SE501 Sotware Modelling and Analysis
SE501 Sotware Modelling and Analysis
Syllabus | International University of Sarajevo - Last Update on Mar 03, 2026
Syllabus Quick Jump
Search and navigate to any syllabus instantly
Software Engineering
Khaldoun Al Khalidi
Course Lecturer
Course Objectives
This course focuses on software models that are used to specify, validate, verify, and analyze software systems. Students will develop knowledge and skills in software verification and validation as well as expertise in data modeling. Various software modeling techniques and frameworks will be covered in this course and students will learn to apply them to the requirements specification, design and development of software artifacts. They will learn to use software verification tools and techniques to ensure that a software system has been built according to the requirements and design specifications defined in the model. Students will also use software validation frameworks to test whether the software actually meets the user’s needs and that the initial specifications were correct.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
There is no specific book.
Additional Literature
1. V.S. Alagar, K Periyasamy, Specification of Software Systems (2nd ed.). Springer, 2011. 2. G. O'Regan, Concise Guide to Formal Methods Theory, Fundamentals and Industry Applications. Springer, 2017. 3. L. Bass, P. Clements,b, R. Kazman, Software architecture in practice (3rd ed.). Upper Saddle River: Addison-Wesley, 2013. 4. K. Wiegers, J. Beatty, Software Requirements (3rd ed.). Microsoft Press, 2014. 5. M. Fowler, Patterns of Enterprise Application Architecture. Addison-Wesley Professional, 2002. 6. M. Fowler, Analysis Patterns: Reusable Object Models. Addison-Wesley Professional, 1996. 7. M. Fowler, UML Distilled: A Brief Guide to the Standard Object Modeling Language (3rd ed.). Addison-Wesley Professional, 2003. 8. R. Mitchell, J. McKim, Design by Contract: By Example 1st Edition. Addison-Wesley Publishing Company, 201.Teaching Methods
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction and Overview | |
| 2 | Modeling principles (e.g., decomposition, abstraction, generalization, projection/views, and use of formal approaches) | 2, 3, 4 |
| 3 | Preconditions, postconditions, invariants, and design by contract | 8 |
| 4 | Information modeling (e.g., entity-relationship modeling and class diagrams) | 7 |
| 5 | Behavioral modeling (e.g., state diagrams, use case analysis, interaction diagrams, failure modes and effects analysis, and fault tree analysis) | 7 |
| 6 | Architectural modeling (e.g., architectural patterns and component diagrams) | 5 |
| 7 | Midterm | |
| 8 | Domain modeling (e.g., domain engineering approaches) | 6 |
| 9 | Enterprise modeling (e.g., business processes, organizations, goals, and workflow) | 4 |
| 10 | Introduction to mathematical models and formal notation | 2, 3 |
| 11 | Analyzing form (e.g., completeness, consistency, and robustness) | 2, 3 |
| 12 | Analyzing correctness (e.g., static analysis, simulation, and model checking) | 2, 3 |
| 13 | Analyzing dependability (e.g., failure mode analysis and fault trees) | 2, 3 |
| 14 | Formal analysis (e.g., theorem proving) | 2, 3 |
| 15 | Review |
Course Schedule (All Sections)
Office Hours & Room
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes :
Midterm
AI: Not AllowedAlignment with Learning Outcomes :
Assignments
AI: Not AllowedAlignment with Learning Outcomes :
Research paper
AI: Not AllowedAlignment with Learning Outcomes :
Presentation
AI: Not AllowedAlignment with Learning Outcomes :
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lecture
42 hours ⏳ (14 week × 3 h)
Research
36 hours ⏳ (12 week × 3 h)
Final Exam Study
6 hours ⏳ (1 week × 6 h)
Assignments
52 hours ⏳ (13 week × 4 h)
Home Study
14 hours ⏳ (14 week × 1 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [SE501] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Mar 03, 2026 | International University of Sarajevo
Print Syllabus
Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| SE501 | Sotware Modelling and Analysis | 3 | 0 | 6 | W 5 PM - 8 PM | |||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Khaldoun Al Khalidi | Office Hours / Room / Phone | Currently not available |
|||||||
| kalkhalidi@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | This course focuses on software models that are used to specify, validate, verify, and analyze software systems. Students will develop knowledge and skills in software verification and validation as well as expertise in data modeling. Various software modeling techniques and frameworks will be covered in this course and students will learn to apply them to the requirements specification, design and development of software artifacts. They will learn to use software verification tools and techniques to ensure that a software system has been built according to the requirements and design specifications defined in the model. Students will also use software validation frameworks to test whether the software actually meets the user’s needs and that the initial specifications were correct. | |||||||||
| Textbook | There is no specific book. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
| Teaching Methods | ||||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction and Overview | |||||||||
| Week 2 | Modeling principles (e.g., decomposition, abstraction, generalization, projection/views, and use of formal approaches) | 2, 3, 4 | ||||||||
| Week 3 | Preconditions, postconditions, invariants, and design by contract | 8 | ||||||||
| Week 4 | Information modeling (e.g., entity-relationship modeling and class diagrams) | 7 | ||||||||
| Week 5 | Behavioral modeling (e.g., state diagrams, use case analysis, interaction diagrams, failure modes and effects analysis, and fault tree analysis) | 7 | ||||||||
| Week 6 | Architectural modeling (e.g., architectural patterns and component diagrams) | 5 | ||||||||
| Week 7 | Midterm | |||||||||
| Week 8 | Domain modeling (e.g., domain engineering approaches) | 6 | ||||||||
| Week 9 | Enterprise modeling (e.g., business processes, organizations, goals, and workflow) | 4 | ||||||||
| Week 10 | Introduction to mathematical models and formal notation | 2, 3 | ||||||||
| Week 11 | Analyzing form (e.g., completeness, consistency, and robustness) | 2, 3 | ||||||||
| Week 12 | Analyzing correctness (e.g., static analysis, simulation, and model checking) | 2, 3 | ||||||||
| Week 13 | Analyzing dependability (e.g., failure mode analysis and fault trees) | 2, 3 | ||||||||
| Week 14 | Formal analysis (e.g., theorem proving) | 2, 3 | ||||||||
| Week 15 | Review | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 35 | Not Allowed | ||
| Semester Evaluation Components | |||||
| Midterm | 1 | 20 | Not Allowed | ||
| Assignments | 6 | 30 | Not Allowed | ||
| Research paper | 1 | 10 | Not Allowed | ||
| Presentation | 1 | 5 | Not Allowed | ||
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture | 3 | 14 | 42 | Research | 3 | 12 | 36 | |||
| Final Exam Study | 6 | 1 | 6 | Assignments | 4 | 13 | 52 | |||
| Home Study | 1 | 14 | 14 | |||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 27/03/2026 | |||||||||