Computer Science, MS
The Master of Science with a major in Computer Science is designed to prepare graduate professionals who can apply the necessary knowledge of computing to information requirements of organizations in business, government, industry and education. The program provides for the education of individuals who will develop, maintain, or manage complex computer-based information systems.
The program provides the experienced professional with up-to-date specialized knowledge while developing those analytical skills necessary to stay abreast of the changing field of computing. The program also provides the recent baccalaureate graduate with additional applied and advanced knowledge, thus facilitating a more useful contribution to his/her career path.
Fast Track Computer Science BS to Computer Science MS
The university allows the opportunity for high-achieving undergraduate students to count a select number of graduate credits toward their undergraduate degree and thereby obtain a graduate degree at an accelerated pace. Students interested in the Fast Track in Computer Science should see the undergraduate catalog.
Prepare students to pursue careers in industry, academia, and government by offering a state of the art curriculum and advanced knowledge.
Student Learning Outcomes
At the time of graduation students will attain:
- the ability for effective oral and written communication of complex ideas to diverse audiences, and
- skills to efficiently solve complex problems from various domains with computers, and
- the ability to comprehend and apply state-of-the-art in the field, and
- an understanding of professional, ethical, legal, and security issues and responsibilities, and the societal impact of computing.
Chronological Procedure Leading to the MS Degree
- Completion of a degree plan
Upon admission to the MS degree program in computer science, and prior to enrollment in any course, the student must contact the Graduate Academic Advisor in the College of Science & Engineering to have a degree plan completed. The student will then be assigned a faculty advisor from the computer science faculty. Students should seek the advice of their faculty advisor on a regular basis about their progress toward their degree.
- Progress toward the degree
Once admitted to the graduate degree program in computer science, a student must complete at least six semester hours of credit per year toward the degree until the degree is completed. Failure to make this minimum progress will result in dismissal from the degree program with possible readmission based on the catalog in effect at the time of readmission. A student who is actively pursuing a graduate project or thesis and has completed all other course work for the degree will be given relief from this requirement, but must register continuously for the project or thesis until it is completed.
- Thesis or Courses Only
Students choosing the thesis option must obtain permission from their faculty advisor (who will chair their committee) to register for COSC 5398 Thesis I (3 sch), which should be taken in the next to last semester. During the first month of Thesis I, the student and their advisor should determine the thesis committee. This committee consists of at least three full-time Texas A&M University-Corpus Christi graduate faculty members, two of which must be in computer science.
While taking Thesis I, the student will develop a written proposal of the thesis work and present the proposal for approval. Upon approval, the student may then register for COSC 5399 Thesis II (3 sch). The student must then continually register for COSC 5399 Thesis II (3 sch) until completion of their thesis. If the student fails to register for COSC 5399 Thesis II (3 sch) or fails their final examination, a grade of No Credit will be assigned to COSC 5398 Thesis I (3 sch) and all COSC 5399 Thesis II (3 sch) courses and the student must begin the process again.
While taking COSC 5399 Thesis II (3 sch), the student will produce a written thesis that discusses their work. A draft copy of the thesis will be given to all committee members and the student will make any changes required by the committee. Upon approval of the thesis committee chair, the student may schedule their final oral examination. The thesis will be published and archived in the Mary & Jeff Bell library. Guidelines for writing the thesis are available in the Computer Science office.
Course Only Option
Students must take all required courses along with their chosen electives with at least two courses from each elective group. COSC 6370 Advanced Software Engineering (3 sch) is taken in the final semester.
- Final examination (Thesis Option)
After the student has completed all other requirements for the MS degree in computer science, he or she must schedule an oral exam over his/her graduate program of study. The oral exam will be administered by the graduate thesis committee and will focus heavily on the thesis itself.
For Additional Information
Center for Instruction, Room 301
Phone: (361) 825-2474
Computer Science Program, Unit 5825
College of Science and Engineering
Texas A&M University-Corpus Christi
6300 Ocean Drive
Corpus Christi, Texas 78412-5825
- In addition to meeting all University requirements, students seeking admission to the graduate degree program in computer science must submit the following to the Office of Research and Graduate Studies:
- An application and application fee
- Transcripts from regionally accredited institutions (international students will be required to submit relevant international transcripts)
- An essay (500-1000 words) discussing why you wish to get a Master’s degree and your areas of interest
- GRE scores (within five years of the date of application)
- International students must show English language proficiency through either TOEFL or IELTS exam and additional documents to the College of Graduate Studies. see http://gradschool.tamucc.edu/international.htm for full requirements
- A student entering the program is expected to have adequate preparation in computer science and mathematics from their undergraduate degree. For computer science, this preparation must include successful completion of coursework in data structures, a high level programming language, computer architecture, operating systems, and software engineering. In mathematics, students must have successfully completed course work in discrete mathematics, calculus, plus one additional junior level or higher mathematics course such as linear algebra, numerical analysis, or applied probability and statistics.
