The Computer Science minor provides students with an excellent foundation in computer science, while providing freedom to explore special topics of interest. The minor builds strong programming and problem solving skills, and is particularly useful when combined with a major in any of the sciences, Mathematics, Business, Economics, Linguistics, or Geography. Students interested in the natural sciences and mathematics will particularly benefit from CPSC 109 and 420. Students interested in pursuing graduate studies in computer science should consider taking CPSC 305, 326, 401 and/or 405.
Computer Science Minor Requirements (20 credits)
Any Computer Science course, of at least 3 credits, numbered 100 or higher; CPSC 220 and 240; any three (3) Computer Science courses numbered 300 or above, for a total of at least 9 credits.
Computer Science Course Offerings
Computer Science course offerings will be found under the 4 letter code of CPSC in the course listings.
104 – The Internet: Technology, Information, and Issues (3)
A survey of the technology and issues underlying the use of the Internet for communication, resource discovery, research, and dissemination of information in multimedia formats. Topics include an introduction to Internet protocols, Internet history and development, electronic mail, use and functions of a Web browser, accessing Internet services and resources, using the Internet for research, Website design and implementation, and social, legal, and ethical issues related to using the Internet.
105 – Problem Solving with Databases (3)
Introduces relational databases as a common problem-solving tool for business, scientific, and personal applications. Covers issues of information representation, abstraction, redundancy and inconsistency. Introduces database schema design based on the relational model, including semantic modeling, integrity constraints, and language-based queries. Students build sample database solutions based on real-world problem domains. May not be taken after passing CPSC 350.
106 – Digital Storytelling (3)
People have been telling stories since the beginning of time, but how is storytelling evolving in the digital age? This course explores how computers are being used to tell stories. We’ll study text-based technologies – blogging, the web – and how those models have changed the way we publish and disseminate narratives. We’ll also study the roles of audio, video, and images in narrative: computer animation, the ethics of altering digital images, and the Story Corps project. Students will use technology including blogs, virtual worlds, and computer games to create and tell their own stories. No previous computer experience is necessary.
109 – Introduction to Modeling and Simulation (3)
This course introduces students to the concepts of modeling and simulation as tools for solving problems in the sciences. Students will be introduced to several modeling and simulation tools and will learn how to decompose problems so they can be represented and solved with the tools. Agent models and system models will be introduced. Example problems to demonstrate the modeling and simulation techniques and tools drawn from a number of scientific fields and will introduce basic problems that will not require depth of knowledge in any particular field of science. Examples of these problems include forest fires, predatory problems, transmission of diseases, chemical reactions, and elementary particle simulations. Students completing the course will be able to model complex systems and have attained programming skills equivalent to those learned in CPSC 110. No previous programming experience or computer background is expected.
110 – Introduction to Computer Science (3)
This course provides a foundation in computer science for a student who does not have prior programming experience. It provides sufficient support to permit a student to continue in the major program. Topics include an introduction to the algorithm and program development process using a high-level structured programming language and the department’s computing facilities. Supervised hands-on experience provided. May not be taken for graded credit after passing any Computer Science course numbered 220 or higher.
219 – Foundations for Data Science (3)
Prerequisite: DATA 101. Skills and tools in acquiring, parsing, manipulating, and preparing data for statistical analysis. Cross-listed as DATA 219 and DSCI 219.
220 – Computer Programming and Problem Solving (4)
Prerequisite: CPSC 110 or 219 or successful completion of the UMW computer science placement exam. Continued coverage of disciplined problem-solving and algorithmic development including emphasis on procedural and data abstraction. Topics include elementary data structures such as arrays, files, and classes. The notions of data modeling and the linking of data type definitions with their associated operations is introduced. Study of program design, coding, debugging, testing, and documentation in a higher level language that supports the object-oriented paradigm. Intended for students who have had previous programming experience.
225 – Software Development Tools (1)
Prerequisites: CPSC 220. This course provides a practical introduction to using common software development tools. Topics will include using the Unix command line, files and permissions, managing processes, the vim text editor, version control, and writing shell scripts.
240 – Object-oriented Analysis and Design (4)
Prerequisite: CPSC 220 (grade of C or better). Theory and practice of the object-oriented software development paradigm including abstraction, encapsulation, inheritance, polymorphism, aggregation, visibility, modeling notations and designs patterns. Also covers issues in collaborative software development including communication, code sharing, diversity, and inclusion. Students work in teams to develop collaborative software solutions in an object-oriented language.
