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Course Criteria
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3.00 Credits
Design, analysis, and implementation of advanced computer algorithms. Emphasis is given to problem-solving techniques, including the greedy method, divide-and-conquer, and dynamic programming. Specific problem domains vary. Topics may include sorting, graphs, networks, computational geometry, NP-completeness, approximation algorithms, text processing, distributed systems, and numerical algorithms. Three lecture and one laboratory hour per week. Prerequisite(s): Computer Science 222. Unit(s): 1
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3.00 Credits
Structure of operating systems, process management, memory management, file systems, and case studies. Three lecture and one laboratory hour per week. Prerequisite(s): Computer Science 222 and 301. Unit(s): 1
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3.00 Credits
Project-oriented course. Principles of software engineering will be emphasized throughout. Three lecture and one laboratory hour per week. Prerequisite(s): Senior standing or two courses at the 300 level that have Computer Science 301 or 315 as a prerequisite. Unit(s): 1
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3.00 Credits
Concepts in design and implementation of programming languages, including compile-time and run-time issues. Support for block-structured procedural languages, object-oriented languages, and functional languages. Three lecture and one laboratory hour per week. Prerequisite(s): Computer Science 301 and 315. Unit(s): 1
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3.00 Credits
Introduction to systematic management of data: design and implementation of relational databases, data modeling, normalization, indexing, relational algebra, query processing, and transaction management.Programming projects include substantial use of SQL and its extensions. Three lecture and one laboratory hour per week. Prerequisite(s): Computer Science 221 and 222. Unit(s): 1
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3.00 Credits
Introduction to simulation. Discrete-event simulation, Monte Carlo simulation, simulation of queuing and inventory systems, random number generation, discrete and continuous stochastic models, elementary statistics, point and interval parameter estimation, and input modeling techniques. Three lecture and one laboratory hour per week. Prerequisite(s): Computer Science 222 and 301. Unit(s): 1
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3.00 Credits
(See Mathematics 328.) Unit(s): 1
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3.00 Credits
Finite state machines, regular languages, push-down automata, and context-free languages. Turing machines, recursive functions, and related topics. Three lecture and one laboratory hour per week. Prerequisite(s): Computer Science 315. Unit(s): 1
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3.00 Credits
Regular languages, context-free languages, finite automata, push-down automata, lexical analysis, parsing, intermediate representation, and code generation. Three lecture and one laboratory hour per week. Prerequisite(s): Computer Science 222 and 301. Unit(s): 1
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3.00 Credits
Principles and techniques for data communication between computers. Topics include design and analysis of communication protocols, routing, congestion control, network-centric applications, and recent advances. Three lecture and one laboratory hour per week. Prerequisite(s): Computer Science 301. Unit(s): 1
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