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Course Criteria
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3.00 Credits
Credits: 3 Cross-Listed with CSI 701 Covers mapping of mathematical models to computer software, including all aspects of developing scientific software such as architecture, data structures, advanced numerical algorithms, languages, documentation, optimization, validation, verification, and software reuse. Examples in bioinformatics, computational biology, computational physics, and global change demonstrate scientific advances enabled by computation. Class projects involve working in teams to develop software that implements mathematical models, using software to address important scientific questions, and conducting computational experiments with it. Prerequisites CS 735 or equivalent. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with CS 815 Topics illustrating contemporary thinking on architectures, application, development environments, algorithms, operating system related issues, language requirements, and performance for parallel computation. Prerequisites CS 635 or CSI 801. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with CS 817 Study of adaptive and competitive principles using distributed and parallel computation. Topics include background from statistics, control, adaptive signal processing, and neurosciences. Basic models, such as those suggested by Grossberg, Hopfield, and Kohonen, are discussed in terms of analytical characteristics and applications. Neural networks assessed as universal approximators. Presents connections to fuzzy approach established through radial basis function approach. Presents applications to perception, knowledge-based systems, and robotics. Prerequisites CS 688, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Cross-Listed with CS 818 Discussion of current research topics in computer systems. Topics vary according to faculty interest. Possible topics include peer-to-peer computing, high-performance distributed computing, sensor and ad hoc networks, autonomic computing, virtualization, and web services and middleware.
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3.00 Credits
Credits: 3 Graphical models for encoding conditional independence assumptions in a multivariate discrete probability distribution. Includes computational methods for updating probabilities when evidence is observed on some variables in model. Algorithms for finding most probable instantiation of network. Applications in expert systems and decision analysis. Prerequisites SYST 664 or 652 Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Study of application of software engineering principles, design methods, and support tools through reallife problems extracted from faculty and industry projects. Prerequisites SWE 621 Notes May be repeated with change in topic. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with CS 732 Perfective maintenance, reuse of software components and patterns, evolving software systems, principles of object-oriented analysis and development. Presents issues regarding technologies supporting perfective software maintenance and reuse. Prerequisites CS/SWE 621 or equivalent, data structures, principles of modern programming, and discrete mathematics; or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Study of software for systems in which failure can be catastrophic. Presents techniques to construct and analyze software for critical applications and examination of inherent limitations of such techniques, and interaction between techniques used during development and behavior of software during operation. Topics include tolerance of software faults, design redundancy, data redundancy, software safety, formal methods, statistical testing, design for analyzability, and design for testability. Prerequisites SWE 620 and STAT 554 Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Different methods for analyzing software, primarily for purpose of testing. Analysis techniques, specific algorithms, tools, and applications. Goals are to explore current research issues, learn how to build software analysis tools, and understand how these techniques can be applied to software development activities. Focuses on applications for testing software, including automatic test data generation, objectoriented testing, and testing client-server applications. Also considers analysis techniques for other software-related activities such as maintenance, reuse, object-oriented development, metrics, and optimization. Prerequisites CS 540 or CS/SWE 637, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with SWE 825 Advanced topics in specifying, designing, modeling, developing, deploying, testing, and maintaining software written as web applications and web services. Prerequisites SWE 642 Software Engineering for the World Wide Web. Notes May be repeated with change in topic. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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