270 – Introductory Special Topics in Computer Science (3)
284 – Applied Discrete Mathematics (4)
Prerequisites: CPSC 110, 219, or 220 or successful completion of the UMW computer science placement exam. Designed to prepare beginning Computer Science majors for advanced study by emphasizing the components of Discrete Mathematics especially related to Computer Science. Topics include number systems, logic, methods of proof, counting techniques, mathematical induction, sets, relations, functions, vectors, matrices, graphs, and trees.
302 – Computer Ethics (3)
Prerequisite: CPSC 110 or 220. An examination of issues and events related to ethics, professional conduct and social responsibility as they apply to the field of Computer Science. Includes study of ethical responsibilities and behaviors appropriate for computer scientists.
305 – Computer Systems and Architecture (4)
Prerequisites: CPSC 225, a grade of C or better in CPSC 240, and either CPSC 284 or MATH 325. This course examines the basic operation of computing systems. It takes a bottom-up approach covering each major component of such systems including hardware, logic circuit design, CPU instruction sets, assemblers, and compilers. Students will gain experience programming in assembly language and C.
310 – Computer Information Systems (4)
Prerequisite: CPSC 220. This course introduces the student to the use and implications of information technology in the business environment. This course covers such topics as data management, networks, analysis and design, computer hardware and software, decision support systems, database management systems, transaction processing systems, executive information systems, and expert systems. It also provides activity with computer-based and non-computer-based problems/cases and includes real-world programming projects that are implemented using a high-level programming language.
320 – Statistics for Computer Scientists (3)
Prerequisites: MATH 121 and CPSC 220. A calculus-based mathematical statistics course with special emphasis on applications in Computer Science. Topics include probability, mass/density functions, discrete/continuous random variables, and general data analysis using a statistical software package.
326 – Theoretical Foundations of Computing (4)
Prerequisites: CPSC 240 and either CPSC 284 or MATH 325. Covers structures and concepts relating to the underlying theory of computation and mathematical models of actual physical processes. Also covers a repertoire of advanced algorithms for data processing, and the asymptotic analysis of those algorithms to describe their running time and space requirements. Topics may include formal languages, automata theory, Turing machines, the halting problem, NP completeness, searching and traversal algorithms, dynamic programming, compression algorithms, and random number generation.
340 – Data Structures and Algorithms (4)
Prerequisite: CPSC 225, a grade of C or better in CPSC 240, and either CPSC 284 or MATH 325. Continued study of data modeling and incorporation of abstract data types including linked lists, stacks, queues, heaps, trees, and graphs. Study of advanced sorting and searching techniques. Provides experience in the use of algorithm analysis. Continued study of program design, coding, debugging, testing, and documentation in an object-oriented higher level language.
345 – Introduction to Computer Security (3)
Prerequisite: CPSC 220 and 225. Provides an introduction to computer security. The focus is on providing the students a wide overview of current computer security. Topics covered include, but are not limited to, basic cryptography, network security, system security, wireless security and mobile security. In addition, course labs provide a hands-on, in-depth exploration of specific topics.
348 – Web Application Development (3)
350 – Applications of Databases (4)
Prerequisite: CPSC 225, and a grade of C or better in CPSC 240. Presents basic techniques for the design and implementation of database-driven web applications. Topics include the design of relational and NoSQL databases and scaling techniques such as the use of load balancing and distributed systems. Programming intensive using a dynamic high-level general-purpose language.
370 through 377 – Special Topics in Computer Science (1–4)
Prerequisites: Specified by Instructor. Lecture or seminar class. Most recently this has included topics such as Information Visualization and Computational Linguistics. May be repeated for credit with a change in topic.
391 – Special Projects in Computer Science (1-4)
Prerequisite: Permission of Instructor. Intensive individual investigation of significant research problem under the direction of a faculty member. GPA and course prerequisites apply.
401 – Organization of Programming Languages (3)
Prerequisites: CPSC 326 and 340. A course in programming language construction and design emphasizing the run-time behavior of programs. Alternative implementations of programming language constructs are considered. Techniques for language definition may also be discussed.
