DEPARTMENT OF COMPUTER SCIENCE

Transcription

1 Department of Computer Science 1 DEPARTMENT OF COMPUTER SCIENCE Gregory W. Donohoe, Dept. Chair (237 Janssen Engr. Bldg ; phone 208/ ; chair@cs.uidaho.edu; Faculty: James Alves-Foss, Bruce M. Bolden, David Buehler,, Robert B. Heckendorn, Robert E. Hiromoto, Clinton L. Jeffery, William S. Junk, Axel W. Krings, Milos Manic, John C. Munson, Paul W. Oman, Robert Rinker, Terence Soule. Adjunct Faculty: Leonard Bond, Wayne F. Boyer, James R. Buffenbarger, W. Scott Harrison, Miles A. McQueen, Carol Taylor, Chunsheng Xin. Computer science is the systematic study of algorithmic processes that describe and transform information: their theory, analysis, design, efficiency, implementation, and application. It is a broad discipline with an ever-growing array of opportunities. Graduates in this field can find employment in a wide spectrum of public and private enterprises. The field of computer science encompasses many areas of specialization. One may find a personal niche in software development, systems development and hardware selection, studies of compatibility between hardware and software, programming language development and modification, information assurance, bioinformatics or perhaps a combination of these and any number of other diverse computer-oriented applications and concepts. Because of this diversity in potential application areas, the computer scientist must be familiar with the language of the physical or biological sciences, mathematics, and English. If the computer is to extend its role as a benefit to mankind, the computer scientist must be broadly educated and conversant with the many implications of the powerful tool that he or she is controlling and developing. The Department of Computer Science was formed in 1981 and is in the College of Engineering. The Bachelor of Science in Computer Science has been offered at UI since This program consists of a carefully designed computer science core, surrounded by an extensive array of challenging technical elective courses. The core consists of courses in algorithms and data structures, programming languages, computer architecture, operating systems, software engineering, theory of computation, and a senior capstone design experience. All of these courses have important components of theory, abstraction, and design. The Bachelor of Science program in computer science is accredited by the Computing Accreditation Commission (CAC) of the Accreditation Board for Engineering and Technology (ABET) 111 Market Place, Suite 1050, Baltimore, MD telephone: (410) The department has made substantial contributions to achieving the University s designation by the US Department of Homeland Security, as a National Center of Excellence in Information Assurance Education. The department offers graduate programs leading to the degrees, Master of Science and Doctor of Philosophy. These programs combine a core of advanced work with a complement of elective courses selected to provide a focused plan of study. Students in computer science have the unique opportunity to draw from the expertise of an outstanding faculty with extensive experience in industry, teaching, and research. Computers currently available to students include an extensive department network of UNIX, Linux, and Windowsbased workstations and several campus personal computer laboratories for research focus. All major campus and department computer systems are networked together with Internet connections, providing a state-ofthe-art computing environment. The department was instrumental in establishing the Center for Secure and Dependable Systems (CSDS) and the Initiative for Bioinformatics and Evolutionary Studies (IBEST). The importance of these labs can be seen from the range of private and government funding which supports the department s research in computer security, computer reliability, bioinformatics, evolutionary computation and high performance computing. Courses See the course description section for courses in Computer Science (CS). Computer Science Undergraduate Curricular Requirements Computer Science (B.S.C.S.) Required course work includes the university requirements (see regulation J-3) and: General Education Electives (5 cr): Comm 101 Fundamentals of Public Speaking (2 cr) Engl 317 Technical Writing (3 cr) Computer Science (43 cr): CS 105 Computer Science as a Profession (2 cr) CS 120 Computer Science I (4 cr) CS 121 Computer Science II (4 cr) CS 150 Computer Organization and Architecture (3 cr) CS 210 Programming Languages (3 cr) CS 240 Computer Operating Systems (3 cr) CS 270 System Software (3 cr) CS 383 Software Engineering (3 cr) CS 385 Theory of Computation (3 cr) CS 395 Analysis of Algorithms (3 cr) CS 401 Contemporary Issues in Computer Science (1 cr) CS 445 Compiler Design (4 cr) CS 481 CS Senior Capstone Design II (3 cr) Mathematics and Statistics (17 cr): Math 170 Analytic Geometry and Calculus