Students who have not successfully completed the above courses may be required to take leveling courses in any missing subjects. All leveling courses must be completed with a grade of “B” or better. In addition, students can take no more than 9 credits towards their degree prior to completing all leveling courses.
- Students seeking admission to the Computer Science MS program have to identify a faculty member willing to serve as their graduate faculty advisor. Applicants can submit their interests at portal.cs.tamucc.edu after they have applied, accounts may take up to two weeks to be created after applying. Applicants will not be admitted to the program without a graduate advisor.
Requirements for the Master of Science in Computer Science degree may be met through one of two options: Thesis Option (Option I) or Course Only Option (Option II). The Thesis Option requires a minimum of 30 credit hours and the Course Only Option requires a minimum of 36 credit hours. The Thesis Option allows for maximum flexibility in choosing elective courses. This option allows the student to concentrate on a particular field or area of computer science. The Course Only Option allows for flexibility in choosing elective courses but requires the student to take at least two electives from each of the three elective concentration tracks. The concentration tracks are Software and Programming, Data Sciences, and Cyber Science.
|COSC 6334||Design and Analysis of Algorithms||3|
|COSC 6351||Advanced Computer Architecture||3|
|COSC 6352||Advanced Operating Systems||3|
|Thesis or Course Option|
|Select one of the following options:||21-27|
|Option 1 - Thesis|
Select a minimum of 12 hours of electives to support thesis
|Research Methods in Computer Science|
Select electives that will support the student’s thesis
|Option II - Course|
Select a minimum of 24 hours, with at least 6 credits hours from each concentration track
|Advanced Software Engineering (Must be taken in last semester) ^|
Select electives across different areas of computer science, and must take at least two courses from each of the concentration tracks
|Software and Programming|
|Compiler Design and Construction|
|Theory of Computation|
|Mobile Software Development|
|Current Trends in Programming|
|Digital Image Processing|
|Introduction to Computer Graphics|
|Advanced Computer Graphics|
|Database Management Systems|
|Advanced Topics in DBMS|
|Artificial Intelligence ^|
|Data Communications and Networking|
|Wireless Sensor Networks|
|Computer Forensics ^|
|Information Assurance ^|
|Network Security ^|
|Advanced Information Assurance ^|
Electives are chosen by the student but are subject to approval by the student’s graduate faculty advisor. For the Thesis Option, electives should be taken that will support the student’s thesis. For the Course Only Option, students must obtain breadth by taking electives across different areas of computer science, and must take at least two courses from each of the concentration tracks. Electives not listed in the concentration tracks may also be taken to fulfill remaining credit hours.
No more than six hours of approved electives may come from courses taken at another university or from outside of computer science. Credit from a master’s degree earned at another institution will not be applied to a second master’s degree at Texas A&M University-Corpus Christi. A maximum of six hours of approved Directed Independent Study may count toward the MS degree.
THIS COURSE INTRODUCES STUDENTS TO THE LEVELING TOPICS IN COMPUTER SCIENCE. THIS COURSE SERVES THE NEEDS OF CERTAIN TOPICS STUDENTS LACK FOR PURSUING A MASTER'S DEGREE IN COMPUTER SCIENCE. GRADE ASSIGNED WILL BE "CREDIT" (CR) OR "NO CREDIT" (NC).
A STUDY OF INTERNAL COMPUTER CONCEPTS WITH RESPECT TO THE FUNCTIONING OF THE HARDWARE SUBSYSTEMS AND THEIR ROLES IN THE COMPUTING PROCESS. AN IN-DEPTH STUDY OF MACHINE AND ASSEMBLY LANGUAGE. (DOES NOT COUNT TOWARD TOTAL HOURS REQUIRED FOR MS IN COMPUTER SCIENCE.)
PROVIDES A BROAD INTRODUCTION TO THE DEVELOPMENT OF COMPUTER-BASED LEARNING ENVIRONMENTS. COVERS THE THEORY AND PRACTICE OF USING THE COMPUTER BOTH IN THE CLASSROOM AND INDIVIDUALLY FOR LEARNING. COVERS A WIDE RANGE OF POSSIBILITIES FROM MULTIMEDIA PRESENTATION OF MATERIAL TO CONSTRUCTIVE ENVIRONMENTS AND COMPUTER-BASED INSTRUCTIONAL SYSTEMS.
