2007-2008 Course Listings

121Q. Computing in the Arts and Sciences. 4 semester hours.

Broad introduction to computing designed for the general liberal arts student. Emphasis on problem-solving through spreadsheets, databases, graphics and elementary programming. Operating systems, computer networks, and issues related to computers in society are also addressed. Laboratory required. Prerequisite: Appropriate level on the Mathematics Placement Exam. Every year.

150Q. Computer Programming I. 5 semester hours.

Introduction to computer science through the use of programming. Designed primarily for the student who expects to take further courses in computer science. Topics include programming in a high-level language, problem-solving, algorithm design, control constructs, data constructs, input output, procedural abstraction and the role of computing in society. Laboratory required. Prerequisite: Appropriate level on the Mathematics Placement Exam. Every year.

246Q. Programming Language Laboratory. 2 semester hours.

Study of one of several possible programming languages (e.g. C++, Java, Scheme, Prolog). Offered occasionally according to the needs and interest of students and/or faculty. Prerequisites vary, depending upon which language is taught, but in all cases the student must already know how to program in at least one high-level language. This course may be repeated for credit.

250Q. Computer Programming II. 5 semester hours.

Continuation of Computer Science 150. Disciplined programming using one or two high-level languages with specific emphasis on program design, style, efficiency and documentation. Includes the theory and application of abstract data types using arrays, lists, stacks, queues, trees and networks. Also provides an overview of computer science. Laboratory required. Prerequisite: Computer Science 150 or equivalent. Writing intensive. Every year.

253Q. Principles of Software Design. 4 semester hours.

This course emphasizes modern software design and development techniques, as well as expanding upon topics introduced in Computer Programming I and II.  Topics covered include object-oriented design issues, formal design languages such as UML, design patterns, use of APIs, exception handling and fault-tolerant computing, event-driven programming, threading and multithreaded code, elementary concepts in security, authentication and encryption, the client-server model of networking, verification techniques, and advanced data structures.  Assignments will be both theoretical and applied.  Prerequisite: Computer Science 250. Every year.

255Q. Principles of Computer Organization. 5 semester hours.

Considers the organization and architecture of the computer from the digital logical level to the conventional machine level to the operating system level. Programming assignments in Assembly language are used to demonstrate and reinforce the various architectural structures and techniques studied. Laboratory required. Prerequisite: Computer Science 150. Every year.

260. Computational Models and Methods. 5 semester hours.

Computational science is the field of study that integrates natural science, computer science and applied mathematics. This course is an introduction to the principles and approaches of computational science. This includes the understanding, development, and use of mathematical models as well as their effective computer implementation using languages such as Mathematica®, C/C++ and FORTRAN. It is specifically designed to be accessible to a wide range of students, especially those with an interest in biology, chemistry, geology, physics or psychology. A spectrum of problems taken from these sciences will be addressed. Topics include: using Mathematica®, Sources of Errors, The Experimental Method, Types of Science Models, Formula Evaluation, Dimensional Analysis, Model Sensitivity, Visualization Methods, Solving Equations, Computer Simulation, Floating-Point Arithmetic, Limits of Computation, Data Fitting, Optimization Methods and Ethical Issues. Each student will undertake a realistic modeling project in one of the sciences. Computer laboratory required. Prerequisites: 1. MATH 131 or MATH 201. 2. COMP 150 or previous programming experience with discretion of the instructor. The student will be expected to be familiar with the use of a scientific graphing calculator. This course is cross-listed as MATH 260. Students may enroll in either COMP 260 or MATH 260, but not both. Mathematical-reasoning intensive. Alternate years.

265Q. Principles of Programming Languages. 4 semester hours.

This course emphasizes the principles and programming styles associated with the four major language paradigms: imperative, functional, object-oriented and declarative; examination of contemporary programming languages. Topics include syntax and semantics, statement and subprogram control, data types and data control, design and implementation issues. Prerequisites: Mathematics 271 and Computer Science 250.  Every year.

275Q. Sequential and Parallel Algorithms. 4 semester hours.

Systematic study of algorithms and of their complexity. A number of symbolic and numeric algorithms from the areas of searching and sorting, string and pattern matching, matrix and vector processing, and graph and tree algorithms are studied. Sequential and parallel algorithms are compared. The issues of intractable problems, P and NP algorithms, and NP completeness are studied. Prerequisites: Mathematics 271 and Computer Science 250. Co-requisite: Mathematics 205. Every year.

280Q. Topics in Computer Science. 2-4 semester hours.