I (4 cr) Math 175 Analytic Geometry and Calculus II (4 cr) Math 176 Discrete Mathematics (3 cr) Math 330 Linear Algebra (3 cr) Stat 301 Probability and Statistics (3 cr) One of the following laboratory science sequences (8-9 cr): Biol 115 and Biol 116 Cells and the Evolution of Life and Organisms and Environments (8 cr) Chem 111 and Principles of Chemistry I and Principles of Chemistry II (9 Chem 112 Phys 211, Phys 211L and Phys 212, Phys 212L Phys 211, Phys 211L and Phys 213, Phys 213L cr) Engineering Physics I and Lab and Engineering Physics II and Lab (8 cr) Engineering Physics I and Lab and Engineering Physics III and Lab (8 cr) Science electives from the following sets of courses (4 cr): Biology all courses except Biol 102 Chemistry all courses except Chem 100 and Chem 101 Environmental Science only EnvS 101 and EnvS 102 Geography only Geog 100, Geog 301, or Geog 401 Geology all courses Microbiology, Molecular Biology, and Biochemistry all courses Physics all courses except Phys 100, Phys 200, Phys 400, and Phys 403 Upper-division technical electives selected to satisfy the credit distribution in these categories (15 cr): Computer Science (12 cr) any upper-division CS course except 499. Mathematics (3 cr) Math 275 or any upper-division Math or Stat course except Math 400, Math 404, Math 499, and Math 513-Math 519. Courses to total 128 credits for this degree, not counting Engl 101, Math 143, and other courses that might be required to remove deficiencies. A minimum grade of C is required in CS 120, CS 121, CS 150, CS 210, CS 240, CS 270, Math 170, Math 176, and Math 175 in order to graduate. Students majoring in computer science must earn a grade of C or better in CS 120, CS 121, and CS 150 and a C or better in Math 176 before registration is permitted in 200 level CS courses. Students majoring in computer science must earn a grade of C or better in CS 210, CS 240,

2 2 Department of Computer Science CS 270, and Math 170 and Math 175 before registration is permitted in upper-division CS courses. Students must consult with their advisors when selecting electives within the curriculum to insure that their career objectives are met. Computer Science Academic Minor Requirements Computer Science Minor CS 120 Computer Science I (4 cr) CS 121 Computer Science II (4 cr) CS 150 Computer Organization and Architecture (3 cr) Math 176 Discrete Mathematics (3 cr) Elective courses (6 cr): CS 210 Computing Languages (3 cr) CS 240 Computer Operating Systems (3 cr) CS 270 System Software (3 cr) Courses to total 20 credits for this minor Computer Science Graduate Academic Certificates Requirements Secure and Dependable Computing Systems Graduate Academic Certificate Note: A grade of B or higher is required in all coursework for this academic certificate. CS 536 Advanced Information Assurance Concepts (3 cr) One of the following (3 cr): CS 438 Network Security (3 cr) CS 538 Network Security (3 cr) Electives (6 cr): CS 448 Survivable Systems and Networks (3 cr) CS 449 Fault-Tolerant Systems (3 cr) CS 504 Special Topics (3 cr) CS 548 Survivable Systems and Networks (3 cr) CS 549 Fault-Tolerant Systems (3 cr) Courses to total 12 credits for this certificate Computer Science Graduate Degree Programs Candidates must fulfill the requirements of the College of Graduate Studies and the Department of Computer Science. See the College of Graduate Studies section for the general requirements applicable to each degree. No 300-level course that is required in the B.S.C.S. curriculum may be used to satisfy the requirements of the graduate degree. A graduate degree in computer science from UI prepares a student for a lifetime of discovery. It enables the graduate to advance the state of the art in computing, not merely to keep up with it. The graduate program develops the student's critical thinking, investigatory, and expository skills. The student will learn the foundations of computer science theory and application, and the interaction between the two. By understanding the extent and limitation of current knowledge in computer science, the graduate will learn to understand what issues are important and why. He or she will acquire the methodological skills to resolve important open problems and tackle challenging new projects. The student will learn to present problems and solutions, both orally and in writing. For examples of active research areas please visit the department s website The study of computer science at the graduate level requires mathematical maturity, skill in the use of high-level and machine-level programming languages, and basic knowledge of computer hardware. Admission to this program is highly competitive. An undergraduate degree in Computer Science is not a requirement. Students with a bachelor s degree from other closely allied undergraduate programs will be considered. Students who wish to enter the graduate program must ultimately demonstrate competence in specific