A STUDY OF THE LOGICAL STRUCTURES USED FOR THE ORGANIZATION, STORAGE AND RETRIEVAL OF DATA. THESE STRUCTURES ARE ADDRESSED FROM BOTH MEMORY-RESIDENT AND FILE-RESIDENT POINTS OF VIEW. ALGORITHMS FOR THE CREATION, SEARCHING, AND MANIPULATION OF STANDARD DATA STRUCTURES USED IN COMPUTING ARE STRESSED. (DOES NOT COUNT TOWARD TOTAL HOURS REQUIRED FOR MS IN COMPUTER SCIENCE.)
Prerequisite: COSC 5324.
INTRODUCTION TO COMPUTER GRAPHICS This graduate course provides students with a foundation in basic principles and techniques for computer graphics on modern graphics hardware. Students will gain experience in interactive computer graphics using the OpenGL API. Topics include: graphics hardware, rendering, perspective, lighting, and geometry.
This course covers advanced computer graphics techniques. Students will be introduced to state-of-the-art methods in computer graphics. This course will focus on techniques for real-time rendering and animation.
INTRODUCTION TO OPERATING SYSTEMS CONCEPTS, PRINCIPLES, AND DESIGN. TOPICS INCLUDE: PROCESSES AND THREADS, CPU SCHEDULING, MUTUAL EXCLUSION AND SYNCHRONIZATION, DEADLOCK, MEMORY MANAGEMENT, FILE SYSTEMS, SECURITY AND PROTECTION, NETWORKING, AND DISTRIBUTED SYSTEMS. SELECTED EXISTING OPERATING SYSTEMS ARE DISCUSSED, COMPARED, AND CONTRASTED. (DOES NOT COUNT TOWARD TOTAL HOURS REQUIRED FOR MS IN COMPUTER SCIENCE.)
Prerequisite: COSC 5313.
An advanced course that concentrates on the design and analysis of algorithms used to solve a variety of problems. The methods of design covered include such topics as: divide-and-conquer, the greedy method, dynamic programming, search and traversal techniques, and backtracking.
A study of contemporary database management concepts. Performance (indexing, query optimization, update optimization), concurrency, security and recovery issues are discussed. Also includes the study of front-end environments that access the database.
Prerequisite: COSC 5335 and 5321.
Graduate-level survey of the field of Human-Computer Interaction (HCI) focusing on design strategies for making software usable by real-world people for doing real-world work. Topics include the role of HCI in the software product life cycle, task analysis of the user's work, architectures for human-computer dialogues, new and traditional approaches to user interface design, and user interface standards.
The study of emerging database technologies. Topics are chosen from data warehousing, distributed databases, spatial databases and web-based applications.
Prerequisite: COSC 5336.
COMPUTER ARCHITECTURE An overview of computer architecture, which stresses the underlying design principles and the impact of these principles on computer performance. General topics include design methodology, processor design, control design, memory organization, system organization, and parallel processing.
Introduction to advanced concepts in operating systems and distributed systems. Topics include distributed system architectures, interprocess communication, distributed mutual exclusion, distributed synchronization and deadlock, agreement protocols, distributed scheduling and process management, distributed shared memory, distributed file systems, multiprocessor system architectures and operating systems, recovery and fault tolerance.
COMPILER DESIGN AND CONSTRUCTION This course introduces the basic concepts and mechanisms traditionally employed in language translators, with emphasis on compilers. Topics include strategies for syntactic and semantic analysis, techniques of code optimization and approaches toward code generation.
Prerequisite: COSC 5330 and MATH 2305.
Fundamental concepts and techniques for the design of computer-based, intelligent systems. Topics include: a brief history, methods for knowledge representation, heuristic search techniques, programming in LISP or Prolog.
DATA COMMUNICATION SYSTEMS Areas studied include principles of computer-based communication systems, analysis and design of computer networks, and distributed data processing.
THEORETICAL ASPECTS OF COMPUTING An introduction to theoretical foundations of modern computing. Topics include finite state machine concepts, formal grammars, and basic computability concepts.
This is a graduate level course on wireless sensor networks; one of the fastest developing areas in computer science and engineering. The focus of this course is on the design of optimized architectures and protocols for such unique networks. Topics include the design principles of wireless sensor networks, energy management, MAC protocols, naming and addressing, localization, routing protocols, applications of wireless sensor networks, and associated challenges and measures.
PARALLEL COMPUTING Introduction to the hardware and software issues in parallel computing. Topics include motivation and history, parallel architectures, parallel algorithm design, and parallel performance analysis. Students will be introduced to a variety of parallel computing paradigms including message passing systems and shared memory systems.
Survey of software development on mobile platforms including both native and cross-platform applications with topics such as: prototyping, programming, testing, debugging, and deploying. Coverage of software life cycle on mobile platforms and how mobile hardware differs from traditional computers. COSC 5321
Areas studied include engineering principles and their application to the design, development, testing, and maintenance of large software systems, tools and processes for managing the complexities inherent in creating and maintaining large software systems.
