DEPARTMENT OF MATHEMATICAL AND
INFORMATION SCIENCES
Computing Science Program
The graduate program in Computing Science provides current, advanced training for students preparing for professional employment or further study at the doctoral level. Computing and Information Science may be selected as the major for the Master of Science degree; also available is the Master of Education, Plan II when Computing Science is selected as a teaching field. Computing Science may also be selected as a minor for MS and MA degrees in related areas.
Admission Requirements
Students seeking admission to the graduate program in Computing Science must, under normal circumstances, meet the basic requirements of Graduate Studies specified in the Graduate Catalogue. In addition the following are required:
1. A combined Verbal + Quantitative GRE score of 1000,
2. At least two letters of recommendation that address qualifications for graduate study.
Graduate study in Computing Science is accessible both to students who have completed undergraduate Computing Science majors or minors and to those with baccalaureate degrees in related fields with the equivalent of a Computing Science minor in formal course work or professional experience. As a minimum, candidates are expected to present a background comparable to that provided in CS 164, 165, 334, 364, 431, 474, MTH 299, MTH 379 as described in the undergraduate catalogue of Sam Houston State University. Applicants with less preparation will be required to complete additional stem work as part of the graduate program. A 3.0 undergraduate grade point average, both overall and in Computing Science courses, is required.
All courses presented as stem work must be completed with a grade of B or higher.
Both Plan I and Plan II of the Master of Science Degree are available. (See the General Information section of this catalogue for general requirements.) The graduate advisor will review each applicant's background and assist in developing individual study plans including any required stem work. Selection of a minor and the choice of electives must be approved by the Computing Science Coordinator to ensure a properly balanced program.
The oral comprehensive examination, required by the University of all master's degree candidates, will be administered by a committee consisting of faculty from the Computing Science Program, a member from the minor area, if any, and a representative from the College of Arts and Sciences. This committee is appointed by the Dean of the College of Arts and Sciences based upon recommendations from the Computing Science Coordinator. Students must submit a request for scheduling the oral examination to the Computing Science Coordinator at least 4 weeks prior to the desired date for the examination.
Master of Science Plans I and II.
Common Requirements:
1. An 18-hour core consisting of CS 531, 536, 561, 564, 566, and 584.
2. An oral examination over Computing Science courses included in the individual degree plan.
3. An oral presentation of the student's practicum project.
4. 6 semester hours of approved Computing Science courses.
Additional Requirements:
1. Plan I must include a 12-semester hour minor in a field approved by the Coordinator of Computing Science. Plan I may only be chosen if the student's plan of study provides for a minimum of 48 semester hours (total graduate and undergraduate) in Computing Science or the student has extensive professional experience in computing science.
2. Plan II must include 12 additional semester hours of approved Computing Science courses.
SENIOR COURSES OPEN TO GRADUATE STUDENTS
| Language Translators | |
| Computer Operating Systems | |
| Software Engineering | |
| Data Structures | |
| Simulation |
COMPUTING 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, file systems, networking and the client/server model, distributed systems, and computer security. Prerequisite: CS 431 and 474.
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 431
CS 533 MICROCOMPUTER INTERFACING. Emphasizes real-time programming techniques useful in interfacing digital systems to an analog environment. Topics include interrupt processing, serial and parallel input/output, digital to analog and analog to digital conversions, handshaking, and interface protocols and standards. Extensive programming will be done. Prerequisites: CS 333.
CS 536 STRUCTURED SYSTEMS DESIGN. 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 specification, software development, and project management are introduced. Prerequisite: CS 437.
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.
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 computing professionals. Prerequisite: Eighteen hours of graduate level CS. 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.
CS 563 NETWORKS AND DATA COMMUNICATIONS. An introduction to the basic techniques for interconnecting computers and peripherals for decentralized computing. Network components, digital communications, interconnection architectures, communications protocols for geographic and local area networks and interprocess communications are covered. Prerequisite: CS 463.
CS 564 PROGRAMMING LANGUAGES. A comprehensive study of computer programming languages. Topics include: language design principles, formal grammars, control structures, procedure operating environment, and language standardization. Language paradigms to be discussed will include procedural programming, logical programming, functional programming, and object-oriented programming. Prerequisite: CS 364.
CS 566 ADVANCED DATABASE SYSTEMS. A survey of contemporary topics in database systems. Topics include: relational database theory, database design issues, secondary storage considerations, security and integrity issues, data recovery, concurrency problems, optimization, distributed database systems, the client/server model, object-oriented databases, logic/knowledge based systems, and other related topics. Prerequisites: CS 334.
CS 582 ADVANCED PROGRAMMING CONCEPTS. 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. Prerequisites: CS 474.
CS 584 ADVANCED DATA STRUCTURES. A number of important concepts and algorithms, with emphasis on correctness and efficiency, 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. Prerequisites: CS 474.
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.
CS 594 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 594. Prerequisite: MTH/CS 394.