.

This course is a continuation of CS110/111. CS210 expands on object-oriented design practices, introduces simple data structures, and explores sorting and searching algorithms. Advanced programming techniques such as recursion and unit testing are also covered. Class lab time is used to reinforce concepts and practices covered in lectures.

This course provides the theoretical foundation of modern computer hardware and software. It provides that foundation in the form of mathematical tools and concepts geared toward computer science applications. Topics covered include: logic and set theory; functions and relations; simple algorithm analysis; and an introduction to graph theory.

This course introduces students to digital computer organization and programming at the assembly level. Students learn the connection between Boolean logic and hardware circuits, the operation of combinational and sequential circuitry comprising the hardware of a modern computer, and the interaction between the hardware and software processes.

• CS210 Computer Science II

A more complete and detailed study of data structures. Lists, queues, stacks and trees are reviewed, but with more emphasis on the mathematical analysis of their properties. Advanced data structures such as balanced trees, graphs and heaps are covered, as are specific algorithms that use these structures efficiently. General algorithm techniques and their analysis are also covered. Class lab time is used to introduce new concepts and explore ones described during lecture.

A comparative study of programming languages. Formal language theory; control flow; data types and abstractions; functions, procedures, and modules; tasks and concurrency. Students write programs in languages such as C, Java, ML, and Prolog that embody the major programming paradigms.

This course builds on fundamental mathematics to present the mathematical foundations of computer science. Topics covered include the basic theoretical models of computation (formal languages and their automata), decidability and un-decidability, and computational complexity.

This course introduces students to operating system concepts while facilitating the synthesis of knowledge related to digital computer organization, assembly language, data structures, and software development. Students learn how operating systems manage processes, provide mechanism for inter process communication and synchronization, and manage computer resources such as memory, processor ti me, and files. Students apply their learning by writing and/or modifying operating system code.

This course is a capstone course wherein students apply the principles of design and development learned from earlier courses toward the implementation of a large-scale software system. Working in inter-disciplinary teams, students explore software life-cycle models, software development methodologies, software revision control, and project management.

The second semester of a two-semester capstone course sequence. While the first semester of the capstone is team based, this second semester gives each student an opportunity to demonstrate the process of independent learning and thinking as it relates to computer science. Students propose, research, write-up and present their own new idea in a computer science area of interest.

This course provides an introduction to the differential and integral calculus. Topics include: the concepts of function, limit, continuity, derivative, definite and indefinite integrals, and an introduction to transcendental functions.

This course provides an introduction to the theory and methods of numerical analysis. Topics include: numerical methods for solving linear and nonlinear equations, polynomial approximation of functions, numerical integration and differentiation, numerical approximation to solutions of differential equations, direct and iterative methods for solving systems of equations.

This is a course on digital electronics and its applications in modern electronic instrumentation. Emphasis is placed on gaining experience with the use of individual digital integrated circuits and programmable arrays. The course covers Boolean algebra, simple gates, combinational and sequential logic circuits, counters, shift registers, state machines, astable multivibrators, encoding, decoding, multiplexing, and conversion between analog and digital representations. Coursework involves both circuit simulation and actual hardware implementations. The course targets applications in the natural sciences, mathematics, and computer science. Three hours of lecture and one three-hour laboratory per week.

• P211 Introductory Physics II
• P212 Introductory Physics II Laboratory