This course will introduce students to the fundamentals of computer forensics and various software tools used in cyber-crime analysis. Students will be introduced to established methodologies for conducting computer forensic investigations, as well as to emerging international standards for computer forensics. Applicable laws and regulations dealing with computer forensic analysis will also be discussed.
Prerequisite: COSC 5312.
An introduction to information security and assurance. This course covers the basic notions of confidentiality, integrity, availability, authentication models, protection models, secure programming, audit, intrusion detection and response, operational security issues, physical security issues, personnel security, policy formation and enforcement, access controls, information flow, legal and social issues, classification, trust modeling, and risk assessment.
Prerequisite: COSC 5312.
This course is a study of networking basics and security essentials with respect to information services provided over a computer network. The course covers the technical details of security threats, vulnerabilities, attacks, policies, and countermeasures such as firewalls, honeypots, intrusion detection systems, and cryptographic algorithms for confidentiality and authentication and the development of strategies to protect information services and resources accessible on a computer network.
Prerequisite: COSC 5375.
This course includes an introduction to cryptographic algorithms and protocols for encrypting information securely, techniques for analyzing vulnerabilities of protocols, approaches to digital signatures and information digests, and implementation approaches for the most significant cryptographic methodologies.
Prerequisite: COSC 5312.
This course encompasses a broad range of topics involving information security, communications security, network security, risk analysis, operational security, health information privacy, criminal justice digital forensics, homeland security, the human element and social engineering, and applicable national and international laws. An in-depth information assurance capstone project or research paper will be required of each student to satisfy the information assurance graduate option requirements.
Prerequisite: COSC 5375.
INDIVIDUAL CONTRACT AGREEMENT INVOLVING STUDENT, FACULTY, AND COOPERATING AGENCY (DISCIPLINE-RELATED BUSINESS, NONPROFIT ORGANIZATION, OR GOVERNMENT AGENCY) TO GAIN PRACTICAL EXPERIENCE APPROPRIATE TO COMPUTER SCIENCE IN OFF-CAMPUS SETTING. GRADE ASSIGNED WILL BE "CREDIT" (CR) OR "NO CREDIT" (NC).
RESEARCH METHODS IN COMPUTER SCIENCE This course provides students with a range of experiences in conducting and communicating research. Students will learn major research methods and techniques. Experiences will be gained in all stages of research: reviewing literature, writing a proposal, designing an approach, and reporting results. Critical-reading/writing assignments and class discussions on state-of-the-art research in Computer Science will provide students with major research aspects. Fall, Spring
AN APPLIED RESEARCH PROJECT IN COMPUTING FROM PROBLEM DEFINITION TO IMPLEMENTATION IN AN AREA OF PARTICULAR INTEREST TO THE STUDENT THAT RELATES TO THE COURSE OF STUDY.
Study in areas of current interest. (A maximum of six hours may be counted toward the MS degree.) Fall, Spring, Summer.
THIS COURSE IS FOR COMPUTER SCIENCE MS STUDENTS CHOOSING THE THESIS OPTION. UPON CHOOSING A THESIS ADVISOR, STUDENTS WILL REGISTER FOR THIS COURSE. THIS COURSE IS ONLY CREDIT/NO CREDIT. STUDENTS WILL BE GIVEN A GRADE OF IN-PROGRESS UNTIL SUCCESSFULLY COMPLETING THEIR THESIS.
Prerequisite: COSC 6393.
THIS COURSE IS FOR COMPUTER SCIENCE MS STUDENTS CHOOSING THE THESIS OPTION. STUDENTS WILL CONTINUALLY REGISTER FOR THIS COURSE UNTIL SUCCESSFUL COMPLETION OF THEIR THESIS. A GRADE OF IN-PROGRESS WILL BE ASSIGNED UNTIL EITHER SUCCESSFUL COMPLETION OR FAILING TO REGISTER. IF FAILING TO REGISTER STUDENTS WILL RECEIVE A GRADE OF NO CREDIT FOR ALL 5399 AND 5398 COURSES.
Prerequisite: COSC 5398.
Variable content study of specific areas of computer and information systems. May be repeated for credit when topics vary. Offered on sufficient demand.
ADVANCED WORK IN A SPECIALIZED AREA OF COMPUTER SCIENCE. DOES NOT COUNT AS CREDIT TOWARD A DEGREE IN COMPUTER SCIENCE. COURSE IS TAKEN AS CREDIT/NON-CREDIT.