Study of special topics not included in other departmental offerings. Offered occasionally according to the needs and interests of students and/ or faculty. Possible topics include Analysis of Algorithms, Compiler Theory, Networks, Optimization Techniques, Parallel Processing, and Simulation Methods. Prerequisites vary. This course may be repeated for credit.

285Q. Theory of Computation. 4 semester hours.

Covers topics in the theory of computation. Topics include the study of finite state machines, pushdown automata, linearly bounded automata, Turing machines, languages, phase-structure grammars (regular, context-free, context-sensitive, unrestricted), parsing, decidability, computability, computational complexity, and the Chomsky Hierarchy. Prerequisite: Mathematics 271 and Computer Science 250. Usually offered in alternate years.

290Q. Databases and Web-Based Computing. 4 semester hours.

The primary topic of this course is databases and how they are used in database-driven web sites.  We will cover some theoretical aspects of the field, but the primary emphasis will be on practical applications.  Topics include design and use of databases through common software, the ER and Relational Data models, PHP, MySQL and develoopment of a web-based database.  Assignments will be both theoretical and applied. Prerequisite: Computer Science 150. Alternate years.

320Q. Numerical Analysis. 4 semester hours.

Introduction to the numerical solution of mathematical problems. Primary emphasis is on the development of computational techniques that can be implemented on a digital computer and on methods for establishing error bounds for approximate solutions. Prerequisites: Computer Science 150 and Mathematics 202 and 205. Usually offered in alternate years.

331Q. Introduction to Computer Hardware. 5 semester hours.

This course covers the design of digital electronic circuits including both combinatinoal logic and synchronous sequential logic.  Small-to-medium scale integrated circuits are used.  Laboratory required.  Prerequisite: Computer Science 255.  Usually offered in alternate years.

345Q. Optimization. 4 semester hours.

Optimization is a very successful area of applied mathematics and its applications are very broad and diverse.  This course addresses the problem of doing the "best" thatone can do, possibly subject to resource constraints.  Simulation models allow one to determine how a function behaves as its variables change.  Optimization models are used to determine the "optimal" values of these variables so that the function can be maximized or minimized.  In this course, one learns how to recognize and formulate different types of optimization models, sometimes called "mathematical programming" models (e.g., unconstrained, linear programming, quadratic programming, and general nonlinear programming).  One learns how to identify local and global solutions to these models and how to find these solutions by using various algorithms (e.g., steepest descent, Newton, BFGS, simplex, gradiient projection, evolution).  This course will present theory, methods, and applications equally.  Both analytic and programming assignments will be given, together with exams.  Mathematica will be used.  This course is cross-listed as Mathematics 345. Prerequisites: Mathematics 201 and 205 and Computer Science 150.

350Q. Artificial Intelligence. 4 semester hours.

Introduction to the major areas of artificial intelligence and the use of computer language with both symbolic and numeric processing capabilities such as Common Lisp. The AI areas include knowledge representation, language understanding vision, expert systems, neural networks and robotics. Programs to implement techniques associated with these areas are written primarily in this language. Social, ethical and philosophical viewpoints related to AI are addressed. Prerequisites: Mathematics 271 and 205 and Computer Science 250. Usually offered in alternate years.

351Q. Operating Systems. 4 semester hours.

Process management, I/O devices, interrupt structures, resource and memory management, and file systems. Students study aspects of several operating systems and work in detail on one. Prerequisite: Computer Science 255. Writing intensive. Usually offered in alternate years.

370Q. Computer Graphics. 4 semester hours.

Explores computer graphics. Emphasis is on the techniques used and mathematics behind the standard graphics algorithms. Graphics software is developed based on a small number of primitive graphics operations. Prerequisite: Computer Science 275. Usually offered in alternate years.

380Q. Topics in Computer Science. 2-4 semester hours.

(See course description for Computer Science 280). This course may be repeated for credit.

460Q. Seminar/Colloquium. 2 semester hours.

Combined individual and group research presentations involving advanced computer science material. Required of all computer science majors. Writing intensive. Every year. This course may be repeated for credit.

480Q. Topics in Computer Science. 2-4 semester hours.

(See course description for Computer Science 280).

490. Independent Study. Variable credit.

Individual study by the advanced student of a topic beyond the scope of regular courses. Prerequisite: Approval of faculty member directing the study. This course may be repeated for credit.

491. Internship. Variable credit.

Open to the junior or senior computer science major by departmental permission only.

499. Honors Thesis/Project. Variable credit.

Prerequisite: 3.50 GPA, permission of the Department Chair.