405 – Operating Systems and Systems Programming (4)
Prerequisites: CPSC 305 and 340. This course examines the abstractions above the hardware that make a computer usable to both programmers and users. These abstractions include processes, context switching, concurrent programming, semaphores, virtual addressing, transactions, access control, and virtualization. Many of these abstractions are the foundation for operating systems kernel development. The abstractions are also applicable to any large-scale programming project. Programming intensive.
414 – Network Principles and Applications (3)
Prerequisite: CPSC 220 and 225. This course provides an introduction to the basic principles of networking. Topics covered in the course include: network topologies, protocols, the OSI Model, methods of data transmission, error detection and correction, TCP/IP, network security and other topics as time permits. This course is theoretical and concept-oriented rather than consisting of the details of specific network packages.
415 – Artificial Intelligence (3)
Prerequisites: CPSC 240 and either CPSC 284 or MATH 325. A survey of current artificial intelligence topics including informed search, knowledge representation, knowledge-based systems, and machine learning. Other topics such as image processing, robotics, and language processing, may also be covered. Artificial intelligence programming projects are required.
419 – Data Mining (3)
Prerequisite: DATA 219, DSCI 219, CPSC 219, or CPSC 220. Practical knowledge of data mining, machine learning, and information retrieval. Students will examine the theoretical foundations of a variety of techniques, gain experience with these techniques using open source software, and learn how to apply them to real-world problems. Topics include decision trees, Naïve Bayes, probabilistic retrieval models, clustering, support vector machines, approaches to web mining, and scalable machine learning applications. Cross-listed as DATA 419.
420 – Modeling and Simulation (3)
Prerequisite: DATA 219, DSCI 219, CPSC 219, or CPSC 220. A robust introduction to techniques of mathematical modeling and computational simulation applied to practical problems. Topics include system dynamics approaches, discrete-event simulation, and agent based models. Students complete small projects on topics as diverse as population growth, epidemic transmission, queuing theory, and forest fire outbreaks. Cross-listed as DATA 420.
425 – Parallel Computing (3)
Prerequisite: CPSC 340. This course provides an introduction to parallel computing, covering topics including parallel architectures, programming techniques and libraries, the study of existing parallel computing systems, and performance analysis. Students will use a variety of hardware to explore current libraries and methods used for parallel programming.
430 – Software Engineering (4)
Prerequisite: CPSC 340 and 350. Techniques for modeling, designing, implementing, and managing large-scale computer programs are studied. Studies include software process models, modeling using UML, and application development with a CASE tool. Continued study of issues in collaborative software development including communication, code sharing, diversity and inclusion. Students work in groups and apply the techniques studied to semester-long projects.
440 – Game Programming (3)
Prerequisite: CPSC 340. Students will design, develop, and implement computer games that involve real-time, event-driven, and multimedia programming techniques. Students learn the history of computer games and the elements of video game design and architecture.
444 – Three Dimensional Computer Graphics (3)
Prerequisites: CPSC 340. The study of three-dimensional modeling involving the use of light, color, texture and transformation; visible surface detection; parallel and perspective projections; clipping algorithms.
445 – Software Security (3)
Prerequisite: CPSC 345 or MIST 411. A course on the intersection of software and information security. A programming intensive course. Topics include but are not limited to: Programming flaws, causes, identification, exploitation and prevention; malicious software, development, identification, and prevention; software fuzzing and other flaw identification and testing methods.
448 – Advanced Web Application Development (3)
Prerequisite: CPSC 348 or 350 or permission of the instructor. An examination and application of contemporary software technologies focused on providing Web-based services and applications. Students work in teams to design and develop leading-edge projects. In the recent past this has included developing advanced data-driven applications employing AJAX, PHP, and a database management system.
470 through 477 – Selected Topics in Computer Science (1-4)
Prerequisite: Specified by Instructor. Treatment of selected topics in Computer Science. Most recently this has included topics such as Cloud Computing, Animation, and Information System Security. May be repeated for credit with a change in topic.
491 –Individual Study in Computer Science (1-4)
Prerequisite: Departmental permission. Individual study under the direction of a member of the department. GPA and course prerequisites apply. May be repeated for credit with a change in topic. Two semesters of 3 credits of study required for graduation with Departmental Honors.
499 – Internship (Credits variable)
Supervised off-campus experience with an academic component, developed in consultation with the department. Only 3 credits may count toward the major and minimum GPA and course prerequisites apply.