areas equivalent to the material covered in several of the undergraduate computer science core courses. Normally a 3.0 undergraduate GPA and a Graduate Record Examination general (aptitude) score in the 60th percentile are the minimum admission requirements. Actual admission is based on a combination of undergraduate GPA and Graduate Record Examination scores. International students for whom English is a second language must have a TOEFL score of 550 or higher for the written test, 213 or higher for the computer based test, or 79 or higher for the internet-based test. As a prerequisite to graduate program admission, competence in the following areas must be demonstrated: knowledge of a structured, highlevel language; algorithms and data structures; and a full year of calculus. If prerequisite requirements are met, a student who does not have an adequate coursework background in computer science may be admitted with deficiencies. He or she must then demonstrate knowledge of this material early on in their graduate studies by either taking the GRE Computer Science Subject Test and receiving a score in the 60th percentile or higher or by completing those courses in which he or she is deficient. Deficiency areas for graduate work in computer science are: computer organization and architecture; computer languages; computer operating systems; software engineering; analysis of algorithms; and theory of computation. Credit for deficiency courses cannot be counted toward the total credits required for the graduate degree. Master of Science. The following are requirements for receiving an M.S. degree in computer science from UI. There is both a thesis and a nonthesis option, though in both options the student must complete courses in the graduate CS core and in a focused plan of study. In both options, the student must successfully complete at least 18 credit hours of 500- level courses and at least 18 credit hours of CS courses. A graduate degree represents mastery of the theory underlying one's discipline, a graduate breadth requirement. This is the foundation on which further study should be based. The student must acquire depth in at least one major area by developing a focused plan of study in consultation with the major advisor. This should be a program that investigates some aspect of computer science in depth, consistent with the goals of the graduate program in computer science. The thesis option requires at least 30 credit hours of study. Specific requirements are: graduate breadth requirement; at least one semester of CS Graduate Seminar, CS 501 (1 cr); and Master s Research and Thesis, CS 500 (at least 6 cr). The thesis must be in the approved format and must represent significant scholarly achievement. The thesis must be presented at a public colloquium. The non-thesis option requires at least 30 credit hours of study, up to 6 credits of which can be CS 580. Specific requirements are: graduate breadth requirement and at least one semester of CS Graduate Seminar, CS 501 (1 cr). At the end of the program, non-thesis students must pass a comprehensive examination that covers their graduate studies. Doctor of Philosophy. The PhD degree represents a continuation in the mastery of the theory underlying computer science. A doctoral student develops a graduate program of at least 78 semester hours in consultation with his or her major professor and supervisory committee. The PhD graduate candidate must successfully complete the CS graduate breadth requirement. As a part of the program the student is required to include at least two semesters of CS 501 (graduate seminar). The student must have at least one full semester of teaching experience, with the teaching assignment determined by the student's supervisory committee. There is no foreign language requirement. The student must satisfy the residency requirement by spending at least two terms at the Moscow campus or a UI Residence Center. The purpose of the residency requirement is to provide the student with access to facilities, faculty, and colleagues. The qualifying examination is a written and/or oral examination, administered by the student's graduate committee, which covers fundamental areas of computer science. The preliminary examination is an examination of a student s proposed dissertation research, including both a written proposal and an oral public presentation covering related research, preliminary results, and a research plan. The student must produce a dissertation, presenting an original, significant contribution to computer science. The dissertation should be publishable, in whole or in part, and should demonstrate the ability of the candidate to successfully initiate and pursue a significant, original research project. A public presentation and defense of the final dissertation is required. It is expected that all PhD students will publish the results of their research before completion of their degree.