THIS COURSE INTRODUCES CONCEPTS AND TECHNIQUES FOR IMAGE PROCESSING. THE OBJECTIVE OF THIS COURSE IS TO INTRODUCE THE FUNDAMENTAL TECHNIQUES AND ALGORITHMS USED FOR PROCESSING AND EXTRACTING USEFUL INFORMATION FROM DIGITAL IMAGES. THE STUDENTS WILL LEARN HOW TO APPLY THE IMAGE PROCESSING METHODS TO SOLVE REAL-WORLD PROBLEMS.
THIS GRADUATE COURSE INTRODUCES CONCEPTS AND TECHNIQUES FOR MACHINE VISION. PARTICULAR EMPHASIS WILL BE PLACED ON METHODS USED FOR OBJECT RECOGNITION, MACHINE LEARNING, CONTENT-BASED IMAGE RETRIEVAL, IMAGE MATCHING, 3D VISION, TRACKING AND MOTION ANALYSIS.
Prerequisite: COSC 6324.
THIS GRADUATE COURSE PROVIDES STUDENTS WITH A FOUNDATION IN BASIC PRINCIPLES AND TECHNIQUES FOR COMPUTER GRAPHICS ON MODERN GRAPHICS HARDWARE. STUDENTS WILL GAIN EXPERIENCE IN INTERACTIVE COMPUTER GRAPHICS USING THE OPENGL API. TOPICS INCLUDE: GRAPHICS HARDWARE, RENDERING, PERSPECTIVE, LIGHTING, AND GEOMETRY.
THIS COURSE COVERS ADVANCED COMPUTER GRAPHICS TECHNIQUES. STUDENTS WILL BE INTRODUCED TO STATE-OF-THE-ART METHODS IN COMPUTER GRAPHICS. THIS COURSE WILL FOCUS ON TECHNIQUES FOR REAL-TIME RENDERING AND ANIMATION.
AN ADVANCED COURSE THAT CONCENTRATES ON THE DESIGN AND ANALYSIS OF ALGORITHMS USED TO SOLVE A VARIETY OF PROBLEMS. THE METHODS OF DESIGN COVERED INCLUDE SUCH TOPICS AS: DIVIDE-AND-CONQUER, THE GREEDY METHOD, DYNAMIC PROGRAMMING, SEARCH AND TRAVERSAL TECHNIQUES, AND BACKTRACKING.
A STUDY OF CONTEMPORARY DATABASE MANAGEMENT CONCEPTS. PERFORMANCE (INDEXING, QUERY OPTIMIZATION, UPDATE OPTIMIZATION), CONCURRENCY, SECURITY AND RECOVERY ISSUES ARE DISCUSSED. ALSO INCLUDES THE STUDY OF FRONT-END ENVIRONMENTS THAT ACCESS THE DATABASE.
AN INTRODUCTION TO FUNDAMENTAL STRATEGIES AND METHODOLOGIES FOR DATA MINING. TOPICS INCLUDE DATA PREPROCESSING, MINING FREQUENT DATA PATTERNS, CLASSIFICATION, CLUSTERING, AND OUTLIER DETECTION.
MACHINE LEARNING IS A SET OF TECHNIQUES THAT HAVE BEEN SUCCESSFULLY USED IN THE PAST FEW DECADES FOR DATA ANALYSIS, PROCESS AUTOMATION, FUNCTION OPTIMIZATION, MODEL BUILDING, AND MANY OTHERS. THESE TECHNIQUES HAVE BEEN EXPLORED IN A DIVERSITY OF FIELDS SUCH AS ROBOTICS, SELF-DRIVING CARS, BIG DATA, CONTROL OF AUTONOMOUS SYSTEMS, IMAGE ANALYSIS, OBJECT RECOGNITION, DATA MINING, BUSINESS, AND FINANCIAL FORECASTING, TRANSPORTATION SYSTEMS, ANTENNA DESIGN, MEDICAL CARE SYSTEMS, AND MANY OTHERS. ML IS A SUBDIVISION OF ARTIFICIAL INTELLIGENCE THAT GIVES MACHINES THE ABILITY TO LEARN AND ADAPT WITH DIFFERENT ACQUIRED KNOWLEDGE AND EXPERIENCE. IN THIS COURSE, A STUDENT WILL LEARN ABOUT STATE OF THE ART ON MACHINE LEARNING AND GET TO KNOW HOW THEY CAN CARRY OUT THESE EVOLVING LEARNING ALGORITHMS. ML ALGORITHMS ATTEMPT TO MIMIC HOW THE HUMAN BRAIN WORKS. WE PLAN TO DEVELOP MANY EXERCISES ON HOW THESE ML ALGORITHMS WORK IN PRACTICAL APPLICATIONS IN BOTH INDUSTRY AND BASIC SCIENCE. WE PLAN TO COVER TOPICS SUCH AS ARTIFICIAL NETWORK NETWORKS, FUZZY LOGIC, HYBRID SYSTEMS, SEARCH AND OPTIMIZATION, CLASSIFICATION, CLUSTERING AND DEEP LEARNING. STUDENTS WILL GAIN EXPERIENCES ON SOME PROGRAMMING TOOLS AND A VARIETY OF APPLICATIONS OF MACHINE LEARNING.
