Course Search Results

• CPSC 8220: Case Study in Operating Sys

  3.00 Credits

  Clemson University

  
  Case study of the design of an operating system. Class periods are devoted to reviewing source code and deducing the structure of the system. Lab exercises require students to make major changes to the system to enhance its performance on particular workloads. Students are expected to have completed coursework in operating systems before enrolling in this course. Coreq: CPSC 8221.
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• CPSC 8221: Case Study in Operatng Sys Lab

  0.00 Credits

  Clemson University

  
  Non-credit laboratory to accompany CPSC 8220. Coreq: CPSC 8220.
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• CPSC 8230: Intro to Quantum Computing

  3.00 Credits

  Clemson University

  
  This course covers a wide range of topics in quantum computing from the basics, such as quantum information framework, computation model, measurements, quantum algorithms, and computational complexity theory, to state of the art research, such as entropy and noiseless coding, quantum error-correcting and fault-tolerance, and quantum machine learning. Students use quantum computers for assignments and projects. Students are expected to have completed a linear algebra course and have familiarity with linear algebra concepts such as unitary and Hermitian matrices over complex numbers before enrolling in this course. Also, students should have successfully completed at least one college-level statistics and probability course before enrolling in this course.
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• CPSC 8240: Advanced Operating Systems

  3.00 Credits

  Clemson University

  
  Recent trends in system design and implementation; operating system structures to support reliable secure systems; verification techniques; fault tolerant systems; operating system considerations for closely coupled multiprocessor systems; network operating systems. Students are expected to have completed coursework in operating systems before enrolling in this course.
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• CPSC 8270: Translation of Progr Languages

  3.00 Credits

  Clemson University

  
  Theoretical foundations and algorithms for compiling and interpreting programming languages. Topics include lexical analysis, syntactic analysis, semantics analysis, optimization and code generation. Implementation of a compiler or a major component of a compiler is normally a term project. Students are expected to have completed coursework in formal language theory and survey of programming languages before enrolling in this course.
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• CPSC 8280: Theory of Program. Languages

  3.00 Credits

  Clemson University

  
  Syntax and semantics of programming languages; finite state and pushdown processors; context-free models of syntax; parsing algorithms and semantic models. Students are expected to have completed coursework in formal language theory and survey of programming languages before enrolling in this course.
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• CPSC 8290: Advanced Compiler Topics

  3.00 Credits

  Clemson University

  
  Code generation, register allocation, program optimization, data flow, interprocedural operations, parallel compilation and distributed compilation. Preq: CPSC 8270.
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• CPSC 8380: Adv Data Structures

  3.00 Credits

  Clemson University

  
  Search trees; data structures for sets; index structures for data bases; data abstraction and automated implementation; implicit data structures; storage compaction of lists; data structures for decision trees; data structures in areas such as computer graphics, artificial intelligence, picture processing and simulation.
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• CPSC 8390: Theoretical Cp Sci Foundations

  3.00 Credits

  Clemson University

  
  Preparation for the study of advanced issues in computational complexity, algorithm correctness and inherent limits to computing; set theory and proof techniques; classes of the Chomsky hierarchy. Students are expected to have completed coursework in formal languages and automata before enrolling in this course.
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• CPSC 8400: Design & Anlys of Algorithms

  3.00 Credits

  Clemson University

  
  Basic techniques for design and analysis of algorithms; models and techniques for obtaining upper and lower time and space bounds; time/space trade-offs; inherently difficult problems. Students are expected to have completed coursework in discrete mathematics before enrolling in this course.
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