PhD Software Engineering


Ph.D. in Software Engineering focuses on the advancement of theory and practice in the area of Software Engineering and relevant computing domains. The Software Engineering discipline is highly interdisciplinary including the application of mathematical, computer science, systems, and software engineering concepts. Ph.D. Software Engineering program thus focuses on producing well-educated researchers who can contribute by the creation of new knowledge and propose solutions to challenges faced by the practitioners and researchers of the discipline.

Program Mission

To enhance the theory and practice in the domain of Software Engineering by creating of new knowledge and highly qualified academicians and fostering innovation in the core areas of Software Engineering and applied computing disciplines.

Program Educational Objectives

The objectives of Ph.D. (Software Engineering) program are:

  • To equip scholars with the necessary knowledge, relevant tools, and techniques to make a significant contribution to the field of study by conducting quality research independently or in collaboration.
  • To prepare scholars to effectively disseminate results in the form of written and oral presentation
  • To produce skilled professionals who can take up the challenges associated with the advancement of science and technology in industry or in academia.

Program Learning Outcomes

Ph.D. scholars who successfully complete their Ph.D. in Software Engineering will be able to:

PLO 1: Synthesize content knowledge, concepts, and principles grounded in the domain of Software Engineering and relevant allied disciplines (Engineering, Mathematics, and Computing).

PLO 2:  Design and conduct research that is grounded in theory, and practice and further extends the existing research in the field.

PLO 3:  Conduct research that positively impacts the domain and society.

PLO 4:  Communicate effectively both in oral and written formats to a diverse audience.

PLO 5:  Collaborate with peers in the domain of Software Engineering and computing to integrate diverse perspectives.

Program Structure

The Ph.D. program consists of 18 credit hours of coursework and 36 credit hours of research work. Coursework should be completed in the first two semesters. After successful completion of coursework, a Ph.D. scholar is required to appear in the comprehensive examination. After passing the comprehensive examination Ph.D. scholar can register in the research phase by registering for THS 900 Ph.D. Thesis course. The first milestone in the research phase is to prepare and submit a research proposal under the guidance of a supervisor. The scholar appears before a panel of examiners to defend the research proposal. After a successful defense, the scholar needs to carry out his/her research and complete a total of 36 credits of research. The scholar will present the research finding in the form of a written thesis, which shall be evaluated as per HEC and BU rules. For further details about rules governing Ph.D. programs refer to Ph.D. Rules Handbook.

Semester wise breakdown of the program is as follows.

Course code Subject Credits
Course Work (Student shall study 3 courses) 9
Total credits for 1st semester 9
Course code Subject Credits
Course Work (Student shall study 3 courses) 9
Total credits for 2nd semester 9
Course code Subject Credits
Comprehensive exam 0
THS-900 Ph.D. Thesis 9
Total credits for 3rd semester 9
Course code Subject Credits
THS-900 Ph.D. Thesis 9
Total credits for 4th semester 9
Course code Subject Credits
THS-900 Ph.D. Thesis 9
Total credits for the 5th semester 9
Course code Subject Credits
THS-900 Ph.D. Thesis 9
Total credits for the 6th  semester 9
Total credit for the Ph.D. program 54

Ph.D. Coursework

    1. A Ph.D. scholar will select 6 courses in consultation and approval of the supervisor/advisory committee from the following list of courses.
    2. Scholars can choose a minimum of 3 courses from Category-1 courses and a maximum of 3 courses from Category-2 courses. Scholars will also be able to take all 700+ courses from the MS Software Engineering program as Category-1 courses.
    3. Relevant 700+ courses of MS/Ph.D. programs in Computer Science, Data Science, and Information Security will be included in category-1 or 2 based on the subject area. The supervisor/Advisory committee will decide on the relevance of such courses for each scholar.

It is mandatory to study ESC 701 Research Methodology if the scholar has not studied this or an equivalent course in the MS program.

S# Course


Title of Course Cr. Hrs.
Category-1 Software Engineering & Information Systems
1          SEN 720 Advanced Human-Computer Interaction 3
2          SEN 756 Advanced Usability Engineering 3
3          SEN 723 Formal Methods and Specifications 3
4          SEN 763 Advanced Software Engineering 3
5          SEN 759 Software Re-Engineering 3
6          SEN 758 Component-Based Software Engineering 3
7          SEN 812 Agile Methods 3
8          SEN 815 Verification and Validation 3
9          SEN 813 Advanced Software Requirements Engineering 3
10      SEN 757 Empirical Software Engineering 3
11      SEN 801 Model Driven Software Engineering 3
12      SEN 802 Special Topics in Software Engineering 3
13      SEN 754 Advanced Web Computing System and Application 3
14      SEN 755 Service Oriented Computing 3
15      SEN 816 Middleware For Networked and Distributed Systems 3
16      CSC 781 Cloud Computing 3
17      CEN 707 Advanced Distributed Systems 3
18      SEN 803 Advanced e-Learning Systems 3
19      SEN 761 Advanced Semantic Web 3
20      SEN 764 Ontology Engineering 3
21      SEN 760 Complex Adaptive Systems 3
22      CEN 708 Advanced System Modeling and Simulation 3
23      CSC 759 Agent-Based Modeling 3
24      SEN 762 Advanced Big Data Analytics 3
25      CSC 711 Advanced Artificial Intelligence 3
26      CSC 741 Advanced Natural Language Processing 3
27      CSC-749 Advanced Neural Networks and Fuzzy Logic 3
28      CSC 751 Pattern Recognition 3
29      CSC 746 Advanced-Data Mining 3
30      CSC 760 Advanced-Data Warehousing 3
31      CSC 801 Advanced Information Retrieval 3
32      CSC 719 Machine learning 3
33      DSC-703 Data Visualization 3
34      DSC-705 Deep Learning and Data Analysis 3
35      CSC 747 Text Mining 3
36      CSC 764 Computer Vision 3
37      CSC 765 Bio-Medical Image Analysis 3
38      CSC 701 Computer-Supported Cooperative Work 3
39      CEN 745 Advanced Digital Image Processing 3
40      CSC 750 Intelligent Tutoring System 3
Category-2 Computing & Cross-Domain Courses
1          ESC 701 * Research Methodology 3
2          GSC 700 Advanced Engineering Mathematics 3
3          CEN 764 Design of Fault-Tolerant Systems 3
4          SEN 753 Power Aware Computing 3
5          SEN 814 Ubiquitous Computing and Interaction 3
6          CSC 704 Advanced Cryptography 3
7          CSC 720 Advanced Operating Systems 3
8          CSC 744 Advanced Computer Graphics 3
9          CSC 753 Distributed Databases 3
10      CSC 757 IP Multimedia System 3
11      CSC 758 Parallel Processing 3
12      CEN 720 Advanced Computer Architecture 3
13      CSC 754 Object Oriented Databases 3
14      CSC 755 Web Based DBMS 3
15      CSC 756 Multimedia Databases 3
16      EET 710 Advanced Computer Networks 3
17      EET 726 Advanced Internet Technologies 3
18      EET 702 Advanced Network Security 3
19      CEN 740 Advanced Embedded Systems 3
20      CEN 742 Advanced Digital System Design 3
21      EET 850 Wireless Sensor Networks 3
22      EET 851 Mobile and Ad-hoc Networks 3
23      EEN 725 Advanced Digital Signal Processing 3

*It is mandatory to study ESC 701 Research Methodology if the scholar has not studied this or an equivalent course in the MS program.