THIS COURSE INTRODUCES CONCEPTS AND TECHNIQUES FOR DEEP LEARNING. THE OBJECTIVE OF THIS COURSE IS TO INTRODUCE THE FUNDAMENTAL THEORY AND APPLICATION OF DEEP LEARNING. PARTICULAR EMPHASIS WILL BE PLACED ON REGULARIZATION AND OPTIMIZATION OF DEEP LEARNING MODELS, CONVOLUTIONAL NETWORK, RECURRENT NEURAL NETWORKS, AUTOENCODERS AND GENERATIVE MODELS. IN ADDITION, THE STUDENTS WILL LEARN HOW TO APPLY THE METHODS TO SOLVE REAL-WORLD PROBLEMS IN SEVERAL AREAS INCLUDING REMOTE SENSING, GEOSPATIAL, AND MEDICAL APPLICATIONS AND DEVELOP THE INSIGHT NECESSARY TO USE THE TOOLS AND TECHNIQUES TO SOLVE ANY NEW PROBLEM.
THIS GRADUATE COURSE INTRODUCES CONCEPTS AND TECHNIQUES FOR HUMAN COMPUTER INTERACTION. ATTENTION WILL BE PAID TO USING NON-TRADITIONAL INPUTS SUCH AS CAMERAS AND MICROPHONES. STUDENTS WILL LEARN TOOLS FOR USING THESE INPUTS TO CREATE INTERACTIONS WITH USERS.
THE STUDY OF EMERGING DATABASE TECHNOLOGIES. TOPICS ARE CHOSEN FROM DATA WAREHOUSING, DISTRIBUTED DATABASES, SPATIAL DATABASES AND WEB-BASED APPLICATIONS.
Prerequisite: COSC 6336.
AN OVERVIEW OF COMPUTER ARCHITECTURE, WHICH STRESSES THE UNDERLYING DESIGN PRINCIPLES AND THE IMPACT OF THESE PRINCIPLES ON COMPUTER PERFORMANCE. GENERAL TOPICS INCLUDE DESIGN METHODOLOGY, PROCESSOR DESIGN, CONTROL DESIGN, MEMORY ORGANIZATION, SYSTEM ORGANIZATION, AND PARALLEL PROCESSING.
INTRODUCTION TO ADVANCED CONCEPTS IN OPERATING SYSTEMS AND DISTRIBUTED SYSTEMS. TOPICS INCLUDE DISTRIBUTED SYSTEM ARCHITECTURES, INTERPROCESS COMMUNICATION, DISTRIBUTED MUTUAL EXCLUSION, DISTRIBUTED SYNCHRONIZATION AND DEADLOCK, AGREEMENT PROTOCOLS, DISTRIBUTED SCHEDULING AND PROCESS MANAGEMENT, DISTRIBUTED SHARED MEMORY, DISTRIBUTED FILE SYSTEMS, MULTIPROCESSOR SYSTEM ARCHITECTURES AND OPERATING SYSTEMS, RECOVERY AND FAULT TOLERANCE.
THIS COURSE INTRODUCES THE BASIC CONCEPTS AND MECHANISMS TRADITIONALLY EMPLOYED IN LANGUAGE TRANSLATORS, WITH EMPHASIS ON COMPILERS. TOPICS INCLUDE STRATEGIES FOR SYNTACTIC AND SEMANTIC ANALYSIS, TECHNIQUES OF CODE OPTIMIZATION AND APPROACHES TOWARD CODE GENERATION.
Prerequisite: MATH 2305.
FUNDAMENTAL CONCEPTS AND TECHNIQUES FOR THE DESIGN OF COMPUTER-BASED, INTELLIGENT SYSTEMS. TOPICS INCLUDE: A BRIEF HISTORY, METHODS FOR KNOWLEDGE REPRESENTATION, HEURISTIC SEARCH TECHNIQUES, PROGRAMMING IN LISP OR PROLOG.
AREAS STUDIED INCLUDE PRINCIPLES OF COMPUTER-BASED COMMUNICATION SYSTEMS, ANALYSIS AND DESIGN OF COMPUTER NETWORKS, AND DISTRIBUTED DATA PROCESSING.
AN INTRODUCTION TO THEORETICAL FOUNDATIONS OF MODERN COMPUTING. TOPICS INCLUDE FINITE STATE MACHINE CONCEPTS, FORMAL GRAMMARS, AND BASIC COMPUTABILITY CONCEPTS.
