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2017-2018 Graduate Bulletin

Department of

Computer Science

College of Arts and Sciences

Web Page: http://www.cs.fsu.edu/

Chair: Xin Yuan; Professors: Aggarwal, Sudhir; Burmester, Mike; Hawkes, Lois; Liu, Xiuwen; Mascagni, Michael; Tyson, Gary; van Engelen, Robert; Whalley, David; Yuan Xin; Associate Professors: Duan, Zhenhai; Kumar, Piyush; Schwartz, Daniel; Srinivasan, Ashok; Wang, An-I (Andy); Yu, Weikuan; Zhang, Zhenghao; Assistant Professors: Ackerman, Margareta; Haiduc, Sonia; Wang, Zhi; Yang, Jie; Zhao, Peixiang; Courtesy Professors: Baker, Theodore; De Medeiros, Breno; Jones, Faye; Lacher, Chris; Levitz, Hilbert; Li, Feifei; Oral, Hakki Sarp; Pakin, Scott; Wang, Xiaoguang; Computing Resources Manager: Wang, Yu; Teaching Faculty 1: Carnahan, Caitlin; Vastola, Melina; Teaching Faculty III: Gaitros, David; Langley, Randolph; Myers, Robert; Professors Emeriti: Baker, Theodore; Lacher, Chris; Levitz, Hilbert

In Computer Science education, whether graduate or undergraduate, being current is essential. Computer Science is an exceptionally fast-moving field, where knowledge is subject to rapid obsolescence and ideas progress swiftly from research to practice. The department, therefore, seeks to offer technical instruction that keeps on the cutting edge of new developments, while simultaneously providing each student with a core of intellectual tools that will never become obsolete. The department views skills in communication, mathematics, and algorithmic reasoning as central and the understanding of underlying principles as more important than familiarity with specific technical products. Still, direct hands-on experience is essential to mastering these skills and principles. If students are to be adequately prepared for careers in Computer Science, they should have extensive experience with machines and software that are state-of-the-art.

The Department of Computer Science offers graduate programs leading to the Master of Science (MS) and Doctor of Philosophy (PhD) degrees. The department has a number of active research programs in:

  1. core disciplines such as programming languages, compilers, real-time systems, networks, parallel computation, databases, fault tolerance, and foundations;
  2. scientific and engineering applications areas, including scientific problem solving environments and large-scale scientific computation and databases;
  3. offensive and defensive security for computers and networks, cryptography; and
  4. other areas including but not limited to: random number generation, software maintenance, cloud computing, big data, mobile programming, neural networks, expert networks and fuzzy sets and systems.

These research programs enjoy external support from agencies ranging from the National Science Foundation to the private sector.

The Department of Computer Science has a full range of computing facilities available for a variety of instructional and research needs. Faculty and graduate students share high-performance workstations, file servers, and compute servers. Students and faculty whose research requires higher computational power have access to a variety of state-of-the-art machines, including supercomputers and computer clusters, across the University.

Other affiliated research laboratories include the following:

The Center for Security and Assurance in Information Technology (C-SAIT) Laboratory is dedicated to synthesis of education and research through the combined focus on theory and application of information security techniques. The center and FSU were recognized by NSA and DHS as a National Center of Academic Excellence In Research (CAE-R) in 2009.

The Architecture and Compilers for Embedded Systems (ACES) Laboratory investigates a wide variety of issues related to embedded systems architecture. Tools are constructed to assist compiler writers in optimization and retargeting.

The Center for Applied Vision and Imaging Sciences (CAVIS) conducts research motivated by psychophysical data and neurophysiological findings to develop models for real-world problems.

The Large-Scale Experimental Network and Systems Laboratory investigates issues related to QoS routing, communication algorithms, and message passing libraries.

The E-Crime Investigative Technologies Laboratory conducts research in the areas of cybersecurity and cybercrime.

The Parallel Architecture and Systems Laboratory (PASL) conducts a broad range of research related to topics in novel architecture and system technologies for big data analytics, cloud computing, high-performance, parallel and distributed processing, computer and network systems, and the use of technologies for fast scientific discoveries on computational biology and climate change.

Other active research groups subjects include the following: brain imaging, realistic illumination, Web-based 3D simulation, tools for distributed applications, tools for weather forecasting, probabilistic networks, knowledge-based management decision tools, random number generation, Monte Carlo and Quasi-Monte Carlo methods, grid-based computing, POSIX/Ada Real-time systems, application of fuzzy relations and non-classical logics, modeling and simulation environments.

Requirements

Please review all college-wide degree requirements summarized in the “College of Arts and Sciences” chapter of this Graduate Bulletin.

Please refer to http://www.cs.fsu.edu/admissions/graduate-admissions/ for the most current information.

A student who proposes to do graduate work in the department is required to take the aptitude test of the Graduate Record Examinations (GRE).

Unless specifically admitted into the part-time graduate program, all students are required to maintain full-time enrollment (excluding Summers) in courses related to their program of studies throughout the entire program of study. The student must receive a grade of “B–” or better on all graduate courses counting toward the graduate degree. All work for the master’s degree, including any transferred credit, must be completed within seven calendar years of the date of graduation.

All candidates for doctoral degrees in the department are required to participate in teaching activities at some time during their graduate careers unless waived by the department chair. All students are required to complete an exit survey for both the Department of Computer Science and the College of Arts and Sciences during their term of graduation.

Master’s Degree

MS in Computer Science

The department offers three majors at the master’s level: Computer Science, Computer Network and System Administration, and Cyber Security. Each major offers thesis, project, and course-based options.