3 Computer Science Courses 3 COMPUTER SCIENCE COURSES Gregory W. Donohoe, Chair, Dept. of Computer Science (237 Janssen Engr. Bldg ; phone 208/ ). Vertically-related courses in this subject field are: CS CS 101 Introduction to Computer Science (3 cr) Survey of computer science and topics of importance to computer scientists; includes topics such as the nature of problems, unsolvability, hardware, human factors, security, social, ethical, and legal issues; exposure to practical aspects of computer networks. Three lectures and one recitation per week. Recommended Preparation: two yrs of high school algebra. CS 105 Computer Science as a Profession (2 cr) Introduction to the computer science profession and curriculum; fields of study available; current topics in departmental research; curriculum planning; legal, ethical, and social issues in computing; academic ethics and responsibilities. (Fall only) CS 112 Introduction to Problem Solving and Programming (3 cr) Intro to fundamental problem solving techniques using the computer; use of a programming language, structured programming concepts; use of fundamental data types, including arrays and structures; basic concepts of computer organization, editing, and program execution; programming lab in which the student gains hands-on experience in problem solving with modern programming tools. Prereq: Math 108 or sufficiently high ACT, SAT, or Math Placement Test score to qualify for Math 143 CS 120 Computer Science I (4 cr) Fundamental programming constructs, Algorithms and problem-solving, Fundamental data structures, Overview of programming languages, Virtual machines, Introduction to language translation, Declarations and types, Abstraction mechanisms, Object-oriented programming. Three lec and one 2-hr lab a wk. Prereq: Math 108 or sufficiently high ACT, SAT, or Math Placement Test score to qualify for Math 143 CS 121 Computer Science II (4 cr) Abstract data types and data structures: linked lists, stacks, queues, trees, and graphs. Methods to implement and algorithms to manipulate these structures. Dynamic memory methods, sequential file processing, additional searching and sorting algorithms, recursion, and objectoriented programming. Three lec and one 2-hr lab a wk. Prereq: CS 120 Coreq: Math 176 CS 127 (s) Programming Language (1-3 cr, max arr) Introduction to computer programming in a selected language. Prereq: Permission CS 130 Programming with Visual Basic (3 cr) Introduction to fundamental problem solving techniques using the computer and the object oriented, event driven language Visual Basic. The course introduces structured programming concepts; the use of fundamental data types, including arrays and database structures; and editing and program execution. Recommended Preparation: Math 143. CS 150 Computer Organization and Architecture (3 cr) Digital logic and digital systems, Machine level representation of data, Assembly level machine organization, Memory system organization and architecture, Interfacing and communication, Functional organization, Multiprocessing and alternative architectures. Prereq: CS 120 CS 204 (s) Special Topics (cr arr) CS 210 Programming Languages (3 cr) Major features of good programming languages, with primary emphasis on language features and their role in writing good software; programming language design alternatives; various types of languages, including procedure, data-flow, functional, and object-oriented languages. Prereq: CS 121 CS 240 Computer Operating Systems (3 cr) Overview of operating systems, Operating system principles, Concurrency, Scheduling and dispatch, Memory management, Introduction to netcentric computing, OS security. Process management. Concurrent programming using threads. Prereq: CS 121 and 150 Coreq: CS 270 CS 270 System Software (3 cr) Programming productivity tools such as make. Debugging tools. Linking and loading. Shell programming and scripting languages. Process management and interprocess communication. Exception handling. Network concepts and network programming. Prereq: CS 121 CS 299 (s) Directed Study (cr arr) CS 324 Computer Graphics (3 cr) Use of the computer to define, store, manipulate, and display 2-D and 3- D objects; 2-D curvefitting and 3-D surface development. Cooperative: open to WSU degree-seeking students. Prereq: CS 121 and Math 330 CS 328 Introduction to Computer Game Development (3 cr) An introduction to data structures, algorithms, and programming techniques useful in the development of computer games. Topics including 2D graphics, sound programming, user interfaces, game genres, computerization of classic board games and simulation games. Prereq: CS 210 and CS 240 CS 336 Introduction to Information Assurance (3 cr) Introduces the confidentiality, availability