Duke University 2008-2009 - Office of the Registrar - Duke University

The Department of Computer Science offers programs leading to the MS and PhD
degrees in areas of concentration including algorithms, artificial intelligence, scientific
computing and numerical analysis, and systems and architecture. The MS program consists
of coursework (30 credits) and a research thesis or project under the supervision of a faculty
advisor. The PhD program consists of coursework and a sequence of research milestones
culminating in a doctoral dissertation. Course programs for both degrees include a breadth
requirement, advanced courses in the declared area of concentration, and two courses in a
related field of study. For the PhD program the breadth requirement is satisfied by earning
qualifying credit in four of six core areas of subject knowledge. All entering graduate
students participate in a special seminar course (Computer Science 300) to introduce them
to the discipline and profession of computer science. A student entering graduate study in
computer science should have a strong undergraduate grounding in the fundamentals of
calculus, linear algebra, and discrete mathematics, and basic knowledge of data structures,
assembly language, and one or more higher-level computing programming languages; some
undergraduate research experience is preferred. Students should consult the official
departmental documents Graduate Degree Requirements and Addendum: Graduate
Research in Computer Science for a full explanation of requirements not listed in this
bulletin.
Outstanding programs in geometric computing; internet systems, networking and
security; biological computing and nanotechnologies; memory systems and massive data
management; learning and modeling, computer graphics and visualization, sensor networks,
numerical analysis, software engineering, complexity theory, and robotics provide exciting
and challenging research opportunities to students in computer science. The research
interests of our faculty overlap with these areas and with researcher areas in other disciplines
such as biology, engineering, nanotechnology, environmental sciences and medicine.
210. Operating Systems. Fundamental principles of operating system design applied to
state-of-the-art computing environments (multiprocessors and distributed systems)
including process management (coscheduling and load balancing), shared memory
management (data migration and consistency), and distributed file systems. Instructor:
Chase or Cox. 3 units.
212. Distributed Information Systems. Principles and techniques for sharing information
reliably and efficiently in computer networks, ranging from high-speed clusters to globalscale
networks (e.g., the Internet). Topics include advanced distributed file systems,
distributed programming environments, replication, caching and consistency, transactional
concurrency control, reliable update and recovery, and issues of scale and security for
Internet information services. Prerequisites: Computer Science 110 or 210 and Computer
Science 214, or consent of the instructor. Instructor: Chase. 3 units.
214. Computer Networks and Distributed Systems. Basic systems support for processto-process
communications across a computer network. The TCP/IP protocol suite and the
Berkeley sockets application programs interface. Development of network application
programs based on the client-server model. Remote procedure call and implementation of
remote procedure call. Prerequisite: knowledge of the C programming language. Instructor:
Staff. 3 units.
215. Wireless Networking and Mobile Computing. 3 units. C-L: see Electrical and
Computer Engineering 256
216. Advanced Database Systems. Advanced database management system design
principles and techniques. Materials drawn from both classic and recent research literature.
Possible topics include access methods, query processing and optimization, transaction
processing distributed databases, object-oriented and object relational databases, data
warehousing, data mining, web and semistructured data, search engines. Programming
projects required. Prerequisites: An introductory database course or consent of instructor.
Instructor: Babu or Yang. 3 units. C-L: Computational Biology and Bioinformatics 233
Courses of Instruction 107