Winter Term 2026/27: Generative KI im Software Engineering

Winter Term 2026/27

Lecturer	Prof. Dr. Dominik Sobania
Lecture Time	Tuesdays, 2 pm to 4 pm, room S - E - SE 111 (from 2026-10-20)
Exercise/Tutorial Time	Thursdays, 10 am to 12 pm, room S - GW 009 (from 2026-11-05)
Moodle	Enrollment key will be announced in the first lecture
Course Catalog (LSF)	Link to entry
Recommended Prerequisites	Knowledge of Python and Java, basics of software engineering
Learning Content	- Functional & non-functional software properties - Performance measurement & software benchmarks - Search-Based Software Engineering (SBSE) - Local and evolutionary search - Multi-Objective Optimization - Genetic Improvement (GI) - Automated Program Repair (APR) - Foundations of Large Language Models (LLMs) - Model types and practical use - Context Engineering - Agentic AI - Agent architectures for software engineering - Tool Use & Function Calling - State management (memory) - Hybrid approaches
Examination	Project-based coursework throughout the semester with a written report and a presentation. Details on scope, submission deadlines and grading criteria will be announced at the start of the course.

Lecturer	Prof. Dr. Dominik Sobania
Dates	- Kick-off meeting: 2026-10-07 at 2 pm in room R12T - R12 T03 F87 - Workshop: Scientific Writing: 2026-10-21 at 3 pm in room S - E - SE 111 - Workshop: Scientific Presenting: 2027-01-20 at 12 pm in room S - M - SM 205 - Presentations 1: 2027-02-16 at 10 am in room S - M - SM 311 - Presentations 2: 2027-02-17 at 10 am in room S - M - SM 311
Maximum Capacity	15
Recommended Prerequisites	Basic knowledge of programming and software engineering and ideally the lecture AI in Software Engineering
Learning Content	Changing topics in the field of Generative Artificial Intelligence.
Registration	Details regarding registration will be announced during the kick-off meeting (see above).

▪ Kick-off meeting on 2026-10-22 from 4 pm to 5:30 pm in room S-GW 215
▪ Weekly meeting: Thursdays at 4 pm, Gerlingstraße 16