Eligible PhD students wishing the MS must have the intention of continuing their PhD program and must first pass the PhD Qualifying Exam, CIS 8962, before applying for the MS. Both the Computer Science and Cyber Security majors have the following prerequisite requirements prior to being admitted to PhD in Computer Science and the MS majors of the Computer Science degree in the two aforementioned options:

Undergraduate Prerequisites for the MS/PhD in Computer Science and SM in Cyber Security degree options:

CDA 3100 Computer Organization (3)

CDA 3101 Computer Organization II (3)

COP 3330 Object Oriented Programming in C++ (3)

COP 4530 Data Structures, Algorithms, and Generic Programming (3)

COP 4531 Algorithm Analysis (3)

COP 4610 Introduction to Operating Systems (3)

COT 4420 Theory of Computation (3)

MAC 2311 Calculus I (3)

MAC 2312 Calculus II (3)

MAD 2104 Discrete Math I (3)

MAD 3105 Discrete Math II (3)

STA 4442 Intro to Probability (3)

Undergraduate Prerequisites for the MS CNSA Degree Program

CDA 3100 Computer Organization (3)

CDA 3101 Computer Organization II (3)

COP 4530 Data Structures. Algorithms, and Generic Programming (3)

COP 4610 Introduction to Operating Systems (3)

In Computer Science and Cyber Security majors, a student must complete thirty-five semester hours in computer science courses numbered 5000 or above, including approved CIS 5930 and CIS 6930. At most one course outside the department at the 5000 or 6000 level can also count towards the thirty-five hours if approved by the major professor. Supervised teaching, supervised research, seminars, directed individual study and courses with prefix CGS are excluded. As part of the thirty-five semester hours each student is required to take CIS 5935, Introductory Seminar on Research (2). For the Computer Science and Cyber Security majors, at least one course from each of the following three core areas must be taken to satisfy the area requirements:

Software

COP 5570 Concurrent, Parallel, and Distributed Programming (3)

COP 5621 Compiler Construction (3)

COP 5725 Database Systems (3)

Systems

CDA 5155 Computer Architecture (3)

CNT 5505 Data and Computer Communications (3)

COP 5611 Advanced Operating Systems (3)

Theory

COT 5310 Theory of Automata and Formal Languages (3)

COT 5405 Advanced Algorithms (3)

COT 5507 Analytical Methods in Computer Science (3)

*The Computer and Network System Administration major does not require a Theory course. In addition to not requiring a Theory course, the CNSA major has the Software and Systems requirement fulfilled in its list of required courses. CNSA requirements are defined below.

Cyber Security Major

A student in the cyber security major is required to meet all the course requirements of the MS in Computer Science, but is also required to take the following courses; those marked with a “*” also satisfy the area requirements:

CIS 5370 Computer Security (3)

CIS 5371 Cryptography (3)

CNT 5412 Network Security, Active and Passive Defenses (3)

CNT 5505 Data and Computer Communications (3)

CNT 5605 Computer and Network Administration (3)

plus one of the following courses:

CDA 5140 Fault Tolerance and Reliability (3)

COP 5570 Concurrent, Parallel, and Distributed Programming (3)*

COP 5611 Advanced Operating Systems (3)*

COT 5310 Theory of Automata and Formal Languages (3)*

COT 5405 Advanced Algorithms (3)*

Computer Network and System Administration Major

CNSA students have to complete the aforementioned undergraduate prerequisites, before graduating, and the following required courses for the CNSA major of the MS in Computer Science degree:

Required Computer Science Courses for the MS CNSA Degree Program:

CDA 5155 Computer Architecture (3)

CNT 5412 Network Security, Active and Passive Defenses (3)

CNT 5505 Data and Computer Communications (3)

CNT 5605 Computer and Network Administration (3)

COP 5570 Concurrent, Parallel, and Distributed Programming (3)

COP 5611 Advanced Operating Systems (3)

In addition to the required courses, the CNSA program has an experience requirement, and students are required to complete system administration internship(s) to complete this requirement. The CNSA program works with various departments and colleges on the FSU campus to provide local systems administration internships for students.

Thesis, Project, and Course-Based Master of Science (MS) Degrees

For each major of the previously mentioned major options in the MS in Computer Science degree, a student must select one of the three options (thesis, project, or course-based) to complete the degree. Each option has a specific number of required courses as well as other requirements, as described below.

Thesis Option

In any major, a student under the thesis option must take, in addition to CIS 5935, Introductory Seminar on Research (2), eight courses (twenty-four semester hours) at or above the 5000 level, plus at least nine semester hours of CIS 5970r, Thesis. At most, nine semester hours of CIS 5970r may be counted toward the required thirty-five semester hours for the Master of Science (MS) degree. The eight courses must include at least one course from each core area as described above. Approved CIS 5930/6930 courses are counted among these, but supervised teaching, supervised research, seminars, directed individual study (DIS), and CIS 5915 may not be included. The thesis is defended by registering for CIS 8976, Master’s Thesis Defense (0).

The student in the thesis option is required to propose and create an individual thesis topic of appropriate focus, size and complexity and to write a document discussing it. The thesis is to be written in accordance with the University standards. Upon completion, a thesis must be defended successfully to the department in an open forum and be approved by the major professor and supervisory committee. An electronic version of the thesis must be submitted to the Graduate School, the CS graduate coordinator, and the CS webmaster.

