DEPARTMENT OF COMPUTER SCIENCE
COMPUTER SCIENCE COURSE DESCRIPTIONS
CS 531 Operating Systems. A comprehensive study of computer operating systems. Topics include: computer architecture, concurrent processes, multi-threaded systems, scheduling, memory management, I/O management, fi le systems, networking and the client/server model, distributed systems, and computer security. Prerequisites: CS 362 and 431. Credit 3.
CS 532 Parallel Computing. This course is a study of large-scale parallel processing systems. The central themes are theoretical models, machine architecture, computer algorithms, and programming languages that model, support, describe and implement parallel processing. Prerequisite: CS 584. Credit 3.
CS 533 Microcomputer Interfacing. This course emphasizes real-time and fault-tolerant computing systems. Topics include interrupt processing, real-time programming and scheduling, fault-tolerant architectures and systems, and robotic programming. Extensive programming will be done. Prerequisite: CS 333. Credit 3.
CS 534 Operating System Security.* This course will provide the rationale and necessity for a full range of security concepts and techniques and how to apply them to multiple operating systems. The course will cover methodologies for the design of operating system security and forensic techniques for operating systems. Also covered will be the identification of best practices in the administration, testing and security for operating systems. Prerequisites: DF 531 or CS 531. Credit 3.
CS 536 Software Engineering. This course emphasizes strategies, techniques, and methodologies that deal with the complexity in developing large-scale information systems. Methods for Software engineering methodologies, conventional as well as object-oriented, are discussed. Software measurement and management are discussed. Formal mechanisms for system specifi cation, software development, and project management are introduced. Prerequisite: CS 437. Credit 3.
CS 537 Database Security.* Database security has an immense impact on the design of today's electronic information systems. This course will provide an overview of database security concepts and techniques and discuss new directions of database security in the context of a connected commercial world. This course provides the information needed to develop, deploy and maintain a secure database solution. It exposes the pitfalls of database design, their means of identification and the methods of exploiting vulnerabilities. Prerequisites CS 334, DF 531 or departmental approval. Credit 3.
CS 538 Computer Graphics. A study of modern Computer Graphics programming techniques. Topics include: representations, transformations, and analysis of 2-dimensional and 3-dimensional objects; techniques for hidden surface/edge removal, illumination and shading, volume rendering, animation, and image data compression; and practical experience in graphics software libraries and applications. Prerequisite: CS438. Credit 3.
CS 544 Data Mining and Knowledge Discovery. An introduction into Data Mining and Knowledge Discovery. Topics include discussion of variety of mining techniques. Mining of complex data such as multimedia database, text database, and world-wide-web will be introduced. The applications and trends in data mining will also be discussed. Prerequisite: CS566. Credit 3.
CS 560 Special Topics. Topics and courses are selected to suit individual needs of students. The course may be repeated for additional credit. Prerequisite: Consent of graduate advisor. Credit 3.
CS 561 Programming Practicum. The practicum provides the student an opportunity to develop their programming and analytical skills by applying concepts and techniques learned in organized classes to real world projects under the supervision of faculty and/or supervisory Computer professionals. Prerequisite: Eighteen hours of Computer Science graduate level course work. Student must register for this course every semester the practicum is in progress but only three hours of practicum will apply to the student’s degree plan. Credit 3.
CS 562 Computer Architecture and Organization. An introduction into Computer Architecture and Organization. Topics include computer evolution and performance issues, the computer systems including system buses, internal and external memory, input/output, and operating system support, CPU issues including computer arithmetic, instruction sets, addressing modes, RISC and superscalar organization, control unit issues, microprogramming, and parallel organization. Prerequisites: CS 333 and CS 431. Credit 3.
CS 563 Networks and Data Communications. An introduction to the basic techniques for interconnecting computers and peripherals for decentralized Computer. Network components, digital communications, interconnection architectures, communications protocols for geographic and local area networks and interprocess communications are covered. Prerequisite: CS 463. Credit 3.
CS 564 Programming Languages. A comprehensive study of computer programming languages. Topics include: language design principles, formal grammars, procedural operating environment, language standardization, and language support for parallel and distributed programming. Language paradigms to be discussed will include procedural programming, logical programming, functional programming, and object-oriented programming. Prerequisite: CS 482. Credit 3.
CS 566 Database Systems. A survey of contemporary topics in database systems. Topics include: relational database theory, database design issues, cryptography, security integrity issues, data recovery, concurrency problems, optimization, distributed database systems, the client/server model, object-oriented databases, stenography, data compression, data warehouse, data mining, logic/knowledge based systems, and other related topics. Prerequisite: CS 334. Credit 3.
CS 568 Cryptography and Steganography.* This course is designed to cover the theoretical and practical aspects of cryptography and steganography including specification, design, and programming. Topics include digital signatures, symmetric and asymmetric (public key) algorithms, hash functions, cryptographic algorithms, cost to break algorithms including key safety, Diffie-Hellmann, RSA, key stores, Secure Socket Layers, Virtual Private Networks (VPN), Certificate Authorities, and important cryptanalysis and stegananalysis strategies. Prerequisites DF 561 or departmental approval. Credit 3.
