CS 500: Graduate Research in Computer Science
CS 510: Computation Theory
CS 515: Design and Analysis of Algorithms
CS 520: Operating Systems
CS 525: Analysis of Computer Systems
CS 531: Program Analysis and Transformation
CS 535: Advanced Programming Language Concepts
CS 540: Parallel Algoritms
CS 550: Software Engineering
CS 560: Parallel Comptuer Architectures
CS 580: Artificial Intelligence
CS 590: Computer Science Seminar
CS 599: Reading and Research
CS 500 Graduate Research in Computer Science (var to 12) f,w,s,su
The study of an acceptable computer science problem and the preparation
of a thesis.
Prerequisite: Permission of Department.
CS 510 Computation Theory (0-4-0) s 4
Properties of context-free, deterministic context-free and LR(K) languages;
linear bounded automata and context-sensitive languages; decidability
problems; other models of computation--multi-tape and RASP machines;
primitive recursive and recursive functions; complexity measures; time
and space hierarchies.
Prerequisite: CS 411
CS 515 Design and Analysis of Algorithms (0-3-3) w 4
This course is a continuation of CS 425 and covers advanced techniqures for
design and analysis of computer algorithms. Topics include amortized
analysis, divide-and-conquer algorithms, dynamic programming, greedy
algorithms, graph algorithms, NP-completeness, approximation algorithms.
Prerequisite:
CS 411 and
CS 425; or permission
of instructor.
CS 520 Operating Systems (0-3-3) f 4
Principles and design philosophies of operating systems. Topics include
process and storage management, deadlocks, determinacy, mutual exclusion,
synchronization, interrupts, paging segmentation, swapping schemes, file
systems, resource allocation, protection and reliability, processor
scheduling and performance anaylsis.
Prerequisites: CS 440
and CS 450
or the consent of the instructor.
CS 525 Analysis of Computer Systems (0-3-3) w 4
Performance analysis and computer system modeling techniques, both stochastic
and analytic. Important issues, including queueing systems, scheduling
disciplines and multiprogramming models will be addressed. There will
be a project.
Prerequisites: CS 520,
a course in probability and statistics, and a course
in discrete simulation techniques or consent of instructor.
CS 531 Program Analysis and Transformation (0-3-3) s 4
Topics include control flow and data flow analysis, program transformations,
code generation, run-time systems and considerations for special
hardware. A major project is required.
Prerequisite: CS 430
CS 535 Advanced Programming Language Concepts (0-3-3) w 4
Formal specification of the syntax and semantics of programming languages:
VDL, Lambda calculus, and others; proofs of program correctness and
termination; semantics of data structures, advanced data types; new high
level languages.
Prerequisites: CS 411
and CS 420
CS 540 Parallel Algorithms (3-0-3) f 4
This course emphasizes principles used in the development of algorithms for
parallel computers, including the topics: programming paradigms,
implementation, analysis and performance evaluation. Algorithms in the
areas of scientific computation and nonnumeric processing are considered,
as are software tools for automatic vectorization and parallelization,
performance visualization, and debugging. Host machines include shared
memory systems, distributed memory systems, and networks of workstations.
Prerequisites: CS450
and CS 425,
or permission of instructor.
CS 550 Software Engineering (0-3-3) f 4
Current issues related to the development of large-scale software. Some
topics covered include formal approaches to requirements definition,
software specifications and designs, language issues, testing criterion,
and management and organizational issues.
Prerequisite: CS 465
CS 560 Parallel Computer Architectures (0-4-0) w 4
An in depth study of various aspects of parallel processing, with an
emphasis on parallel processing architectures. The course will have an
analytical focus and will investigate models of various aspects of the
design and analysis of parallel processing systems. Topics include:
simple uniprocessor/multiprocessor performance models, pipelining, parallel
processing and multiprocessor design issues (synchronization,
communication, contention), processor array architectures, and algorithms
for multiprocessors and processor arrays.
Prerequisites: CS 450
and MA 321
CS 580 Artificial Intelligence (0-3-3) s
Concepts in artificial intelligence are presented including problem-solving
methods: state-space representations, heuristics, production systems,
problem reduction methods; knowledge representation: semantic networks,
frames, scripts, predicate calculus, augmented transition networks;
learning; and natural language understanding.
Prerequisites: CS 420
CS 590 Computer Science Seminar (var to 5) (on demand)
From time to time, depending on student demand, a seminar will be offered on advanced topics in current Computer Science research.
CS 599 Reading and Research (var to 5) (on demand)
Individual reading and research on current topics in comptuer science.
Prerequisite: consent of instructor
Department of Computer Science
Last Updated: Monday, August 27, 2001