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Graduate Studies

Computer Systems and Software Design
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The Department of Mathematical, Computing and Information Sciences offers the Master of Science (MS) with a major in computer systems and software design with two concentrations.

Required Application Materials

Applicants for the MS with a major in computer systems and software design may be permitted to enroll for one semester of graduate course work, with the permission of the graduate coordinator of the program, while completing all general application requirements.

Applicants for the MS with a major in computer systems and software design must submit the following documentation to the College of Graduate Studies, Jacksonville State University, 700 Pelham Road North, Jacksonville, Alabama 36265-1602, to be considered for admission:

Completed JSU Graduate Application for Admission (http:/www.jsu.edu/graduate/grad_app.html)
Non-refundable $30.00 application processing fee
Official transcripts(s) from all postsecondary institutions attended. (Students who have previously attended JSU do not need to request a transcript from the University.)
Official tests scores on the GMAT or the General Test of the GRE (please refer to page 18 of this Bulletin). The GRE or GMAT must have been taken within five years of enrollment.
Three “Graduate Reference Forms” completed by individuals who can provide qualitative assessment of the applicant’s potential for success in graduate course work. This form is available in the office of the College of Graduate Studies or online at http:///www.jsu.edu/graduate/forms.html or http://www.jsu.edu/graduate/docs/ref_form.pdf.

If English is not the applicant’s native language, the applicant is required to submit an official TOEFL score report or an IELTS score report (please refer to page 28 of this Bulletin).

Admission Requirements

In addition to meeting the general admission requirements of the College of Graduate Studies, applicants for the MS with a major in computer systems and software design must have the equivalent of an undergraduate degree with a major in computer science, software engineering, or information systems as determined by the graduate computer science faculty. Applicants with degrees in related fields with three to five years experience in systems and software design may be considered. These applicants should have the equivalent of a minor in computer science including courses equivalent to Software Engineering I (CS 310), Software Engineering II (CS 491), Operating Systems (CS 350), Database Systems (CS 488), either Calculus and Its Applications (MS 120) or Calculus I (MS 125), and demonstrated proficiency in a procedural or object-oriented programming language. Applicants who are deficient in these areas may be required to take additional courses at the graduate and/or undergraduate levels.

Students receiving undergraduate degrees from institutions not accredited by a United States regional accrediting association must meet unconditional admission requirements.

Applicants must meet one of the following formula requirements. For purposes of computing the undergraduate GPA, a 4.0 grade-point scale is used. The plus (+) and minus (-) grades from undergraduate transcripts are not used in calculating the GPA.

Unconditional Admission

(200 x undergraduate GPA) + (GMAT) ≥ 950 points

(450 x undergraduate GPA) + (total of verbal & quantitative sections of GRE General Test) ≥ 2100 points.

200 times the undergraduate GPA on the last 64 hours attempted toward completion of the initial undergraduate degree plus the GMAT score is equal to or greater than a total of 1000 points;

(200 x undergraduate GPA (last 64 hours attempted)) + (GMAT) ≥ 1600 points.

(450 x undergraduate GPA (last 64 hours attempted)) + (total of verbal & quantitative sections of GRE General Test) ≥ 2450 points.

Conditional Admission

Any applicant failing to meet the requirements for unconditional admission, as defined above, will receive a letter to that effect from the Dean of the College of Graduate Studies. Under exceptional circumstances, consideration for conditional admission may be given to a student meeting one of the following formula requirements:

(200 x undergraduate GPA) + (GMAT) ≥ 850 points.

(450 x undergraduate GPA) + (total of verbal & quantitative sections of GRE General Test) ≥ 1700 points.

(200 x undergraduate GPA (last 64 hours attempted)) + (GMAT) ≥ 900 points.

(450 x undergraduate GPA (last 64 hours attempted)) + (total of verbal & quantitative sections of GRE General Test) ≥ 1850 points.

Applicants who are granted conditional admission must achieve a GPA of at least 3.0 on the first 12 graduate hours attempted within the time frame specified by the graduate faculty and indicated in writing to the student. Failure to comply will result in the students being dropped from the program.

All applications will be reviewed by the graduate faculty in the program. The faculty will submit to the Dean of the College of Graduate Studies its recommendation on the conditional admission of each applicant. The Dean of the College of Graduate Studies will make the final decision on the conditional admission of the student.

Studio Option:

A total of 30 semester hours in graduate computer science courses is required. There is a core of 15 graduate semester hours required for all concentrations. In addition to the core, students must take a concentration-specific Studio Component consisting of six semester hours. The remaining nine semester hours consist of a concentration-specific course and/or electives per the requirements for each concentration.