THIS IS A GRADUATE LEVEL COURSE ON WIRELESS SENSOR NETWORKS; ONE OF THE FASTEST DEVELOPING AREAS IN COMPUTER SCIENCE AND ENGINEERING. THE FOCUS OF THIS COURSE IS ON THE DESIGN OF OPTIMIZED ARCHITECTURES AND PROTOCOLS FOR SUCH UNIQUE NETWORKS. TOPICS INCLUDE THE DESIGN PRINCIPLES OF WIRELESS SENSOR NETWORKS, ENERGY MANAGEMENT, MAC PROTOCOLS, NAMING AND ADDRESSING, LOCALIZATION, ROUTING PROTOCOLS, APPLICATIONS OF WIRELESS SENSOR NETWORKS, AND ASSOCIATED CHALLENGES AND MEASURES.
INTRODUCTION TO THE HARDWARE AND SOFTWARE ISSUES IN PARALLEL COMPUTING. TOPICS INCLUDE MOTIVATION AND HISTORY, PARALLEL ARCHITECTURES, PARALLEL ALGORITHM DESIGN, AND PARALLEL PERFORMANCE ANALYSIS. STUDENTS WILL BE INTRODUCED TO A VARIETY OF PARALLEL COMPUTING PARADIGMS INCLUDING MESSAGE PASSING SYSTEMS AND SHARED MEMORY SYSTEMS.
INTRODUCES AND EVALUATES IMPORTANT MODELS OF PARALLEL AND DISTRIBUTED COMPUTATION. TOPICS INCLUDE A SELECTION OF PARALLEL ALGORITHMS FOR VARIOUS MODELS OF PARALLEL COMPUTATION, COMBINATIONAL CIRCUITS, PARALLEL PREFIX COMPUTATION, DIVIDE AND CONQUER, POINTER BASED DATA STRUCTURES, LINEAR ARRAYS, MESHES AND RELATED MODELS, AND HYPERCUBES.
SURVEY OF SOFTWARE DEVELOPMENT ON MOBILE PLATFORMS INCLUDING BOTH NATIVE AND CROSS-PLATFORM APPLICATIONS WITH TOPICS SUCH AS: PROTOTYPING, PROGRAMMING, TESTING, DEBUGGING, AND DEPLOYING. COVERAGE OF SOFTWARE LIFE CYCLE ON MOBILE PLATFORMS AND HOW MOBILE HARDWARE DIFFERS FROM TRADITIONAL COMPUTERS.
THIS IS A SURVEY OF CURRENT TRENDS IN COMPUTER PROGRAMMING. THE FOCUS OF THIS COURSE IS ON THE DEVELOPMENT OF COMPUTER PROGRAMS UTILIZING THE LATEST TECHNOLOGIES AND PARADIGMS. TOPICS INCLUDE STATE-OF-THE-ART IN PROBLEM SOLVING AND SOFTWARE DEVELOPMENT, PROGRAMMING TECHNIQUES AND APPROACHES, PROGRAMMING LANGUAGES, DEVELOPMENT TOOLS AND ENVIRONMENTS, AND SOFTWARE DEPLOYMENT METHODS.
AREAS STUDIED INCLUDE ENGINEERING PRINCIPLES AND THEIR APPLICATION TO THE DESIGN, DEVELOPMENT, TESTING, AND MAINTENANCE OF LARGE SOFTWARE SYSTEMS, TOOLS AND PROCESSES FOR MANAGING THE COMPLEXITIES INHERENT IN CREATING AND MAINTAINING LARGE SOFTWARE SYSTEMS.
THIS COURSE WILL INTRODUCE STUDENTS TO THE FUNDAMENTALS OF COMPUTER FORENSICS AND VARIOUS SOFTWARE TOOLS USED IN CYBER-CRIME ANALYSIS. STUDENTS WILL BE INTRODUCED TO ESTABLISHED METHODOLOGIES FOR CONDUCTING COMPUTER FORENSIC INVESTIGATIONS, AS WELL AS TO EMERGING INTERNATIONAL STANDARDS FOR COMPUTER FORENSICS. APPLICABLE LAWS AND REGULATIONS DEALING WITH COMPUTER FORENSIC ANALYSIS WILL ALSO BE DISCUSSED.
AN INTRODUCTION TO INFORMATION SECURITY AND ASSURANCE. THIS COURSE COVERS THE BASIC NOTIONS OF CONFIDENTIALITY, INTEGRITY, AVAILABILITY, AUTHENTICATION MODELS, PROTECTION MODELS, SECURE PROGRAMMING, AUDIT, INTRUSION DETECTION AND RESPONSE, OPERATIONAL SECURITY ISSUES, PHYSICAL SECURITY ISSUES, PERSONNEL SECURITY, POLICY FORMATION AND ENFORCEMENT, ACCESS CONTROLS, INFORMATION FLOW, LEGAL AND SOCIAL ISSUES, CLASSIFICATION, TRUST MODELING, AND RISK ASSESSMENT.