Project Option

In any major, a student under the project option must take, in addition to CIS 5935, Introductory Seminar on Research (2), nine courses (twenty-seven semester hours) at or above the 5000 level, plus at least six semester hours of CIS 5915r, Graduate Software Project. At most six semester hours of CIS 5915 may be counted toward the required thirty-five semester hours for the Master of Science (MS) degree. The nine courses must include at least one from each of the core areas described above. Approved CIS 5930/6930 courses are counted among these, but supervised teaching, supervised research, seminars, directed individual study (DIS), and CIS 5970 may not be included. The student also must register for CIS 8974, Master’s Project Defense (0), to defend the project. An electronic version of the project must be submitted to the CS graduate coordinator and the CS webmaster.

Course-Based Option

In any major, a student under the course-based option must take, in addition to CIS 5935, Introductory Seminar on Research (2), eleven courses (thirty-three semester hours) at or above the 5000 level, including at least one course from each of the three core areas detailed above. A student must earn a “B+” or higher for at least six of the eleven courses in order to graduate under the course-based option. Approved CIS 5930/6930 courses count toward the eleven-course requirement, but supervised teaching, seminars, directed individual study (DIS), supervised research, CIS 5915 and CIS 5970 may not be included. A student must also register for CIS 8966, Master’s Comprehensive Examination (0) the semester of graduation.

Supervisory Committee

For the thesis and project options, it is the student’s responsibility to form a supervisory committee regardless of his or her selected major. No later than the beginning of work on the thesis or project, the student must secure the consent of an eligible computer science faculty member to serve as the major professor. In consultation with the major professor, the student must secure the consent of at least two additional graduate faculty members to serve as the supervisory committee, chaired by the major professor.

MS in Computer Criminology Degree

The initial track for the MS CC degree is coursework only. The general degree requirements include four graduate criminology courses and seven graduate computer science (CS) courses related to information assurance and computer security for a total of thirty-three hours.

In addition, MS CC students have to complete certain undergraduate prerequisites, shown below, before graduating, and will likely have to complete a subset of these courses before being admitted to the MS CC degree program. Note that CIS 4385 is required for the FSU BS in Computer Criminology and the other four courses are required for the FSU BS in Computer Science and BA in Computer Science degrees.

Undergraduate Prerequisites for the MS CC Degree Program:

CDA 3101 Computer Organization II (3)

CIS 4385 Cybercrime Detection and Forensics (3)

COP 4530 Data Structures, Algorithms and Generic Programming (3)

COP 4610 Operating Systems and Concurrent Programming (3)

COP 4710 Theory and Structure of Databases (3)

The graduation requirements include completing all of the undergraduate prerequisites, completing four graduate criminology courses, and completing seven graduate computer science courses. The graduate courses for the MS CC degree are listed below:

Criminology Courses for the MS CC Degree Program (Students must take at least three):

CCJ 5016 Crimes of the Powerful (3)

CCJ 5285 Survey of Criminal Justice Theory and Research (3)

CCJ 5606 Survey of Criminological Theories (3)

CCJ 5607 History of Criminological Thought (3)

CCJ 5636 Comparative Criminology and Criminal Justice (3)

Course descriptions for the above criminology courses are available at: http://www.criminology.fsu.edu/p/academic-syllabi.php.

Required Computer Science Courses for the MS CC Degree Program:

CIS 5370 Computer Security (3)

CNT 5412 Network Security, Active and Passive Defenses (3)

CNT 5505 Data and Computer Communications (3)

CNT 5605 Computer and Network Administration (3)

COP 5611 Advanced Operating Systems (3)

COP 5725 Database Systems (3)

One of the required four criminology courses can be a graduate criminology elective and one of the seven required computer science courses can be a graduate computer science elective. The four criminology courses can be taken in any order as none of these courses are prerequisites for any of the other courses. However, the six required graduate computer science courses each have undergraduate prerequisites that must be completed before the student will be allowed to take these courses.

Doctoral Degree

The Doctor of Philosophy is regarded as a research degree and is awarded on the basis of accomplishment in a recognized specialty in computer science. Such accomplishment should include scholarly mastery of the field, significant contributions to new knowledge in the field, and written and oral communication skills appropriate for the field.

The requirements for the PhD include the following: passing CIS 8962, the qualifying examination (portfolio defense), and CIS 8964, preliminary examination (area survey); satisfaction of the course requirements; successfully defending a dissertation prospectus; and successfully defending a dissertation. All candidates for doctoral degrees in the department are required to participate in teaching activities at some time during their graduate careers unless waived by the department chair. Additionally, each doctoral student must complete at least one oral research presentation which is critiqued by at least one faculty member. This can be at the departmental research conference, or any discipline-related conference.

Course Requirements

Doctoral students must complete six core courses (eighteen hours), two courses in each of the three areas (Software, Systems, and Theory). Equivalent courses taken at other institutions must be approved by the Portfolio Evaluation Committee (PEC). Additionally the student must complete CIS 5935 Introductory Seminar on Research (2).

Students entering the program after earning a master’s degree in Computer Science or related area must take at least four additional courses (twelve hours) beyond those taken for the MS degree, at the 5000 or 6000 level, as advised by the student’s major professor and supervisory committee. These courses must be taken at FSU and a maximum of two courses (six hours) may come from outside of the department that were not previously used in the completion of a previous degree. Core courses can also be used to meet this “four additional courses” requirement provided they are taken at FSU and were not completed as part of an MS program. Supervised Teaching, Supervised Research, DIS and courses with prefix CGS do not count towards this requirement.