Students accepted into the MS with a major in computer systems and software design with the studio option must complete a six-hour studio component. The student must meet with a graduate advisor who will select an Advisory Committee to supervise the studio component of the program. The advisor and committee are responsible for determining successful completion of the studio component of the program.

Non-Studio Option:

A total of 33 semester hours in graduate computer science courses is required. There is a core of 15 graduate semester hours required for all concentrations. In addition to the core, students must take eighteen (18) graduate credit hours of a concentration-related course and/or elective per the requirements for each concentration.

Students accepted into the MS with a major in computer systems and software design with the Non-Studio option must successfully complete both written and oral comprehensive examinations.

Students must select and complete the requirements for one of the following two concentrations:

General Concentration:
(30 graduate semester hours for Studio option)/33 graduate semester hours for non-Studio option)

Required Core Courses (as listed) (15)

Studio Option:

Studio Component (6) and electives (select three additional course from the electives listed) (9)

Non-Studio Option:

Select six additional courses from the electives listed (18)

Information Security and Assurance Concentration:
30 graduate semester hours for Studio option/33 graduate semester hours for non-Studio option

Required Core Courses (as listed) (15)
CS 545, Advanced Computer Networking (3)

Studio Option:

Studio Component (must be a topic in Information Security and Assurance ) (6) and electives (select two courses from the electives listed) (6)

Non-Studio Option:

Select 3 from the following courses related to Information Security and Assurance: EM 505, CS 525, CS 530, CS 565 (9) and two additional courses from the electives listed) (6)

MS with a major in Computer Systems and Software Design

Required Core Courses (15 semester hours):

CS 501 - Database Management Systems (3)
CS 521 - Applied Software Engineering I (3)
CS 523 - Applied Software Engineering II (3)
CS 550 - Distributed Computing Systems (3)
CS 570 - Advanced Computer Security (3)

Electives:

EM 505 - Foundations of Emergency Management (3)
CS 502 - Research Methods and System Evaluation (3)
CS 525 - Advanced Web Application Development Using Web Services (3)
CS 530 - Human-Computer Interaction (3)
CS 534 - Emerging Software Architectures and Methodologies (3)
CS 536 - Computational Intelligence (3)
CS 538 - Business Intelligence and Data Mining (3)
CS 540 - Bioinformatics Algorithms (3)
CS 543 - Advanced Expert Systems (3)
CS 544 - Applied Artificial Intelligence (3)
CS 545 - Advanced Computer Networking (3)
CS 553 - Simulation, Modeling & Forecasting (3)
CS 565 - Embedded & Real-Time Software Development (3)
CS 591 - Special Topics in Computer Science (3)
CS 592 - Special Topics in Computer Science (3)

Studio Component (6 semester hours) only for Studio Option:

CS 595 - Studio Component (3)
CS 596 - Studio Component (3)

