CS305 Programming Languages
CS305 Programming Languages
Syllabus | International University of Sarajevo - Last Update on Apr 04, 2026
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Computer Sciences and Engineering
Özge Büyükdağlı
Course Lecturer
Course Objectives
- Improve the background for choosing appropriate programming languages for certain types of programming problems
- Be able in principle to program in a procedural, an object-oriented, a functional, and a logical programming language
- Understand the significance of an implementation of a programming language
- Increase the ability to learn new programming languages
- Increase the capacity to express programming concepts and choose among alternative ways to express things in a programming language
- Be able in principle to design a new programming language
- Use of languages that are already known
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Concepts of Programming Languages, Robert W. Sebesta, Addison-Wesley, 8th edition, 2008.
Additional Literature
TBATeaching Methods
Lectures
Tutorials
Class discussion with examples
In-lab assignment
And a project.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Course logistics | |
| 2 | Preliminaries | Chapter 1 |
| 3 | Describing Syntax and Semantics | Chapter 3 |
| 4 | Names, Bindings, Type Checking, and Scopes | Chapter 5 |
| 5 | Data Types | Chapter 6 |
| 6 | Expressions and Assignment Statements | Chapter 7 |
| 7 | Statement-level control structures | Chapter 8 |
| 8 | Midterm Exam | |
| 9 | Subprograms | Chapter 9 |
| 10 | Subprogram Implementation | Chapter 10 |
| 11 | Functional Programming Languages | Chapter 15 |
| 12 | Functional programming languages | Chapter 15 |
| 13 | Logic Programming Languages | Chapter 16 |
| 14 | Logic Programming Languages | Chapter 16 |
| 15 | Review |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| CS305.1 | Course | Tuesday 16:00 - 17:50 | A F1.11 | Wednesday 11:00 - 11:50 | A F1.11 |
| CS305.1 | Tutorial | Monday 18:00 - 19:50 | A F1.18 - Computer Lab | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Tuesday | 09:00 - 12:00 | A F2.28 | |
| Thursday | 14:00 - 17:00 | A F2.28 |
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4
Midterm
AI: Not AllowedAlignment with Learning Outcomes : 1 2
Quiz
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4
In Lab assignment
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4
Project
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4
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 Hours
45 hours ⏳ (15 week × 3 h)
Tutorials
28 hours ⏳ (14 week × 2 h)
Project
12 hours ⏳ (1 week × 12 h)
Home study
30 hours ⏳ (15 week × 2 h)
Midterm exam study
15 hours ⏳ (1 week × 15 h)
Final exam study
20 hours ⏳ (2 week × 10 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 [CS305] 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 Apr 04, 2026 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| CS305 | Programming Languages | 3 | 2 | 6 | ||||||
| Prerequisite | CS206 | It is a prerequisite to | - | |||||||
| Lecturer | Özge Büyükdağlı | Office Hours / Room / Phone | Tuesday: 9:00-12:00 Thursday: 14:00-17:00 |
|||||||
| obuyukdagli@ius.edu.ba | ||||||||||
| Assistant | Mirza Selimovic, Adna Dedic | Assistant E-mail | mselimovic@ius.edu.ba | |||||||
| Course Objectives | Improve the background for choosing appropriate programming languages for certain types of programming problems Be able in principle to program in a procedural, an object-oriented, a functional, and a logical programming language Understand the significance of an implementation of a programming language Increase the ability to learn new programming languages Increase the capacity to express programming concepts and choose among alternative ways to express things in a programming language Be able in principle to design a new programming language Use of languages that are already known |
|||||||||
| Textbook | Concepts of Programming Languages, Robert W. Sebesta, Addison-Wesley, 8th edition, 2008. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Lectures, Tutorials, Class discussion with examples, in-lab assignment, and a project. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Course logistics | |||||||||
| Week 2 | Preliminaries | Chapter 1 | ||||||||
| Week 3 | Describing Syntax and Semantics | Chapter 3 | ||||||||
| Week 4 | Names, Bindings, Type Checking, and Scopes | Chapter 5 | ||||||||
| Week 5 | Data Types | Chapter 6 | ||||||||
| Week 6 | Expressions and Assignment Statements | Chapter 7 | ||||||||
| Week 7 | Statement-level control structures | Chapter 8 | ||||||||
| Week 8 | Midterm Exam | |||||||||
| Week 9 | Subprograms | Chapter 9 | ||||||||
| Week 10 | Subprogram Implementation | Chapter 10 | ||||||||
| Week 11 | Functional Programming Languages | Chapter 15 | ||||||||
| Week 12 | Functional programming languages | Chapter 15 | ||||||||
| Week 13 | Logic Programming Languages | Chapter 16 | ||||||||
| Week 14 | Logic Programming Languages | Chapter 16 | ||||||||
| Week 15 | Review | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 30 | 1,2,3,4 | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm | 1 | 25 | 1,2 | Not Allowed | |
| Quiz | 1 | 5 | 1,2,3,4 | Not Allowed | |
| In Lab assignment | 1 | 20 | 1,2,3,4 | Not Allowed | |
| Project | 1 | 20 | 1,2,3,4 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture Hours | 3 | 15 | 45 | Tutorials | 2 | 14 | 28 | |||
| Project | 12 | 1 | 12 | Home study | 2 | 15 | 30 | |||
| Midterm exam study | 15 | 1 | 15 | Final exam study | 10 | 2 | 20 | |||
| 0 | ||||||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 16/04/2026 | |||||||||