and integrity goals of information systems; resistance, recognition and response categories of assurance. Focus on computer security and survivability, including cryptography, network security, general purpose operating system security and dependability and special purpose systems for high assurance security and dependability. Prereq: CS 240 CS 350 Intermediate Computer Architecture (3 cr) Applied understanding of processor architecture. Design and construction of processor components, including the Arithmetic-Logic Unit (ALU), registers, datapath and control units. Memory interface to the processor. Performance optimizations, including pipelining techniques, cache memory. Portions of a processor will be constructed and simulated using a Hardware Description Language (HDL). Prereq: CS 150 and CS 240 CS 360 Database Systems (3 cr) Study of database design and implementation; comparison of basic models (entity-relationship, hierarchical, network, relational); study of query languages; discussion of issues of integrity, security, dependencies, and normal forms. Prereq: CS 240 and 270 CS 383 Software Engineering (3 cr) Current topics in development of software systems; software life cycle model, requirements definition, requirements analysis, software specification, software architectural design, engineering discipline in software development, software measurement, user interface design, legal and ethical issues in software product development. Projects are developed to demonstrate application of concepts. (Fall only) Prereq: CS 210, CS 240 and CS 270 or Permission CS 385 Theory of Computation (3 cr) See Math 385. CS 395 Analysis of Algorithms (3 cr) See Math 395. CS 398 (s) Computer Science Cooperative Internship (1-3 cr, max 3) Supervised internship in professional computer science settings, integrating academic study with work experience; requires formal plan of activities before co-op assignment and final written report evaluated by oncampus faculty members. Graded P/F. Prereq: Permission

4 4 Computer Science Courses CS 401 Contemporary Issues in Computer Science (1 cr) Ethical, legal, and intellectual property issues; current research topics; and other issues of importance to the professional computer scientist. Graded P/F. Prereq: Senior standing in CS CS 404 (s) Special Topics (cr arr) CS J411/J511 Parallel Programming (3 cr) Analysis, mapping, and the application of parallel programming software to high-performance systems; the principles of spatial- and temporallocality of data memory hierarchies in performance tuning; architectural considerations in the design and implementation of a parallel program; the tradeoff between threaded (shared memory) and message-passing (distributed memory) programming styles and performance. Additional projects/assignments required for graduate credit. Recommended Preparation: Proficiency in programming using a modern language such as C or C++. Prereq: CS 395 CS J412/J512 Parallel Algorithms (3 cr) Parallel algorithm design; formal analysis of parallel algorithmic complexity; measures of parallel efficiency; relationship between algorithmic structure and parallel mapping strategies; the consequences of spatialand temporal-locality. Additional projects/assignments required for graduate credit. Prereq: CS 395 CS J415/J515 Computational Biology: Sequence Analysis (3 cr) Design and analyze algorithms that address the computational problems posed by biological sequence data, such as DNA or protein sequences. Topics may include: comparing sequences (from genes to genomes), database searching, multiple sequence alignment, phylogenetic inferencing, gene discovery and annotation, and genome assembly. Additional class presentation and/or paper required for graduate credit. Prereq: Knowledge of high level programming language, basic probability theory, basic molecular biology, or Permission CS J420/J520 Data Communication Systems (3 cr) Concept and terminology of data communications, equipment, protocols (including ISO/OSI and TCP/IP), architectures; transmission alternatives, regulatory issues and network management. Additional projects/assignments reqd for grad cr. Prereq: CS 150 and 240 CS J428/J528 Multi-User Games and Virtual Environments (3 cr) Software design and programming issues involved in constructing multiuser computer games and virtual environments, incorporating networking and 3D graphics. Additional projects and assignments are required for graduate credit. Prereq: CS 210, CS 324, and CS 328 CS J438/J538 Network Security (3 cr) Practical topics in network security; policy and mechanism, malicious code; intrusion detection, prevention, response; cryptographic techniques for privacy and integrity; emphasis on tradeoffs between risk of