Studio Option: 30 Graduate Semester Hours Required for this Degree

Non-Studio Option: 33 Graduate Semester Hours Required for this Degree

Computer Science Courses

Prefix CS

501.		Database Management Systems (3). Prerequisite: A programming language. Information as corporate resource, data modeling, database design, implementation strategies and administration; security, information centers, decision support systems, mini- and microcomputer environment; teams of students will design and implement a relational database application.
502.		Research Methods and System Evaluation (3). Prerequisite: Undergraduate of graduate statistics course. Introduction to the research techniques and methodologies used to evaluate systems such as control systems, computer systems, security systems, and information systems. Topics include methodological foundations, qualitative research methods, and quantitative research methods.
510.		Introduction to Computing (3). Includes fundamental computer science concepts, computer programming, software engineering, data structures, and algorithms. (For graduate students with limited computer science backgrounds who wish to major in computer systems and software design; cannot be used for Master’s degree credit.)
514.		Introduction to Computer Systems (3). Prerequisite: Permission of the instructor. Study of operating systems, networks, and computer architecture; advanced systems programming using an object-oriented programming language. (For graduate students with limited computer science backgrounds who wish to major in computer systems and software design; cannot be used for Master’s degree credit.)
521.		Applied Software Engineering I (3). Prerequisite: Comprehensive undergraduate course in software engineering or industrial software engineering experience with a large project. Focuses specifically on methods that guide software engineers from requirements to code; provides broad understanding of current methods, and specific skills in using these methods.
523.		Applied Software Engineering II (3). Prerequisite: CS 521. Provides knowledge and skills necessary to lead a project team, understand the relationship of software development to overall product engineering, and understand the software process.
525.		Advanced Web Application Development Using Web Services (3). Prerequisite: Undergraduate software engineering course equivalent. Utilization of various technologies and tools for developing Web applications using Web Services, emphasizing organizational issues, challenges, and security concerns related to the effective deployment of those applications. Students will evaluate real-world applications of Web services as well as the unique decision-making framework involved with their adoption while employing those lessons learned in practical solutions.
530.		Human-Computer Interaction (3). Prerequisite: Comprehensive undergraduate course in software engineering or industrial software engineering experience with a large project. Human-computer interface, human performance, diversity, and mental models, interaction devices, dialog and interface styles, documentation, and usability testing.
534.		Emerging Software Architectures and Methodologies (3). Prerequisite: Comprehensive undergraduate course in software engineering or industrial software engineering experience with a large project. Explores emerging technologies and contemporary development methodologies for large scale software systems; difficulties and benefits of software by component composition, component reuse and software architectures.
536.		Computational Intelligence (3). Prerequisite: Experience with an object oriented programming language. Introducing concepts, models, algorithms, and tools for development of intelligent systems. Example topics include artificial neural networks, genetic algorithms, fuzzy systems, swarm intelligence, ant colony optimization, artificial life, and hybridizations of the above techniques. Additional focus will be placed on research methodologies and preparing research papers and reports.
538.		Business Intelligence and Data Mining (3). Prerequisite: Undergraduate or graduate statistics course. Introduction to business intelligence and data mining methodologies and tools that enable users to analyze new patterns/relations and develop insight for decision making. This course provides students thorough conceptual framework, discussion, and hands-on experience in business intelligence and data mining. Techniques that the course covers include, but are not limited to, linear modeling, decision trees, association rules, classisfication rules, clustering & visualization, and text mining methodologies. Topics covered will include business intelligence, data mining methods, predictive analysis, information quality, and a term project that applies the skills learned.
540 .		Bioinformatics Algorithms (3). Prerequisites: Basic knowledge in probability and statistics, data structures, and algorithms. Provides fundamental background in bioinformatics for computer science or biological science students. Provides the principles that drive an algorithm's design. Covers various topics such as DNA and RNA structure, gene structure and control, protein structure, sequence alignment production, homologous sequences searches, phylogenetic trees structure and interpretation.
543.		Advanced Expert Systems (3). Prerequisite: Experience with a procedural or object-oriented programming language. This course provides an in-depth study of expert knowledge-based problem-solving systems. Students perform a classification and comparison of selected systems by analyzing the architecture,knowledge, and problem-solving style. Students evaluate the contributions of each to the understanding of problem domains for expert systems.
544.		Applied Artificial Intelligence (3). Prerequisite: Undergraduate artificial intelligence course or equivalent. Survey of artificial intelligence emphasizing applications in business, industrial, and scientific system development; autonomous agents, data mining, pattern recognition, and machine vision.
545.		Advanced Computer Networking (3). Prerequisite: Undergraduate operating system course or equivalent. A study of advanced topics in computer networks with emphasis on wireless communications. Fundamentals of cellular communications, CDMA systems, wireless security, Wireless Application Protocols (WAP), Bluetooth, and new wireless technologies are also covered.
550.		Distributed Computing Systems (3). Prerequisite: Undergraduate course in computer networking or equivalent. Design and analysis of distributed computing systems; system architecture; load balancing and scheduling; remote procedure calls and message passing; distributed operating systems and database systems.
553.		Simulation, Modeling, and Forecasting (3). Prerequisite: CS 521. Deterministic and stochastic models are studied; simulation techniques, languages, and programming packages used to implement simulation models; virtual reality simulations.
565.		Embedded and Real-Time Software Development (3). Prerequisite: CS 521. In-depth study of requirements or real-time and embedded software; examination of operating systems, languages, and devices that support these systems; real-time multimedia applications emphasized.
570.		Advanced Computer Security (3). Prerequisite: Undergraduate operating system course or equivalent. Study of advanced network security architectures, models, benchmarks and metrics, cryptography, authentication and authorization protocols, secure application and systems development, federal regulations and compliance, and advanced security topics on intrusion detection, biometrics, web services, and data mining. Emphasis is on security professional certification.
591, 592.		Special Topics in Computer Science (3). Prerequisites: Permission of the advisor and approval of the department head. Selected topics from current problems in computing; topics vary from semester to semester. May be taken twice for credit.
595, 596.		Studio Component (3). Prerequisites: Permission of the advisor and approval of department head. Provides students with a laboratory for direct application of concepts learned in course work; students will produce a variety of software products.

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