Students entering the program after earning a bachelor’s degree in computer science or related area must take at least ten courses (thirty hours) at the 5000 or 6000 level, as advised by the student’s major professor and supervisory committee. Six of these courses (eighteen hours) must meet the PhD core course requirement. The remaining four courses (twelve hours) must be taken at FSU and cannot be part of an MS degree program outside of the FSU Computer Science Department. A maximum of two courses (six hours) may come from outside of the Computer Science Department. Supervised teaching, supervised research, DIS, and courses with prefix CGS do not count towards this requirement that were not used in the attainment of a previous degree.

The student’s PhD committee can require the student to take more than the aforementioned number of courses. The student must receive a grade of “B–” or better on all graduate courses taken to satisfy the minimum course requirements of the degree. Once these minimum requirements are met, however, it is permissible to take any subsequent courses on an S/U basis.

The doctoral student must also complete at least twenty-four hours of CIS 6980r Dissertation. A student may enroll in CIS 6980r only after being admitted to candidacy. Once admitted to candidacy, students must be enrolled for a minimum of two dissertation hours each semester until completion of the degree. The student must graduate with the doctoral degree within five years of being admitted to doctoral candidacy.

Major Professor and Supervisory Committee

As early as is feasible in the student’s program, the student should identify an area for dissertation research and secure an informal agreement with a faculty member to serve as the student’s major professor. This agreement should include an understanding as to the area and timeline of the dissertation research. This agreement is formalized when the department chair appoints that faculty member to serve in this capacity. In a similar manner the student must secure agreements with, and the chair must approve, the remaining members of the student’s supervisory committee. This committee must consist of: one additional faculty member of the department; and one member of the graduate faculty in another department as the University Representative. In addition, the chair will appoint a member to serve as departmental representative. All members must hold graduate faculty status and the University Representative must be a tenured member of the faculty.

The supervisory committee is responsible for approving an individual program of study, possibly including additional course requirements, and verifying that the student satisfies the following departmental requirements. The area examination, prospectus, and dissertation defenses must be unanimously approved by the major professor and supervisory committee.

Qualifying Examination (Student Portfolio Defense)

The PhD Portfolio is intended to provide the department with a complete view of the student’s accomplishments and abilities that relate to likelihood of success as a PhD professional. The portfolio is reviewed regularly by the Portfolio Evaluation Committee to determine whether the student is making suitable progress towards the degree, and must be completed with a list of the satisfactory grades (“B” or higher) for the six core graduate courses when the student takes the Doctoral Qualifying Exam. Based on the completion of the portfolio, a student can enroll in CIS 8962 Doctoral Qualifying Exam. A passing grade “P” for the CIS 8962 Doctoral Qualifying Exam is one of the two required components of admission to candidacy.

The student should be enrolled in CIS 8962 Doctoral Qualifying Exam when he or she has completed the six core graduate courses, completed the portfolio, and both the student and major professor agree that the student is ready to take the Doctoral Qualifying Exam. (Doctoral Qualifying Exams may be scheduled for Fall or Spring semester, but not Summer semester). The Portfolio Evaluation Committee will schedule and conduct the Doctoral Qualifying Exam during the semester. The exam will be oral and will cover the six core graduate courses taken by the student. The student will be tested on the six core graduate course topics. The student is strongly advised to study the core course topics well in advance in preparation for the Doctoral Qualifying Exam. Students that obtain an “A” in any of the core subjects will be exempt from that portion of the oral exam. If a student gets all “A”’s in the six core classes used for the Qualifying Exam, that student will still need to submit a copy of the portfolio to the Portfolio Review Committee.

All students admitted to the program but not yet admitted to candidacy, are required to compile and keep current a portfolio containing information relevant to the student’s progress in the program. Required contents of the portfolio, submission dates, and guidelines for preparing the portfolio are at http://www.cs.fsu.edu/academics/graduate-programs/portfolio/.

A student cannot take the Doctoral Qualifying Exam if he or she has not completed the six core graduate courses. However, there is one exception to this rule. A student who has received satisfactory grades with a cumulative GPA of 3.5 or higher for all but one of the core courses can take the Qualifying Exam in the Spring term in which the last core course is being taken, assuming that the Qualifying Exams take place after spring break. In that case, the student is expected to be able to answer questions about all of the six core courses, including the core course currently being taken. If the student passes the oral, the exam is not recorded as passed until after the end of the term, and the chair of the Portfolio Evaluation Committee has verified that the remaining core course has been passed with an acceptable grade.

The portfolio of any student not yet in candidacy is reviewed annually by the departmental Portfolio Review Committee (PRC). This committee consists of a core that is appointed by the Department Chair and normally meets in the Spring. Feedback to the student on the contents of the portfolio and on progress toward admission to candidacy is provided after each review.

The final review occurs in conjunction with the defense of the portfolio. Thus, when a student and his or her major professor agree the portfolio is complete, the student should register for the Doctoral Qualifying Exam, CIS 8962 (0) for the next semester. At most, students can take the Qualifying Exam twice. A student either passes or fails; there is no conditional pass.

Preliminary Examination (Area Survey)

The preliminary examination (area survey) CIS 8964 covers the student’s intended area of research. It has both written and oral parts. Both parts of the examination are conducted by the student’s supervisory committee, which may delegate the responsibility to a larger area committee. It is strongly recommended that the student write an area survey paper as part of this exam. The oral part is open to all department faculty members having doctoral status who elect to participate. The oral part of the examination is held in an open forum that other students are invited to attend and is followed by a closed session if the committee so desires. Students who do not pass the area exam may be advised to retake it at a later time. A student who changes to a new research area after having previously passed this exam will be required to stand for a further exam over the new area. At most, a student can fail the exam once.