misuse, cost of prevention, and societal issues; concepts implemented in programming assignments. Additional projects/assignments reqd for grad cr. Recommended Preparation: Knowledge of C or C++. CS 438 is a cooperative course available to WSU degree-seeking students. Prereq: CS 336 CS J439/J539 Applied Security Concepts (3 cr) Hands-on approach to computer security with emphasis on developing practical knowledge of how cyber attacks work and how to defend against them. Detailed exploration of attacks such as buffer overruns, string attacks, worms, trojan horses, and denial-of-service attacks, and development of defenses against them. Additional work reqd for grad cr. Recommended preparation: Good knowledge of C, operating system concepts and Unix. Prereq: CS 336 or Permission CS 445 Compiler Design (4 cr) Algorithms used by the following system software: assemblers, macroprocessors, interpreters, and compilers; compiler design options and code optimization; all concepts implemented in major programming assignments. Prereq: CS 210 and 385 CS J447/J547 Computer and Network Forensics (3 cr) Competence in using established forensic methods in the handling of electronic evidence; rigorous audit/logging and data archival practices; prevention, detection, apprehension, and prosecution of security violators and cyber criminals; identifying and correcting computer vulnerabilities in a way that is smart, prudent, and responsible. Additional work required for graduate credit. Prereq: CS 336 and Permission CS J448/J548 Survivable Systems and Networks (3 cr) Computers and networks under malicious threat or attack. Attributes of survivability, trustworthiness, dependability and assurance. Threats to survivability, security, reliability and performance. Models and analytical methods to assess survivability, vulnerability, interdependence and risk. Systemic inadequacies and approaches for overcoming deficiencies. Literature review and case studies. Additional projects/assignments required for graduate credit. Recommended Preparation: CS J449/J549 or CS 438. CS J449/J549 Fault-Tolerant Systems (3 cr) Same as ECE J449/J549. Design, modeling, analysis and integration of hardware and software to achieve dependable computing systems employing on-line fault tolerance; theory and fundamental concepts of designing reliable systems; analytical evaluation techniques, faults and advances in ultra-reliable distributed systems, fault-tolerant software systems; case studies include the space Shuttle, Airbus, and Boeing flyby-wire primary flight computers as well as systems in reliable data bases and financial markets. Additional projects and assignments reqd for grad cr. Prereq: ECE 441 or Permission CS J451/J551 Advanced Computer Architecture (3 cr) Same as ECE J441/J541. Principles and alternatives in instruction set design; processor implementation techniques, pipelining, parallel processors, memory hierarchy, and input/output; measurement of performance and cost/performance trade-off. Additional work required for graduate credit. Prereq: CS 150, Stat 301 or Permission CS J452/J552 Real-Time Operating Systems (3 cr) Topics of interest in the implementation of Real-Time Operating Systems, especially as applicable to embedded systems, including a relevant hardware review, interrupts and interrupt handling, real-time scheduling principles and implementation, latency, task management, shared data and synchronization, timers, message passing, tradeoffs between memory space and speed. Students will build a simple but relatively complete real-time operating system over the course of the semester. Additional projects and assignments are required for graduate credit. (Spring only) Prereq: CS 240 CS J460/J560 Database Management Systems Design (3 cr) Theory, analysis and implementation of database architecture, security, performance, query optimization, recovery and concurrency control, reliability, integrity, commit protocols, distributed processing, deadlock detection and management. Additional projects/assignments required for graduate credits. Prereq: CS 360 CS J470/J570 Artificial Intelligence (3 cr) Concepts and techniques involved in artificial intelligence, Lisp, goaldirected searching, history trees, inductive and deductive reasoning, natural language processing, and learning. Extra term paper reqd for cr in 570. Prereq: CS 210 CS J472/J572 Evolutionary Computation (3 cr) Solving computation problems by growing solutions; simulates natural evolution using analogues of mutation, crossover, and other generic transformations on representations of potential solutions; standard EC techniques such as genetic algorithms and evolutionary programming, mathematical explanations of why they work, and a survey of some applications; the focus is on solving real-world problems using projects. Graduate-level research and possible paper or presentation required for grad cr. Prereq: CS 210 CS 480 CS Senior Capstone Design I (3 cr) Capstone design sequence for computer science majors. Formal development techniques applied to definition, design, coding, testing, and documentation of a large software project. Projects are customer-

