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Course Criteria
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3.00 Credits
Prerequisite: CSCI 4401 or consent of the department. This course provides a systematic study of concepts, methodologies, models and methods that specifically address problems in the development of distributed software. The topics include architectural design for distributed applications, distributed object models, interface definition languages, concurrent task structuring, modeling for dynamic behavior, and static analysis and debugging for distributed programs.
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3.00 Credits
Prerequisite: CSCI 4401 or consent of department. This course provides an introduction to major topics in mobile computing, including software engineering issues for resource-constrained devices (e.g. cellular phones, palmtops), mobile databases, fault tolerance, service discovery, and wireless networking. The course has substantial theoretical and applied components. Students will be required to develop a non-trivial mobile application and prepare a class presentation on a topic in mobile computing.
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3.00 Credits
Prerequisite: CSCI 4401 or consent of department. A systematic study of concepts, theories, methods and algorithms that specifically address problems in distributed programming. Topics include concurrency, interference, monitors and distributed programming issues, such as: synchronous and asynchronous message passing, remote procedure call, and rendezvous.
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3.00 Credits
Prerequisite: CSCI 4401 or consent of the department. This course will examine models for the analysis of performance of computer systems. Topics include stochastic processes, discrete and continuous Markov chains, queuing models, and stochastic Petri models. These models will be applied to uni- and multiprocessor systems, including crossbar multiprocessor architectures, single- and multi-bus multiprocessors with external and distributed common memory.
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3.00 Credits
Prerequisite CSCI 4401 or consent of department. This course provides an introduction to major topics in fault tolerance and reliability, concentrating on distributed systems. These topics include failure modes, failure detection, logical time systems for distributed systems, N-version programming, checkpointing, optimistic and pessimistic logging schemes, software engineering issues in designing fault tolerant and reliable software, and schemes for reliable communication. Students will be required to develop a non-trivial reliable distributed application and prepare a class presentation on a topic in reliability .
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3.00 Credits
Prerequisite: CSCI 4401. A study of the concepts and design principles used in the construction of distributed computer systems. Topics include architecture and design goals; distributed time management; state and deadlock detection; name resolution; synchronization, mutual exclusion, and communication; collaborating servers; protection and security; error recovery.
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3.00 Credits
Prerequisite: CSCI 4501. Formal definitions and specifications for the semantics of programming languages including lambda-calculus, domain theory, and denotational descriptions of common programming language concepts.
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3.00 Credits
Prerequisite: CSCI 4510 or consent of department. Emphasis will be placed on the implementation of programming languages. Review of lexical, syntactic and semantic analysis. Topics will include code generation, optimization, run-time structures and support, attribute grammars, table-driven code generators, and data flow analysis.
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3.00 Credits
Prerequisite: CSCI 4101 or CSCI 4103 or CSCI 4501 or CSCI 4510 or consent of the department. An introduction to the theory, design and application of visual programming languages. Topics include: basic theory of such languages; overview of existing visual languages and their tools; visual grammars; design of graphical language elements; generalized spreadsheet language; applications and examples.
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3.00 Credits
Prerequisite: CSCI 4525. The area of artificial intelligence is one of the most diverse in the computing field. This course will go indepth into one or more core AI sub-areas, as chosen by the instructor. Example sub-areas of study are machine learning, planning, natural language processing, automated deduction, etc.
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