Normal expectations are that the portfolio defense occurs prior to taking the area exam or at least in the same semester as the area exam. A doctoral student should take the area exam within two semesters (including summer) of passing the Qualifying Exam.

Admission to Candidacy

In order to be advanced to candidacy for the doctoral degree, the student must:

  • pass CIS 8962, the qualifying examination, which consists of passing the defense of the portfolio and completion of the six core course with a grade of “B” or better
  • pass CIS 8964, the preliminary exam, which consists of passing the area examination
  • complete the admission to candidacy form located at the registrar’s Web site (http://registrar.fsu.edu/services/images/admiss_to_candidacy.pdf).

Prospectus

The student must formally propose the research to comprise the dissertation to his or her supervisory committee in the form of a prospectus. The prospectus should consist of much of the background work for the dissertation, including:

  1. A thorough literature review
  2. Theory, preliminary computational results, and/or bases for the feasibility of the research
  3. A proposal for research to be completed for the dissertation

In addition, as an appendix to the prospectus, publication plans should be presented. The research proposed should make clear and substantial advances in the state of knowledge in computer science, and the publication plans should be designed to affirm the quality and nature of the research. Publication should be in nationally recognized conferences and journals in the field. The prospectus must be successfully defended before the student’s supervisory committee in an open meeting.

Dissertation

After completing the research proposed in the prospectus, the student must write a dissertation. The dissertation represents the fulfillment of the proposals made in the prospectus. The dissertation document must comply with all current University standards for style. The dissertation must be successfully defended before the student’s committee in an open meeting. The dissertation must be successfully defended within five years of passing the preliminary exam (CIS 8964). An electronic version of the dissertation must be submitted to the university as well as the CS webmaster and CS graduate coordinator.

Definition of Prefixes

CAP—Computer Applications

CDA—Computer Design/Architecture

CEN—Computer Software Engineering

CGS—Computer General Studies

CIS—Computer Science and Information Systems

CNT—Computer Networks

COP—Computer Programming

COT—Computing Theory

ISC—Interdisciplinary Sciences

Graduate Courses

CAP 5415. Principles and Algorithms of Computer Vision (3). Prerequisite: COP 4530. This course examines the basic computational principles and algorithms to extract information from images and image sequences. Topics include imaging models, linear and nonlinear filtering, edge detection, stereopsis and motion estimation, texture modeling, segmentation and grouping, and deformable template matching for recognition.

CAP 5605. Artificial Intelligence (3). Prerequisite: COP 4530. This course is an introduction, representing knowledge, controlling attention, exploiting constraints, basic LISP programming, basic graph searching methods, game-playing and dealing with adversaries, understanding vision, theorem proving by computer, computer programs utilizing artificial intelligence techniques.

CAP 5638. Pattern Recognition (3). Prerequisites: Knowledge of probability and at least one programming language. This course explores applications of mathematical tools, in particular, probabilistic, algebraic, and linguistic tools, to problems in pattern recognition and classification. Feature selection procedures, syntactic pattern recognition. Applications of fuzzy set theory to pattern recognition and classification.

CAP 5726. Introduction to Computer Graphics (3). Prerequisite: COP 4530. This course covers fundamental principles and algorithms underlying computer graphics, and also provides a brief introduction to openGL. The course is intended for computer-science graduate students who are interested in computer-graphics related careers or in learning and applying computer-graphics techniques.

CAP 6417. Theoretical Foundations of Computer Vision (3). Prerequisite: CAP 5415. This course covers theoretical foundations of computer vision. By formulating vision as an inference process, approaches to vision are presented and analyzed systematically. Topics include Marr’s computational vision paradigm, regularization theory, Bayesian inference framework, pattern theory, and visual learning theories.

CDA 5125. Parallel and Distributed Systems (3). Prerequisite: COP 4610. This course introduces various systems aspects of parallel and distributed computing. Topics include parallel computer architectures, interconnects, parallel programming paradigms, compilation techniques, runtime libraries, performance evaluation, performance monitoring and tuning, as well as tools for parallel and distributed computing.

CDA 5140. Fault Tolerance and Reliability (3). Prerequisite: CDA 5155. This course covers basic definitions; self-checking circuits; error detection measures; interconnection networks; test generation and testability; distributed fault tolerance systems; software fault tolerance; fault tolerance and VLSI; error recovery.

CDA 5155. Computer Architecture (3). Prerequisite: CDA 3101. This course focuses on computer system components; microprocessor and minicomputer architecture; stack computers; parallel computers; overlap and pipeline processing; networks and protocols; performance evaluation; architecture studies of selected systems.

CEN 5000. Knowledge Management and Data Engineering (3). Prerequisite: COP 5710. This course is a survey of techniques and tools representing the transition from database management to knowledge management; database architecture and models; fuzzy databases; construction of knowledge bases.

CEN 5035. Software Engineering (3). Prerequisites: CEN 4021, COP 4020, and COP 4531. This course surveys software engineering and a detailed study of topics from requirements analysis and specification, programming methodology, software testing and validation, performance and design evaluation, software project management, and programming tools and standards.

CEN 5055. Project Development (3). Prerequisite: CEN 5035. This course deals with the planning, design, validation and implementation of a large scale project using IEEE deliverables, state-of-the-art software engineering techniques, and analysis and design project reviews and evaluations prior to implementation in the Graduate Software Project.

