A Variance-Based Drift Metric for Inconsistency Estimation in Model Variant Sets

By: Karl Kegel, Sebastian Götz, Ronny Marx, Uwe Aßmann

Abstract

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 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.

Keywords

Software Metrics, Model Metrics, Model Evolution

Cite as:

Karl Kegel, Sebastian Götz, Ronny Marx, Uwe Aßmann, “A Variance-Based Drift Metric for Inconsistency Estimation in Model Variant Sets”, Journal of Object Technology, Volume 23, no. 3 (July 2024), pp. 1-14, doi:10.5381/jot.2024.23.3.a2.