| Code |
16230
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| Year |
3
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| Semester |
S1
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| ECTS Credits |
6
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| Workload |
PL(30H)/T(30H)
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| Scientific area |
Informatics
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Entry requirements |
N/A
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Mode of delivery |
Face-to-face.
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Work placements |
Not applicable.
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Learning outcomes |
1) Knowledge: By the end of the course unit, students should know: Agile/Scrum; requirements (user stories, scenarios, modeling); design/architecture (UML/SysML); QA, testing, and CI; AI’s impact (testing, refactoring, generation); code smells/refactoring; DevOps, pipelines, and AI-supported workflows.
2) Skills: Students should be able to: gather/specify requirements (user stories, modeling); apply Agile to plan/track/reflect on sprints; model systems (e.g., use case diagrams); implement tests (unit, integration, exploratory) with AI assistance; analyze quality and refactor code smells; design/operate CI/CD; use assistants responsibly; communicate effectively in teams (retrospectives, planning, demos).
3) Competences: Students should demonstrate: iterative team delivery (Scrum); collaborative proficiency (GitHub/pipelines); critical thinking; ethics/sustainability (responsible AI); continuous/lifelong learning.
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Syllabus |
1. Introduction to Software Development and Software Products
2. Software Processes and Agile Development
3. Lifecycle Models: Waterfall, Iterative, Incremental
4. Features, Scenarios, and User Stories
5. Model-Driven Requirements Engineering
6. System Architecture
7. System Modeling
8. Software Testing and AI-Assisted Testing
9. Automated Refactoring and Code Smells with Intelligent Tools
10. Continuous Integration and Software Engineering Platforms
11. AI-Assisted Software Engineering
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Main Bibliography |
- Bass L., Lu Q., Weber I., and Zhu L., Engineering AI Systems: Architecture and DevOps Essentials, Pearson, 2025
- Sommerville I., Engineering Software Products: An Introduction to Modern Software Engineering, Pearson, 2020
- Fowler M., Refactoring (2nd Edition), Addison-Wesley Signature Series, 2018
- Sommerville I., Software Engineering, 9th edition, Pearson Education, 2011
- Pressman R. S. and Ince D., Software Engineering - A Practitioner’s Approach, McGraw-Hill, 2007
- Rambaugh J., Jacobson I. and Booch G., The Unified Modeling Language Reference Manual, Addison-Wesley, 2005
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Teaching Methodologies and Assessment Criteria |
Teaching Methodologies
• Theoretical lectures
• Practical and laboratory classes
• Group project
• Practical assignments, both individual and group-based, conducted in the classroom
Assessment
1) During the teaching-learning period
• F1: 1st Term Test – 5 marks
• F2: 2nd Term Test – 6 marks
• BT: 2 Badges (Individual Tasks) – 1 mark
• P: Group Project – 8 marks
Final Grade (Continuous Assessment) = F1 + F2 + BT + P
Maximum Score: 20 marks
2) Exam Option
• E: Written Exam – 12 marks
• P: Individual Project – 8 marks
Final Grade (Exam Option) = E + P
Maximum Score: 20 marks
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Language |
Portuguese. Tutorial support is available in English.
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