CEN 5064. Advanced Software Design (3). Prerequisites: CEN 5035. This course concentrates on the design of software systems after requirements engineering has been completed. The course offers education in techniques such as architectural design, pattern integration, and refactoring’s.

CEN5526.Wireless and Mobile Computing (3). This course introduces students to the design, implementation, and analysis of mobile systems and applications in various domains, including urban sensing, mobile healthcare monitoring, security and privacy, location-aware services, and vehicular computing. Integral to the course are the course projects in which students develop mobile applications on mobile devices. Through the course projects, students gain hands-on experience on building mobile applications and validate their research ideas in practice.

CGS 5267. Principles of Computer Organization (3). (S/U grade only). Corequisites: COP 3330 and MAD 2104. This course is for graduate non-majors and graduate majors needing foundational work in computer science; credit may not be applied toward a graduate degree in computer science. Basic computer structure and design, register transfer and micro operations, central processor organization, microprogramming, arithmetic processor design, input-output, memory organization, virtual memory, microprocessors and microcomputer architecture.

CGS 5268. Principles of Computer Organization II (3). (S/U grade only). Prerequisite: CDA 3100 or CGS 5267. This course explores fundamental concepts in processor design, including data path and control, pipelining, memory hierarchies, and I/O.

CGS 5409 Object-Oriented Programming in C++ for Non-majors (2). Prerequisite: COP 3014 or a comparable course in C or C++ Programming. Pre- or corequisite: COP 3353. In this course, topics include basics of C++ language, objects and classes, programming with classes, constructors and destructors, dynamic memory allocation, function and operator overloading, master classes, the class iostream, base and derived classes, and templates. May not be applied toward a degree in computer science.

CGS 5425. Object-Oriented Programming with Data Structures (3). (S/U grade only). Prerequisites: COP 3330 and MAD 2104. Pre- or corequisite: CDA 3100. This course is for graduate non-majors and graduate majors needing foundational work in computer science; credit may not be applied toward a graduate degree in computer science. Structured and object-oriented programming; invariant relations, stepwise refinement; text processing, internal sorting methods, linear tables, pointers and linked data structures, recursive programming and recursion elimination, sequential file processing; trees and graphs; program verification and running time analysis; application of concepts through programming projects.

CGS 5426. Programming Language Concepts (3). (S/U grade only). Corequisite: COP 4530. This course is for graduate non-majors and graduate majors needing foundational work in computer science; credit may not be applied toward a graduate degree in computer science. A survey of programming languages and language features and an introduction to compilers. Languages to be discussed include FORTRAN, Pascal, Ada, PL/1, APL, and LISP. An oral presentation is required.

CGS 5427. Algorithm Design and Analysis (3). (S/U grade only). Prerequisites: COP 4530, MAD 3105, or MAD 3107. Corequisite: STA 4442, STA 4321 or STA 3032. This course is for graduate non-majors and graduate majors needing foundational work in computer science; credit may not be applied toward a graduate degree in computer science. Techniques for the analysis of computer algorithms; examples of well-designed algorithms and associated data structures; principles of algorithm design and application of programming projects.

CGS 5428. Relational Database Theory (3). (S/U grade only). Prerequisite: COP 3330 and MAD 2104. This course is for graduate non-majors and graduate majors needing foundational work in computer science; credit may not be applied toward a graduate degree in computer science. Basic file organization methods, indexed files, multi-key processing; architecture of database management systems; relational, hierarchical network, and semantic database models; normalization, distributed databases and file systems; practical use of a DBMS and the building of a database application.

CGS 5429. Introduction to Computer Theory (3). (S/U grade only). Prerequisite: MAD 3105. This course is for graduate non-majors and graduate majors needing foundational work in computer science; credit may not be applied toward a graduate degree in computer science. Regular expressions; regular, context-free, context-sensitive, and unrestricted grammars; foundations of language theory; finite automata and linear grammars; pushdown automata; Turing machines and non-solvability.

CGS 5466. Programming for Non-Majors (3). (S/U grade only). Prerequisite: MAC 1140. This course examines fundamental concepts and skills of programming in a high-level language. Flow of control topics such as sequence, selection, iteration, and subprograms are covered. Data structures topics such as arrays, strings, structs, and ADT lists and tables are also covered, along with algorithms using selection and iteration (decision making, finding maxima and minima, basic searching and sorting, simulation, etc). Good program design using a procedural paradigm, structure, and style are emphasized.

CGS 5765. Principles of Operating Systems (3). (S/U grade only). Prerequisites: CDA 3101 and COP 4530. This class if for graduate non-majors and graduate majors needing foundational work in computer science; credit may not be applied toward a graduate degree in computer science. Design principles of batch multi-programming and time-sharing operating systems. Linking, loading, input-output systems, interacting processes, storage management, process and resource control, file systems.

CGS 5935r. Special Topics in Computer Science for Non-Majors (1–3). (S/U grade only). Prerequisite: Instructor permission. This special-topics course is intended for non majors. Topics may vary. May be repeated within the same term, to a maximum of three semester hours.

CIS 5105. Computer Systems Performance Analysis (3). Prerequisite: COP 4610, MAD 3105, and STA 4442. This course covers empirical, simulation, and analytical methods to evaluate computer systems. The emphasis is on the empirical methods. Through the course project, the students gain experience measuring and evaluating a system using proper experimental design, metrics, workloads, and statistical analysis techniques.

