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College of Arts & Sciences
Office of Dean - College of Arts & Sciences
1871 Old Main Drive
Shippensburg PA 17257
pahoop@ship.edu (717) 477-1151
Department
Computer Science Department
1871 Old Main Drive
Shippensburg, PA 17257
(717) 477-1178 compsci@ship.edu
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Computer Science
Interested in a master’s degree in computer science but earned a bachelor’s degree in another field?
The M.S. in Computer Science is designed
to accommodate students from several
different backgrounds. Students with at
least a minor in computer science will find a
traditional M.S. in Computer Science. Our
undergraduates may obtain an advanced
degree through a 4+1 B.S./M.S. option.
Students who wish to transition from math,
science, or engineering into computer science
may be fully enrolled in the program
after taking three prerequisite undergraduate
courses.
Degree Requirements
The degree requires 30 graduate credits.
There are six core courses out of a total
of 10 total courses required. At most two
400-level courses may be used as electives.
Traditional students can be admitted in
either the spring or fall and complete the
degree in three semesters plus one summer.
The following two tables show the course
schedules for traditional students entering
in the fall and spring, respectively.
| Fall | Spring | Summer | Fall |
| Algorithms | Operating Systems | 500- level elective | Automata Theory |
| Architecture | High Performance Computing | Database Management Systems | |
| Elective | Elective | Elective |
| Spring | Summer | Fall | Spring |
| Database Management Systems | 500- level elective | Architecture | High Performance Computing |
| Elective | Automata Theory | Operating Systems | |
| Elective | Algorithms | Elective |
The two 500-level courses that they take
in the spring of their senior year will count
as electives in their B. S. program and
cannot be substituted for any course in
their concentration (these courses cannot
replace core courses in the B.S.)
For transitional students, the combination
of a math or science undergraduate degree
with a computer science masters degree can
create unique and marketable skills. People
with that background are poised to apply
computer science in areas for which traditional
computer scientists are unprepared.
We do require that a transitional student
have had at least one programming course.
Then, in their fi rst fall semester they must
take three undergraduate courses:
CSC 111 – Computer Science II
CSC 220 – Computer Organization
MAT 225 – Discrete Math
Note that while taking these UG courses, the student is not eligible for a graduate assistantship. In the spring, they can be fully enrolled in the MS program using the same schedule as traditional students.
Our bachelor’s students can complete the
M.S. degree in only one year beyond the
B.S. degree by using the following course
table:
| Spring of Senior Year | Summer | Fall | Spring |
| Database Management Systems | 500-level elective | Architecture | High Performance Computing |
| 500- level elective | 500- level independent study | Automata Theory | Operating Systems |
| Algorithms | elective |
This program offers a unique opportunity
to be involved in a challenging,
well-respected program. The time to take
advantage of this opportunity is now.
Interested in a master’s degree in computer
science but earned a bachelor’s degree in
another field?
Admission Requirements
To gain admission to the M.S. in computer
science program, an applicant must
satisfy the general admission requirements
of the graduate school. Students are
admitted in the fall only. Applicants whose
overall quality point average is below
2.75 will be required to take the Graduate
Record Examination (GRE) prior to
admission. All international applicants
who have not graduated from a four-year
American university must take the Test of
English as a Foreign Language (TOEFL).
Additionally, all such applicants must
achieve a minimum score of 237 on the
TOEFL (computer based).
Resources
The Department of Computer Science maintains its own computer lab and classrooms. There are two PC (Windows and Linux) computer classrooms and one Sun/Graphics classroom with 30 Sun Blade 1500 machines (Solaris) and 10 dual processor G5 Macs. The department computer lab contains PC machines for use by all students taking computer science courses. The Sun/Graphics classroom is available for use as a lab when classes are not being held. In all there are roughly 100 computers available for use by computer science students, roughly one computer for every three students. These computers are maintained by a dedicated lab technician.
There are three servers that help manage the department’s network. Clipper, a dual processor Sun Blade, acts as the main server for the department. All students are provided an account on Clipper, which also supports an Oracle database server and a web server via Apache. Additionally, there is Cutter, a student managed machine for gaining hands-on learning, and Trawler, a Windows server providing web page support through IIS and MS SQL database server.
The department machines and servers provide access to a large number of software programs (Eclipse, MS Office, Visual Studios .NET, etc.) and languages (Java, C++, LISP, etc.). Through campus licenses students have access to many of these programs for downloading and installation on their machines. Additionally, the department subscribes to the Microsoft Developers Network Academic Alliance, giving students access to additional software. The university provides support for both wireless and Ethernet networking of student computers on campus.
Faculty
The majority of computer science department faculty hold earned doctorates. Some faculty members also serve as consultants to government and to nearby firms.
James H. Mike, Ph.D., dean, College of Arts and Sciences.
Carol A. Wellington, Ph.D., chair, North Carolina State University, operating systems, real-time systems, artificial intelligence.
John C. Arch, Ph.D., University of Oregon, artificial intelligence, computer education.
Thomas H. Briggs, M.S., Shippensburg University, operating systems, database management, and web programs.
C. Dudley Girard, Ph.D., University of South Carolina, artificial intelligence and biological modeling
David Hastings, Ph.D., University of Massachusetts, algorithms for parallel computing.
Jeonghwa Lee, Ph.D., University of Kentucky, scientific simulation, parallel algorithms, security.
Dave Mooney, Ph.D., University of Delaware, artificial intelligence.