CS 572 Artificial Intelligence. (Prior to Fall 2006 this course was CS 582.)A survey of topics in artificial intelligence. Topics include: history of AI, knowledge representation, knowledge acquisition, search techniques, control strategies, and AI languages. Applications include natural language processing, neural nets, and expert systems. Prerequisite: CS 362. Credit 3.
CS 573 Neural Networks. (Prior to Fall 2006 this course was CS 583.) An introduction into Neural Networks. Topics include discussion of variety of standard neural networks, with architecture, training algorithm, and applications; and development of neural network expert systems. Prerequisite: CS 362. Credit 3.
CS 574 Data Structures. (Prior to Fall 2006 this course was CS 584.) A number of important concepts and algorithms, with emphasis on correctness and effi ciency, are reviewed. The advanced treatment of sorting, searching, hashing, and dynamic storage management is provided. Advanced data structures, such as advanced tree structures, graphs, and networks, are introduced. Applications to distributed file structures, database management systems, internet/intronetworks are covered. Prerequisite: CS 362. Credit 3.
CS 582 Artificial Intelligence. (Effective Fall 2006 this course will be CS 572.) A survey of topics in artificial intelligence. Topics include: history of AI, knowledge representation, knowledge acquisition, search techniques, control strategies, and AI languages. Applications include natural language processing, neural nets, and expert systems. Prerequisite: CS 362. Credit 3.
CS 583 Neural Networks. (Effective Fall 2006 this course will be CS 573.) An introduction into Neural Networks. Topics include discussion of variety of standard neural networks, with architecture, training algorithm, and applications; and development of neural network expert systems. Prerequisite: CS 362. Credit 3.
CS 584 Data Structures. (Effective Fall 2006 this course will be CS 574.) A number of important concepts and algorithms, with emphasis on correctness and effi ciency, are reviewed. The advanced treatment of sorting, searching, hashing, and dynamic storage management is provided. Advanced data structures, such as advanced tree structures, graphs, and networks, are introduced. Applications to distributed file structures, database management systems, internet/intronetworks are covered. Prerequisite: CS 362. Credit 3.
CS 583 Educational Multimedia.* This course explores the uses of multimedia in the classroom and extends the teachers skill base in the development of appropriate multimedia examples to support and enhance the middle school and high school curricula. Throughout the course students will gain experience in still and motion digital editing, audio and animation production. This course may not be counted toward the M.S. in Computer Science, Information Assurance and Security or Digital Forensics. Prerequisite: Graduate standing. Credit 3.
CS 585 Critical Analysis of Instructional Software.* This course examines the instructional and educational value of commercially available software for the pre-k through 12th grade. The course builds upon a foundation of instructional theory to identify appropriate characteristics of instructional software and explores the effectiveness of instructional software in the classroom. This course may not be counted toward the M.S. in Computer Science, Information Assurance and Security or Digital Forensics. Prerequisites: CS 583. Credit 3.
CS 587 Designing Instructional Materials for the Web.* This course examines the development of web sites for instructional purposes. The course looks at the systematic design of instruction, a process that examines the development of appropriate course goals, the identification of measurable objectives that meet those goals and intelligent approaches to assessing student performance. This design approach is then applied to the development of web-based materials, providing opportunities for skills acquisition in a variety of multimedia applications and their incorporation into a web site. The course culminates in the development of a geometry web site for use in schools. This course may not be counted toward the M.S. in Computer Science, Information Assurance and Security or Digital Forensics. Prerequisites: CS 585. Credit 3.
CS 589 Development of Technology Infrastruction in School.* This course examines the funding, design and implementation processes required to establish and realize a coherent technology acquisition and management strategy. This course may not be counted toward the M.S. in Computer Science, Information Assurance and Security or Digital Forensics. Prerequisites: Graduate standing. Credit 3.
CS 593 Modeling Theory. This course is a study of the use of analytical models as aids in the formulation and resolution of system alternatives. Emphasis is on problem definition, formulation and resolution using appropriate mathematical methodologies and analysis software packages. Prerequisites: MTH 379 and CS 477. Credit: 3.
CS 661 Network Security II.* This course extends the practical skills and basic concepts provided in Network Security I to provide experience and skills in intrusion detection, management and prevention alongside the theoretical and conceptual basis for secure communication and perimeter defense in depth. The course explores the capabilities and limitations of 'best practices' approaches to network security together with significant case studies to provide the commercial an industrial context for the network security professional. Prerequisites: DF 561. Credit 3.
CS 694 Numerical Analysis. Topics include solutions of equations, approximation and interpolation, numerical differentiation and integration, the fast Fourier transform, and numerical simulation. Also listed as MTH 694. Prerequisite: MTH/CS 394. Credit 3.
CS 698, 699 Thesis. Credit 3 hours for each course.
* Subject to action by the Texas Higher Education Coordinating Board.