CIS 5370. Computer Security (3). Prerequisites: COP 4610. In this course, topics include computer security threats and attacks, covert channels, trusted operating systems, access control, entity authentication, security policies, models of security, database security, administering security, physical security and TEMPEST, and brief introductions to network security and legal and ethical aspects of security. A research paper or project is required.

CIS 5371. Cryptography (3). Prerequisite: MAD 3105. This course addresses issues of modern cryptography covering theory and practice. Algorithms such as the RSA, ElGamal, and the Digital Signature Standard are covered in depth.

CIS 5900r. Directed Individual Study (1–9) (S/U grade only). May be repeated to a maximum of twenty-seven semester hours.

CIS 5910r. Supervised Research (1–5). (S/U grade only). This course cannot be applied to the master’s degree. May be repeated to a maximum of five semester hours.

CIS 5915r. Graduate Software Project (1–12). (S/U grade only). A minimum of six semester hours of credit is required for project option MS students.

CIS 5920r. Colloquium (1). (S/U grade only). This course consists of a series of lectures given by faculty and visiting computer scientists. May be repeated up to a maximum of ten semester hours.

CIS 5930r. Selected Topics in Computer Science (1–3). May be repeated to a maximum of twelve semester hours.

CIS 5935. Introductory Seminar on Research (2). (S/U grade only). Prerequisite: Instructor permission. This seminar is a series of lectures given by faculty on the research being conducted by the Department of Computer Science. Other lectures include guidelines on the preparation of the doctoral portfolio, and on the use of library research tools.

CIS 5940r. Supervised Teaching (1–5). (S/U grade only). May be repeated to a maximum of five semester hours.

CIS 5949r. Internship in Computer Science (0–9). (S/U grade only). Prerequisite: COP 4610. This internship is a field placement in an approved industry or government entity having a significant information technology or computer science component. May be taken for variable credit and repeated with departmental approval. Credits do not count towards graduation. Successful completion requires satisfactory job evaluation and demonstration of educational value of placement via a paper. May be repeated to a maximum of thirty-six semester hours.

CIS 5970r. Thesis (1–12). (S/U grade only). A minimum of nine semester hours of credit is required for thesis option MS students.

CIS 6900r. Directed Individual Study (1–12). (S/U grade only). May be repeated to a maximum of twenty-four semester hours.

CIS 6930r. Advanced Topics in Computer Science (1–3). May be repeated to a maximum of twelve semester hours.

CIS 6935r. Advanced Seminar in Computer Science (1). This course is an advanced seminar in computer science. May be repeated, and duplicate registration allowed during the same term, for a total of twelve semester hours.

CIS 6980r. Dissertation (1–12). (S/U grade only).

CIS 8962r. Doctoral Qualifying Examination (0). (P/F grade only.) May be repeated twice at most.

CIS 8964. Preliminary Doctoral Examination (0). (P/F grade only.)

CIS 8966. Master’s Comprehensive Examination (0). (P/F grade only.)

CIS 8974. Master’s Project Defense (0). (P/F grade only.)

CIS 8976. Master’s Thesis Defense (0). (P/F grade only.)

CIS 8985. Dissertation Defense (0). (P/F grade only.)

CNT 5412. Network Security, Active and Passive Defenses (3). Prerequisite: COP 4530. This course analyzes threats to computer networks, network vulnerabilities, techniques for strengthening passive defenses, tools for establishing an active network defense, and policies for enhancing forensic analysis of crimes and attacks on computer networks. Topics include private and public key cryptography, digital signatures, secret sharing, security protocols, formal methods for analyzing network security, electronic mail security, firewalls, intrusion detection, Internet privacy, and public key infrastructures. A research paper or project is required.

CNT 5415. Applied Computer and Network Security (3). In this course, students familiarize themselves with current and emerging threats to the security of computer systems and networks, including viruses, worms, and network intrusion; and with techniques for the prevention, detection, and recovery from such attacks, such as firewalls, intrusion detection systems, secure coding practices, and others. Attack and defense mechanisms are studied in a systematic way to develop students’ practical and analytical skills to identify and correct or mitigate threats to computer systems and networks.

CNT 5505. Data and Computer Communications (3). Prerequisites: CDA 3101 and COP 4610. This course offers an overview of networks; data communication principles; data link layer; routing in packet switched networks; flow and congestion control; multiple access communication protocols; local area network protocols and standards; network interconnection; transport protocols; integrated services digital networks (narrowband and broadband); and switching techniques and fast packet switching

CNT 5529. Wireless Networking (3). This course is intended to cover a wide spectrum of topics on wireless networks, including the physical layer, the medium access control layer, and the network layer. The focus is on understanding, implementing, and experimenting with various wireless networking technologies in different layers with software.

CNT 5605. Computer and Network Administration (3). Prerequisite: COP 4610. This course covers UNIX user commands and shell programming. Also covered are problem solving and diagnostic methods, system startup and shutdown, device files and installing devices, disk drives and file systems, NFS, NIS, DNS, sendmail. Students also learn how to manage a WWW site, manage UNIX software applications, system security, and performance tuning. Legal and professional issues, ethics and policies are covered.

COP 5385. Reactive Systems and Hierarchical State Machines (3). Prerequisites: COP 4530 and COP 4610. This course covers the theory of hierarchical state machines (HSM) and the use of HSM to model and implement reactive systems (RS). Implementations of HSM in C, C++, and Java are explored. HSM are applied for modeling and implementing RS, including real-time, multi-threaded, and embedded systems. Selected articles from the rapidly expanding literature and an advanced project are included. Permission of instructor required for students with credit for CEN 4xxx.

