UC Davis General Catalog, 2006-2008 - General Catalog - UC Davis

Engineering: Computer Science 235
students who have taken Electrical and Computer
Engineering 170.—I, II, III. (I, II, III.) Farrens,
Mukherjee
154B. Computer Architecture (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 154A or Electrical and Computer Engineering
170; and course 110. Hardwired and microprogrammed
CPU design. Memory hierarchies.
Uniprocessor performance analysis under varying
program mixes. Introduction to pipelining and multiprocessors.
I, II, III. ( I, II, III.) Farrens
155. Computer Security for Non-Majors (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
programming skill at the level of course 30; Mathematics
21C. Principles, mechanisms, implementation,
and sound practices of computer security and
data protection. Cryptography. Authentication and
access control. Internet security. Malicious software.
Common vulnerabilities. Practical security in everyday
life. Not open for credit to students who have
completed course 153.—I. (I.) Chen, Bishop
156. Discrete-Event Simulation (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
programming skill at the level of course 110; calculus-based
course in probability theory, such as Statistics
120 or 130A or 131A/Mathematics 131 or
Civil and Environmental Engineering 114. Design of
discrete-event simulation software. Random number
generators. Event, process and activity-scanning
approaches. Data structures and algorithms for event
lists. Statistical output analysis. Applications to computer
systems and networks; reliable systems; transportation;
business management.—I.(I.) Matloff
157. Computer Networks for Non-Majors
(4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
programming skills on the level of course 30. Shorter
version of course 152AB featuring World Wide
Web and e-mail examples. Local and wide-area
computer network structures. ISO seven-layer model.
Network protocols for data transmission and internetworking.
Introduction to basic TCP/IP and Web
programming. No credit allowed to students who
have completed courses 152A or 152B.—III. (III.)
Ghosal, Liu, Matloff, Mohapatra, Mukherjee
158. Programming on Parallel
Architectures (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 150; course 154B recommended. Techniques
for software development using the shared-memory
and message-passing paradigms, on parallel architectures
and networks of workstations. Locks, barriers,
and other techniques for synchronization.
Introduction to parallel algorithms.—III. (III.) Farrens,
Ma, Matloff, Pandey
160. Introduction to Software Engineering
(4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 140A. Requirements, specification, design,
implementation, testing, and verification of large
software systems. Study and use of software engineering
methodologies. Team programming.—I, II,
III. (I, II, III.) Levitt, Devanbu
163. Information Interfaces (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 110; course 175 recommended. Art and science
of information visualization and interfaces for
information systems. Design principles of humancomputer
interaction. Visual display and navigation
of non-spatial and higher dimensional data. Implementations,
performance issues, tradeoffs, and evaluation
of interactive information systems.—III. (III.)
Ma, Amenta
165A. Database Systems (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 110. Database design, entity-relationship
and relational models, relational algebra, query language
SQL, storage and file structures, query processing,
system architectures.—II. (II.) Gertz,
Ludaescher
165B. Database Systems (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 165A. Advanced database systems: objectoriented
and object-relational database systems; distributed
and multidatabase systems; advanced database
applications: Web-based database access,
data warehouses.—III. (III.) Gertz, Ludaescher
166. Scientific Data Management (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
programming skills at course level 40; Mathematics
21C. Relational databases, SQL, non-standard databases,
XML, scientific workflows, interoperability,
data analysis tools, metadata.—I. (I.) Gertz, Ludaescher
170. Introduction to Artificial Intelligence
(4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 140A. Design and implementation of intelligent
computer systems. Knowledge representation
and organization. Memory and inference. Problem
solving. Natural language processing.—II. (II.) Levitt
175. Introduction to Computer Graphics (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 110 or Electrical and Computer Engineering
73; Mathematics 22A. Principles of computer graphics.
Current graphics hardware, elementary operations
in two- and three-dimensional space,
transformational geometry, clipping, graphics system
design, standard graphics systems. Individual
projects.—I, II, III. (I, II, III.) Amenta, Joy, Hamann,
Ma, Staadt
177. Introduction to Visualization (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 175. Graphics techniques for generating
images of various types of measured or computersimulated
data. Typical applications for these graphics
techniques include study of air flows around car
bodies, medical data, and molecular structures.—II.
(II.) Joy, Hamann, Ma, Staadt
178. Introduction to Geometric Modeling
(4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 175. Interactive graphics techniques for
defining and manipulating geometrical shapes used
in computer animation, car body design, aircraft
design, and architectural design.—I. (I.) Joy,
Hamann, Max, Staadt
188. Ethics and the Information Age (3)
Seminar—2 hours; term paper. Prerequisite: upper
division standing. Responsibilities of computer scientists
as influenced by growth in computer use and
networks.—I, II, III. (I, II, III.)