THIS COURSE IS A STUDY OF NETWORKING BASICS AND SECURITY ESSENTIALS WITH RESPECT TO INFORMATION SERVICES PROVIDED OVER A COMPUTER NETWORK. THE COURSE COVERS THE TECHNICAL DETAILS OF SECURITY THREATS, VULNERABILITIES, ATTACKS, POLICIES, AND COUNTERMEASURES SUCH AS FIREWALLS, HONEYPOTS, INTRUSION DETECTION SYSTEMS, AND CRYPTOGRAPHIC ALGORITHMS FOR CONFIDENTIALITY AND AUTHENTICATION AND THE DEVELOPMENT OF STRATEGIES TO PROTECT INFORMATION SERVICES AND RESOURCES ACCESSIBLE ON A COMPUTER NETWORK.
Prerequisite: COSC 6375.
THIS COURSE INCLUDES AN INTRODUCTION TO CRYPTOGRAPHIC ALGORITHMS AND PROTOCOLS FOR ENCRYPTING INFORMATION SECURELY, TECHNIQUES FOR ANALYZING VULNERABILITIES OF PROTOCOLS, APPROACHES TO DIGITAL SIGNATURES AND INFORMATION DIGESTS, AND IMPLEMENTATION APPROACHES FOR THE MOST SIGNIFICANT CRYPTOGRAPHIC METHODOLOGIES.
THIS COURSE ENCOMPASSES A BROAD RANGE OF TOPICS INVOLVING INFORMATION SECURITY, COMMUNICATIONS SECURITY, NETWORK SECURITY, RISK ANALYSIS, OPERATIONAL SECURITY, HEALTH INFORMATION PRIVACY, CRIMINAL JUSTICE DIGITAL FORENSICS, HOMELAND SECURITY, THE HUMAN ELEMENT AND SOCIAL ENGINEERING, AND APPLICABLE NATIONAL AND INTERNATIONAL LAWS. AN IN-DEPTH INFORMATION ASSURANCE CAPSTONE PROJECT OR RESEARCH PAPER WILL BE REQUIRED OF EACH STUDENT TO SATISFY THE INFORMATION ASSURANCE GRADUATE OPTION REQUIREMENTS.
Prerequisite: COSC 6375.
THIS COURSE WILL INTRODUCE STATE-OF-THE-ART TECHNIQUES TO PROCESS AND ANALYZE DIFFERENT TYPES OF DATA, GENERATE INSIGHTS AND KNOWLEDGE FROM DATA, AND MAKE DATA-BASED DECISIONS AND PREDICTIONS. REAL-WORLD EXAMPLES WILL BE USED TO FAMILIARIZE STUDENTS WITH THE THEORY AND APPLICATIONS. MAIN TOPICS INCLUDE DATA PREPROCESSING, PROBABILITY THEORY, TESTS OF HYPOTHESIS, AND VARIOUS DATA ANALYSIS TECHNIQUES (E.G., CLUSTERING, CLASSIFICATION, PREDICTION/FORECASTING, ETC.) FOR DIFFERENT TYPES OF DATA INCLUDING STATIC, TIME-SERIES, SPATIAL, AND SPATIOTEMPORAL.
THIS COURSE PROVIDES STUDENTS WITH A RANGE OF EXPERIENCES IN CONDUCTING AND COMMUNICATING RESEARCH. STUDENTS WILL LEARN MAJOR RESEARCH METHODS AND TECHNIQUES. EXPERIENCES WILL BE GAINED IN ALL STAGES OF RESEARCH: REVIEWING LITERATURE, WRITING A PROPOSAL, DESIGNING AN APPROACH, AND REPORTING RESULTS. CRITICAL-READING/WRITING ASSIGNMENTS AND CLASS DISCUSSIONS ON STATE-OF-THE-ART RESEARCH IN COMPUTER SCIENCE WILL PROVIDE STUDENTS WITH MAJOR RESEARCH ASPECTS. SPRING
STUDY IN AREAS OF CURRENT INTEREST. (A MAXIMUM OF SIX HOURS MAY BE COUNTED TOWARD THE MS DEGREE.) FALL, SPRING, SUMMER.
VARIABLE CONTENT STUDY OF SPECIFIC AREAS OF COMPUTER AND INFORMATION SYSTEMS. MAY BE REPEATED FOR CREDIT WHEN TOPICS VARY. OFFERED ON SUFFICIENT DEMAND.