COP 5517. Generic Programming (3). Prerequisite: COP 4530. This course covers all fundamental aspects of generic programming, including generic algorithms, generic iterators, as well as function and predicate objects. Examples are drawn from the FSU and STD template libraries, while techniques for extending these support libraries are covered in the context of a template-graph library. Policy-based design is then used to create generic implementations of several design-pattern implementations, including singleton, smart pointer, and abstract factory.

COP 5570. Concurrent, Parallel, and Distributed Programming (3). Prerequisite: COP 4610. This course covers UNIX and C standards, file I/O, file access and attributes, directories, the standard I/O library, systems administration files, the process environment, process control, process relationships, signals, terminal I/O, daemon processes, interprocess communication, and pseudo terminals.

COP 5611. Advanced Operating Systems (3). Prerequisites: CDA 3101, COP 4610, and introductory probability or statistics. This course focuses on design principles of batch, multiprogramming, and time-sharing systems; distributed systems; problems of concurrency.

COP 5621. Compiler Construction (3). Prerequisites: CDA 3101, COP 4020, and COT 4420. This course serves as an introduction to compiling, elements of language theory, syntax-directed translation, lexical analysis, symbol tables, LR(k) parsing, intermediate code generation, code optimization, code generation, error detection and recovery. There are a number of significant programming projects in this course.

COP 5641. Kernel and Device Driver Programming (3). Prerequisites: COP 4610 and COP 5570, or instructor permission. This course covers internals of the Linux operating system kernel, including virtual and physical memory management, scheduling, and device drivers. Focus is also placed on kernel modules, hardware interfaces, char and block devices, kernel debugging, interrupt handling, and memory mapping. Laboratory exercises include modifying example modules and project developing a new device driver.

COP 5642. RealTime Systems Theory and Practice (3). Prerequisites: COP 4610 or 5570. This course addresses the theoretical foundations and practical techniques for the design and implementation of real-time computer systems. Topics include applicable scheduling theory, the use of computers for controlling real-time processes and the use of real-time operating system. Laboratory work includes writing software to control a physical device with hard-timing constraints and analysis of scheduling performance by simulation. A term project and report are required.

COP 5659r. Mobile Programming (3). Prerequisite: COP 4530. This course teaches students how to program mobile devices. Students use event-based models to write and deploy an intent based application using a mobile computing software framework. May be repeated to a maximum of nine semester hours.

COP 5725. Database Systems (3). Prerequisites: COP 4610 and COP 4710. This course examines the use of a generalized database management system; characteristics of database systems; hierarchical, network, and relational models; file organizations.

COP 5818. Distributed Applications Development (3). Prerequisite: COP 3252. This course analyzes programming of distributed Web applications using Java database connectivity, servlets, Java server pages, remote method invocation, and enterprise Java beans (both session and entity beans); use of the Sun Microsystems Java 2 Enterprise Edition development platform either directly or through an integrated development environment such as IBM’s Websphere.

COP 6622. Advanced Topics in Compilation (3). Prerequisite: COP 5621. This course covers attribute grammars and attribute grammar processors, formal methods of semantic analysis, generalized tree transformers, code selection, analysis and optimization, as well as error analysis and recovery.

COT 5310. Theory of Automata and Formal Languages (3). Prerequisites: COP 4020 and COT 4420. This course examines normal models of computation; automata; formal languages, their relationships, decidable and undecidable problems.

COT 5315. Programming Language Foundations (3). Prerequisites: COP 4020 and MAD 3105. In this course, topics include conceptual subtleties in programming languages; formal specification of syntax and semantics; and issues in the design and implementation of programming languages.

COT 5405. Advanced Algorithms (3). Prerequisite: COP 4531. This course covers algorithms, formal proofs of correctness, and time complexity analysis for network flow problems, approximation of NP hard combinatorial optimization problems, parallel algorithms, cache-aware algorithms, randomized algorithms, computational geometry, string algorithms, and other topics requiring advanced techniques for proof of correctness or time/space complexity analysis.

COT 5507. Analytic Methods in Computer Science (3). Prerequisite: COP 4531. This course teaches computer science students the fundamental discrete mathematics required for serious graduate work in algorithms and theoretical computer science. It specifically covers topics in recurrent problems, sums, integer functions, elementary number theory, binomial coefficients, special numbers, and generating functions.

COT 5540. Logic for Computer Science (3). Prerequisite: COT 4420. This course examines syntax, semantics, and proof theory of propositional logic and first order languages; prenex normal form; Gentzen systems; resolution for propositional logic; elements of PROLOG and program verification.

COT 5715. Random Number Generation (3). Prerequisite: COP 4531. This course provides a graduate-level examination of all aspects of random number generation as used in simulation; specifically, the course concentrates on pseudorandom number generation and quasi-random number generation theory and practice.

ISC 5228. Monte Carlo Methods (3). Prerequisites: ISC 5305, MAC 2311, and MAC 2312. This course provides an introduction to probabilistic modeling and Monte Carlo methods (MCMs) suitable for graduate students in science, technology, and engineering. It provides an introduction to discrete event simulation, MCMs and their probabilistic foundations, and the application of MCMs to various fields. In particular, Markov chain MCMs are introduced, as are the application of MCMs to problems in linear algebra and the solution of partial differential equations.

COMPUTER THEORY:

see Computer Science

CONSUMER AFFAIRS:

see Family and Child Sciences

COUNSELING PSYCHOLOGY AND HUMAN SYSTEMS:

see Educational Psychology and Learning Systems

CREATIVE WRITING:

see English