STAF 2024
Mon 8 - Thu 11 July 2024 Enschede, Netherlands
Mon 8 Jul 2024 14:30 - 15:00 at Waaier 2 - ECMFA Session 1 Chair(s): Adrian Rutle

Nowadays, iterative development has become a state-of-the-art engineering process. The shared artifacts, i.e., models, must be edited collaboratively to make iterative development work in large engineering teams. The typical non-real-time collaboration workflow consists of three phases: The collaborators create copies of the model; Each collaborator edits their variant (copy) of the model; The collaborators merge the edited models back into one. During the merge phase, conflicting changes become apparent and must be resolved. This is a time and resource-intensive task. However, if potential merge conflicts can be detected during the editing phase, the collaborators can take suitable measures in time. This work proposes an early warning system for merge conflicts in model-based development projects. We introduce the novel metric Drift to quantify the amount of inconsistency between all co-existing variants of a model. An increase in Drift indicates an increase in potential merge conflicts. We evaluate the correctness of the Drift for synthetical modeling projects and syntactical model differences. We develop an openly available tool for calculating the Drift for arbitrary Git repositories.

Mon 8 Jul

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

13:30 - 15:00
ECMFA Session 1ECMFA Technical Track at Waaier 2
Chair(s): Adrian Rutle Western Norway University of Applied Sciences
13:30
20m
Break
Prolonged lunch break
ECMFA Technical Track

13:50
10m
Day opening
Conference opening
ECMFA Technical Track
Adrian Rutle Western Norway University of Applied Sciences, Judith Michael RWTH Aachen University
14:00
30m
Research paper
Automated Proof Tactics for Model Transformation
ECMFA Technical Track
A: Julien Cohen Nantes Université, A: Massimo Tisi IMT Atlantique, LS2N (UMR CNRS 6004), A: Rémi Douence IMT Atlantique
14:30
30m
Research paper
A Variance-Based Drift Metric for Inconsistency Estimation in Model Variant Sets
ECMFA Technical Track
A: Karl Kegel Technische Universität Dresden, A: Sebastian Götz Technische Universität Dresden, A: Ronny Marx Technische Universität Dresden, A: Uwe Aßmann TU Dresden, Germany