Computer Science Major and Minor

Computer Science Curriculum Guide

The computer science degree curriculum is based on three themes: abstraction, integration, and languages and paradigms.

Abstraction

Abstraction is based on the concept of layers in which the details of one layer of abstraction are hidden from layers at a higher level. A computer scientist uses abstraction as a thinking tool to understand a system, model a problem, and master complexity. The ability to abstract cannot be acquired in a single course, but must be developed over several years. Consequently, all courses in the computer science major curriculum emphasize the abstraction process, not only as a framework to understand the discipline but also as a tool to solve problems.

Integration

The curriculum focuses on how well the courses are integrated as opposed to how many courses are offered. There are two important aspects of integration in the curriculum—integration between courses and the integration of theory and practice. Without integration between courses the curriculum becomes simply a collection of unrelated facts with no unity based on fundamental principles. The integration of theory and practice not only serves to reinforce the students' understanding of abstract concepts but also provides them with insight and appreciation of the practical solutions at hand.

Languages and Paradigms

Because of the continued evolution of programming languages and paradigms, we emphasize multiple programming languages and paradigms throughout the curriculum.

Our curriculum seeks to strike the proper balance between breadth and depth. Too much breadth will not equip students with the detailed skills necessary to solve realistic problems. Too much depth in one language or paradigm will give students a narrow vision that makes it difficult to consider multiple approaches to a problem.

Breadth is achieved by giving students a choice of programming languages and associated courses during the first semester. Depth is achieved by using a different single industrial-strength language during the second and third semesters. Courses in the following semesters introduce other programming paradigms based on different languages.

The language choice for the first two years is driven by both pedagogical and practical industry concerns. Pedagogical concerns are important during the first two years, because this is when students begin to form algorithmic thinking patterns and develop problem-solving skills. The criteria are that the programming environment should be simple to learn yet powerful enough to illustrate fundamental concepts of computing.

Skill in a practical language is necessary for students to be well equipped for their postgraduate careers. The languages for the third and fourth years are chosen for the variety of programming paradigms on which they are based.