Empirical Study
Teaching
- Empirical Study on Merge Conflict Dynamics: The Role of Personas in Merge Resolutions
| Teaching
Context
Merge conflicts are a common challenge in collaborative software development, requiring developers to manually resolve inconsistencies between different code versions. Prior research has explored automated approaches to merge conflict resolution, but the impact of developer behavior and personas on the merge process remains not fully investigated [1].
- Energy Profiling vs. Runtime Profiling
| Teaching
Context
In present-day times of climate change all industry sectors should bring down their green house gas emissions (carbon footprint). However, the IT-sector’s emissions increase unchecked. The research area for this seminar thesis is the field of “green” software engineering. In this research area one aims at finding ways to lower the energy consumption of a piece of source code when run as a program. Using specialized registers (so called model specific registers) that deliver the cumulated energy consumption of the CPU one can track back energy consumption to different parts of a program.
- Evaluating Refactoring-Aware Merging: An Experimental Study
| Teaching
Context
Traditional merge tools (e.g., Git merge) often treat refactorings as conflicting changes, leading to unnecessary conflicts. On the contrary, a refactoring-aware approach may recognize and account for refactorings, preventing false positives in conflict detection.
- Undervolting
| Teaching
Context
In present-day times of climate change all industry sectors should bring down their green house gas emissions (carbon footprint). However, the IT-sector’s emissions increase unchecked. The research area for this seminar thesis is the field of “green” software engineering. In this research area one aims at finding ways to lower the energy consumption of a piece of source code when run as a program. Using specialized registers (so called model specific registers) that deliver the cumulated energy consumption of the CPU one can track back energy consumption to different parts of a program.