5 Computer Science Courses 5 specified, includes real-world design constraints, and usually encompasses two semesters. Students work in teams. Significant lab work required. Prereq: CS 383, Engl 317, and Senior standing CS 481 CS Senior Capstone Design II (3 cr) Continuation of CS480. Application of formal design techniques to development of a large computer science project performed by students working in teams. Significant lab work required. Prereq: CS 480 CS 499 (s) Directed Study (cr arr) CS 500 Master's Research and Thesis (cr arr) CS 501 (s) Seminar (cr arr) CS 502 (s) Directed Study (cr arr) CS 504 (s) Special Topics (cr arr) CS 510 Programming Language Theory (3 cr) Advanced topics in programming language theory including formal syntax, formal semantics, denotational semantics, and type theory; principles of programming language design are stressed; not a comparative language class. Cooperative: open to WSU degree-seeking students. Coreq: CS 385 or Equivalent CS 511 Parallel Programming (3 cr) See CS J411/J511. CS 512 Parallel Algorithms (3 cr) See CS J412/J512. CS 513 Concurrent Systems (3 cr) Issues of parallel computer architecture considering a hardware/software approach; topics include convergence of parallel architectures, fundamental design issues, parallel programs, programming for performance, workload-driven evaluation, shared memory multiprocessors, snoopy-based multiprocessor design, scalable multiprocessors, cache coherence, hardware software tradeoffs, interconnection network design, latency tolerance, and future directions of concurrent systems. Prereq: CS 150 and CS 240 CS 515 Computational Biology: Sequence Analysis (3 cr) See CS J415/J515. CS 520 Data Communication Systems (3 cr) See CS J420/J520. CS 524 Advanced Computer Graphics (3 cr) Graphical user interfaces; rendering for realism including shading, shadows and textures; fractals; raster displays, pixmaps, and antialiasing; 3D curves and surfaces; color theory; hidden surfaces; ray tracing; games. Additional work required for graduate credit. (Spring only) Prereq: CS 324, Math 175 CS 528 Multi-User Games and Virtual Environments (3 cr) See CS J428/J528. CS 536 Advanced Information Assurance Concepts (3 cr) Advanced topics in design and analysis of network, database, and operating system security; current trends and research in mandatory and discretionary security policies. Recommended preparation: CS 336. CS 538 Network Security (3 cr) See CS J438/J538. CS 539 Applied Security Concepts (3 cr) See CS J439/J539. CS 547 Computer and Network Forensics (3 cr) See CS J447/J547. CS 548 Survivable Systems and Networks (3 cr) See CS J448/J548. CS 549 Fault/Tolerant Systems (3 cr) See CS J449/J549. CS 551 Advanced Computer Architecture (3 cr) See CS J451/J551. CS 552 Real Time Operating Systems (3 cr) See CS J452/J552. CS 560 Database Management Systems Design (3 cr) See CS J460/J560. CS 570 Artificial Intelligence (3 cr) See CS J470/J570. CS 572 Evolutionary Computation (3 cr) See CS J472/J572. CS 576 Data Mining Topics and Techniques (3 cr) This course will focus on the development of relevant tools, methods, and design of Knowledge from Data (KDD) Systems. Further, it will concentrate on the design and implementation of an advanced data mining system with expectations of optimal performance and flexibility. Prereq: Graduate Standing or Permission CS 578 Neural Network Design (3 cr) See ECE 578. CS 580 Graduate Project (1-6 cr, max 6) Application of formal design and documentation techniques to the development of computer programming project; project selected in consultation with student's major professor. Prereq: CS 383, CS 480 or Permission CS 599 (s) Non-thesis Master's Research (cr arr) Research not directly related to a thesis or dissertation. (There is a limit on the number of credits in 599 that can be included on a study plan.) Prereq: Permission CS 600 Doctoral Research and Dissertation (cr arr)

6 6 Index INDEX C Computer Science (B.S.C.S.) 1 Computer Science Academic Minor Requirements 2 Computer Science Courses 3 Computer Science Graduate Academic Certificates Requirements 2 Computer Science Graduate Degree Programs 2 Computer Science Minor 2 Computer Science Undergraduate Curricular Requirements 1 COMPUTER SCIENCE, DEPARTMENT OF 1 S Secure and Dependable Computing Systems Graduate Academic Certificate 2