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CS 360: Systems Programming
3.00 Credits
Minnesota State University-Mankato
This course focuses on machine level I/O and operating system fi le processing. Structure of systems programs including assemblers, linkers, and object-oriented utilities and interfaces. Students will gain experience in writing utility programs and extensions to an operating system. Pre: CS 111 or EE 107, and CS 320 Fall
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CS 360 - Systems Programming
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CS 361: Windows Programming
3.00 Credits
Minnesota State University-Mankato
This course introduces the student to Windows programming in C++ using the Application Programming Interface. Windows programs are created in a visual development environment which includes editing and code generating facilities. Hands-on programming skills are developed in the lab. Pre: CS 210 Variable
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CS 361 - Windows Programming
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CS 370: Concepts of Programming Languages
3.00 Credits
Minnesota State University-Mankato
Fundamental concepts of programming languages, including principles of language design, language constructs, and comparison of major languages. Topics: formal methods of examining syntax and semantics of languages and lexical analysis of language components and constructs, and propositional and predicate calculi. Pre: CS 210 Fall
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CS 370 - Concepts of Programming Languages
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CS 380: Analysis and Design of Software Systems
3.00 Credits
Minnesota State University-Mankato
Students are introduced to techniques used in analysis and design of software systems. Traditional techniques are reviewed and current methodologies for both object-oriented and procedural systems are studied. Standard notations used to document software requirements and designs are presented. Pre: CS 300 Spring
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CS 380 - Analysis and Design of Software Systems
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CS 400: Software Design and Architecture
3.00 Credits
Minnesota State University-Mankato
Current processes, methods and tools related to formal methods for modeling and designing software systems. Topics include software architectures, methodoligies, model representations, component-based design, patterns, frameworks, CASE-based designs, and case studies. Pre: CS 300 and MATH 121 Variable
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CS 400 - Software Design and Architecture
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CS 410: Formal Languages/Abstract Machines
3.00 Credits
Minnesota State University-Mankato
This course studies the theoretical underpinnings of modern computer science, focusing on three main models of computation: DFA, PDA, and Turing Machines. Students determine model capabilities and limitations: what is and is not computable by each of them. Pre: CS 310 and MATH 375 Fall
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CS 410 - Formal Languages/Abstract Machines
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CS 415: High Performance Computing
3.00 Credits
Minnesota State University-Mankato
High Performance Computing techniques used to address problems in computational science. Topics include application areas and basic concepts of parallel computing, hardware design of modern HPC platforms and parallel programming models, methods of measuring and characterizing serial and parallel performance. Pre: CS 310, CS 350, and MATH 247 Variable
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CS 415 - High Performance Computing
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CS 420: Advanced Computer Architecture
3.00 Credits
Minnesota State University-Mankato
This course addresses advanced topics in computer architecture including a major emphasis on measuring and improving computer performance. Topics include advances in pipelining and analysis and optimization of storage systems and networks, multiprocessor challenges and trends. Pre: CS 320 and MATH 375 Variable
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CS 420 - Advanced Computer Architecture
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CS 425: Real-time and Embedded Systems
3.00 Credits
Minnesota State University-Mankato
This course provides an overview of embedded and real-time systems including design principles, methodologies, design tools and problem solving techniques. Students design and build a real-time operation system with a microprocessor to host real-time service data processing using sensor/actuator devices. Pre: CS 210 and CS 320 Variable
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CS 425 - Real-time and Embedded Systems
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CS 430: Artifi cial Intelligence
3.00 Credits
Minnesota State University-Mankato
Basic introductory concepts and a history of the fi eld of Artifi cial Intelligence (AI) are covered. Emphasis is placed on the knowledge representation and reasoning strategies used for AI problem solving. Solutions are found using the LISP programming language. Pre: CS 210 or CS 230 Fall-Alt
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CS 430 - Artifi cial Intelligence
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