189A-L. Special Topics in Computer Science
(1-5)
Lecture, laboratory or combination. Prerequisite:
consent of instructor. Special topics in (A) Computer
Science Theory; (B) Architecture; (C) Programming
Languages and Compilers; (D) Operating Systems;
(E) Software Engineering; (F) Data Bases; (G) Artificial
Intelligence; (H) Computer Graphics; (I) Networks;
(J) Computer-Aided Design; (K) Scientific
Computing; (L) Computer Science. May be repeated
for credit when topic differs.—I, II, III. (I, II, III.)
190C. Research Group Conferences in
Computer Science (1)
Discussion—1 hour. Prerequisite: upper division
standing in Computer Science and Engineering; consent
of instructor. Research group conferences. May
be repeated for credit. (P/NP grading only.)—I, II,
III. (I, II, III.)
190X. Senior Seminar (2)
Seminar—2 hours. Prerequisite: senior standing.
Examination of a special topic in a small group setting.
192. Internship in Computer Science (1-5)
Internship. Prerequisite: completion of a minimum of
84 units; project approval prior to period of internship.
Supervised work experience in computer science.
May be repeated for credit. (P/NP grading
only.)
197T. Tutoring in Computer Science (2-3)
Discussion—1 hour; laboratory/discussion—3-6
hours. Prerequisite: upper division standing, consent
of instructor. Tutoring in computer science courses,
especially introductory courses. (P/NP grading
only.)
198. Directed Group Study (1-5)
Prerequisite: consent of instructor. (P/NP grading
only.)
199. Special Study for Advanced
Undergraduates (1-5)
(P/NP grading only.)
Graduate Courses
201A. Advanced Computer Architecture (4)
Lecture—3 hours; term paper. Prerequisite: course
154B or Electrical and Computer Engineering 170;
course 150. Modern research topics and methods in
computer architecture. Design implications of memory
latency and bandwidth limitations. Performance
enhancement via within-processor and between-processor
parallelism. Term project involving studentproposed
extensions/modifications of work in the
research literature. Not open for credit to students
who have completed course 250A.—I. Farrens
201B. High-Performance Uniprocessing (4)
Lecture—3 hours; term paper. Prerequisite: course
201A. Maximizing uniprocessor performance. Barriers
to high performance; solutions to the problems;
historical and current processor designs. Not open
for credit to students who have completed course
250B.—II. Farrens
201C. Parallel Architectures (4)
Lecture—3 hours; project—1 hour. Prerequisite:
course 201A. Evolution of parallel architectures from
special-purpose machines to commodity servers.
Emphasis on recent machines and applications that
drive them. Not open for credit to students who have
completed course 250C.—III.
203. Novel Computing Technologies (4)
Lecture—3 hours; project—1 hour. Prerequisite:
course 201A. Novel computing technologies that
could revolutionize computer architecture. Quantum
computing technologies, including algorithms,
devices, and fault tolerance. A survey of other
unconventional technologies including nanoscale
electronics, MEMS devices, biological devices, and
nanotechnology. Offered in alternate years.—II.
220. Theory of Computation (4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 120, 122A. Time and space complexity
classes. Reductions, completeness, and the role of
randomness. Logic and undecidability.—III. Rogaway
222A. Design and Analysis of Algorithms
(4)
Lecture—3 hours; discussion—1 hour. Prerequisite:
course 122A; Statistics 131A recommended. Techniques
for designing efficient algorithms, analyzing
their complexity and applying these algorithms to a
broad range of applications. Methods for recognizing
and dealing with difficult problems.—I, II. (I, II.)
Amenta, Franklin, Gusfield, Martel, Rogaway
222B. Advanced Design and Analysis of
Algorithms (4)
Lecture—3 hours; project—1 hour. Prerequisite:
course 222A. Advanced topics in complexity theory.
Problem classification. The classes P, NP, P-space,
co-NP. Matching and network flow algorithms.
Matrix multiplication. Approximation algorithms.—
III. (III.) Gusfield, Franklin, Martel, Rogaway
223. Parallel Algorithms (4)
Laboratory/discussion—3 hours; project—1 hour.
Prerequisite: course 222A. Models of parallel computer
systems including PRAMs, loosely coupled systems
and interconnection networks. Parallel
algorithms for classical problems and general techniques
for their design and analysis. Proving lower
bounds on parallel computation in several settings.—II.
(II.) Martel
Quarter Offered: I=Fall, II=Winter, III=Spring, IV=Summer; 2007-2008 offering in parentheses
General Education (GE) credit: ArtHum=Arts and Humanities; SciEng=Science and Engineering; SocSci=Social Sciences; Div=Social-Cultural Diversity; Wrt=Writing Experience