623.828 (24S) Current Topics in Software Engineering: AI for Software Engineering
Überblick
- Lehrende/r
- LV-Titel englisch Current Topics in Software Engineering: AI for Software Engineering
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- LV-Modell Präsenzlehrveranstaltung
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 4.0
- Anmeldungen 18 (20 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 05.03.2024
- eLearning zum Moodle-Kurs
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
After completing this course students will be able to:
- explain and discuss the potential of recent research in software engineering of using AI for automating some tasks in software development
- apply recent research in using AI for automating a particular task in software development, such as detecting a vulnerability or repairing a small program
Lehrmethodik
Lectures, literature research, discussion, lab assignment
Inhalt/e
Topics will include recent research articles on:
- Mining and analyzing source code changes and their impacts
- Program completion and program synthesis
- Auto-repairing programs and (build) configurations
- Vulnerability detection and remediation
- Generating API documentation and/or commit messages
Literatur
Various references to our and related publications will be provided in the course.
Prüfungsinformationen
Prüfungsmethode/n
One lab assignment on automating a software engineering task, student presentation and written report
Prüfungsinhalt/e
Lab assignment on automating a software engineering task
Beurteilungskriterien/-maßstäbe
The following criteria are used:
- Quality of the solution
- Quality of the presentation (content, style, language, slides)
- Quality of the written report (content, language)
Please note, the use of AI tools in this course is generally permitted throughout the work and writing process. However, students agree to disclose any use of AI tools in the work and text product and to mark AI-generated code and text passages accordingly. Furthermore, students assume sole responsibility for the code and text produced.
Beurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Masterstudium Informatics
(SKZ: 911, Version: 19W.2)
-
Fach: Software Engineering
(Wahlfach)
-
Weitere LVen aus dem gewählten Spezialisierungsfach (
0.0h XX / 12.0 ECTS)
- 623.828 Current Topics in Software Engineering: AI for Software Engineering (2.0h VC / 4.0 ECTS) Absolvierung im 1., 2. Semester empfohlen
-
Weitere LVen aus dem gewählten Spezialisierungsfach (
0.0h XX / 12.0 ECTS)
-
Fach: Software Engineering
(Wahlfach)
- Masterstudium Information Management
(SKZ: 922, Version: 19W.1)
-
Fach: Specialisation in Information Management
(Wahlfach)
-
Specialisation in Information Management (
0.0h VO, VC, KS / 16.0 ECTS)
- 623.828 Current Topics in Software Engineering: AI for Software Engineering (2.0h VC / 4.0 ECTS) Absolvierung im 1., 2., 3. Semester empfohlen
-
Specialisation in Information Management (
0.0h VO, VC, KS / 16.0 ECTS)
-
Fach: Specialisation in Information Management
(Wahlfach)
- Masterstudium Information Management
(SKZ: 922, Version: 23W.1)
-
Fach: Specialisation in Information Management
(Wahlfach)
-
Specialisation in Information Management (
0.0h VO, VC, KS / 16.0 ECTS)
- 623.828 Current Topics in Software Engineering: AI for Software Engineering (2.0h VC / 4.0 ECTS) Absolvierung im 1., 2., 3. Semester empfohlen
-
Specialisation in Information Management (
0.0h VO, VC, KS / 16.0 ECTS)
-
Fach: Specialisation in Information Management
(Wahlfach)