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Software Engineering Master's Program (with Thesis) (M.S., 1 - 2 Years)

In view of the rapid development of computer and information technology, the increasing degree of complexity and diversity of computer applications, and the indispensability of interdisciplinary research activities, the Department of Computer Engineering has established the degree of Master of Science (M.S.) in Software Engineering. The department is well equipped with research facilities which are currently being used by staff members, and graduate students from various departments. The basic objectives of the Software Engineering graduate program can be outlined as follows: (1) to develop skills in the use of computer tools and in the application of computerized techniques, and to promote interdisciplinary research; (2) to stimulate independent study, critical and creative thinking; (3) to ensure a deeper understanding of the fundamental aspects of computer engineering area; (4) to provide opportunities for advanced specialization and creative research activities in software engineering; and (5) to contribute to the education of prospective academicians.

Admission Requirements

Applicants to M.S. program should have a B.S. degree in an engineering, mathematics or natural sciences field with a CGPA greater than or equal to 2.2/4.0.

Research Interests

Software Architecture, Database and File Security, User Interface Development, Web Technologies and Services, Testing Web Applications and Services, Software Quality Assurance and Reliability, Software System Modeling and Analysis, Big Data Analytics, Biometric based human identification systems, Multimedia systems, Computer networks, Artificial intelligence, Text mining, Robotics, Fuzzy logic, Parallel processing, Neural networks, Expert systems, Network security, Computer communication/Wireless networks, Positioning systems, Performance evaluation, Multi-objective optimization, Real time systems, Automated deduction, Constraint programming, and Declarative programming languages, Evolutionary computation, Hybrid methods, Metaheuristics, Pattern recognition, Multiple classifer systems.


Tel: +90 392 630 1484
Fax: +90 392 365 0711

Please contact to department and/or faculty for detailed information about courses.

Course Title Credit Lec. Tut.
CMSE500 Master Thesis - - -
RES1 Restricted Elective Course 3 3 -
RES2 Restricted Elective Course 3 3 -
RES3 Restricted Elective Course 3 3 -
RES4 Restricted Elective Course 3 3 -
REQ1 Elective Course 3 3 -
REQ2 Elective Course 3 3 -
REQ3 Elective Course 3 3 -
CMSE598 Seminar - - -
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