Guidelines and Selection Criteria for Composing Analysis Techniques
| Typ | Masterarbeit | |
|---|---|---|
| Aushang | Master-Thesis.pdf | |
| Betreuer | Wenden Sie sich bei Interesse oder Fragen bitte an: Bahareh Taghavi (E-Mail: bahareh.taghavi@kit.edu, Telefon: +4917661623035) |
Motivation
Modern systems, such as large-scale software are highly complex. To ensure they operate reliably and meet quality standards, we rely on analysis techniques that evaluate their structure, behavior, and performance. But in most cases, a single technique cannot cover all aspects of these systems. To develop tailored and effective analysis methods, it is crucial to combine multiple analysis techniques, especially given the diverse quality properties and the overlap of multiple domains. This approach is known as analysis composition, a strategic method where specialized techniques work together to provide a complete picture.
However, there is a gap:
- How do we choose the proper composition operators (the mechanisms that connect these techniques)?
- When should we use existing operators, and when do we need to design new ones?
Tasks
- Identify selection criteria for composition operators (e.g., the type of analysis, such as black-box, white-box, or grey-box).
- Develop a classification scheme that includes operator types and selection criteria.
- Analyze research gaps and assess the applicability of current approaches.
Benefits
- Close connection to ongoing research projects
- Opportunity to contribute to a scientific publication
- Excellent working environment and intensive support (English)