Abstract In a collaborative multi-user model-driven engineering context, it becomes important to track who changed what model part how and why. Operation-based versioning addresses this need by persisting a meaningful edit history which enables a single user to navigate through a model’s evolution over time, to analyze arbitrary previous model versions, or to trace the impact of an operation. However, to load a distinct prior version, it must be restored by reapplying all previous operations, which is time-consuming and, thus, interrupts a user’s workflow. Caching with a fixed distance between caches helps to overcome this problem to the cost of increasing memory requirements. Further, there is no caching approach supporting branches, merges, and possibly resolved conflicts. We propose two advanced caching strategies for operation-based versioning capable of the previously mentioned features: zonal and adaptive caching. Both strategies reduce the memory in use by not applying the same static distance between two caches across the whole edit history. Instead, the distance increases depending on a version’s age and its distance to a branch’s head. Both strategies aim to reduce the restoration time of arbitrary prior versions below a threshold to not interrupt a user’s flow of thought. Zonal caching employs predefined distances compatible with a broad range of model sizes. In contrast, adaptive caching derives the distances individually depending on the initial time to load the model on a user’s computer and the model’s size.We conducted controlled experiments with models of varying sizes and compared the time to restore model versions and the memory in use for no caching, caching with static distances, zonal, and adaptive strategies on different computers. The developed strategies decrease the time to restore a version remarkably while using less memory than static caching. Our results show that for all considered systems and models individual adaptive caching reduces memory usage even further compared to zone-based caching while still satisfying application responsiveness requirements.

Context: Technically sophisticated systems are the result of the joint work of several domain experts. However, the more people collaborate, the more important it becomes to make the model evolution and its single edit operations accessible and comprehensible for involved stakeholders. Objective: We developed the textual and semantic aware query language EditQL. It enables domain experts to search for model versions, changes, and causing edit operations within a model's edit history. Based on an operation-based versioning system, the query language covers both edit operations and all model states. Method: We systematically elaborate the requirements of a query language for edit histories. Based on this, we present a DSL integrated into an existing modeling tool. We conducted a mixed-methods usability study with 15 participants in which they had to answer various questions about a model's evolution using EditQL. Results: All participants agreed on the usefulness of the query language, particularly the possibility of querying for semantic changes in the model. The measured System Usability Scale (SUS) scores range from OK to good. In addition, we identified a set of possible improvements. Conclusion: The study confirmed that EditQL and the underlying concepts are suitable tools to help domain experts understand the evolution of a model.

Context: Modeling industrial systems is mostly done collaboratively. In such a scenario, a model is modified by multiple people over a possibly long period of time. In consequence, modelers have to be able to understand a model’s evolution and, in particular, what elements of a model have changed, how, why, when, and by whom. Objective: We derive six distinct user goals and systematically design a graphical modeling languageagnostic set of tools that support users in achieving these goals. Method: We implement those tools and integrate them into an existing graphical modeling tool for technology roadmaps. To measure the tools’ usability, we conducted a mixed-methods study with participants of different levels of experience. With the set of developed tools at hand, in different scenarios, participants had to answer several questions regarding the evolution of a model. Results: The SUS score for assessing usability ranged from 80 to 95, indicating good to excellent usability. Task completeness (measured per scenario) ranged from 92% to 100%. Further, participants emphasized the added value of the tools while completing the scenarios. Conclusion: Although participants stated that the set of tools can be classified as expert tools, the developed tools achieve the goal of enabling users to comprehend changes made by others and trace the impacts of operations.

The introduction of major innovations in industry requires a collaboration across the whole supply chain. A common way to organize such a collaboration is the use of technology roadmaps, which act as an industry-wide long-term planning tool. Technology roadmaps are used to identify industry needs, estimate the availability of technological solutions, and identify the need for innovation in the future. Roadmaps are inherently both time-dependent and based on uncertain values, i.e., properties and structural components can change over time. Current approaches for model-driven engineering do not inherently support these aspects. We present a novel model-driven approach treating those aspects as first-class citizens. To address the problem of missing support for time in the context of roadmap modeling, we introduce the concepts of a common global time, time-dependent properties, and time-dependent availability. This includes requirements, properties, and the structure of the model or its components as well. These concepts result in a continuous range of various valid models over time instead of a single valid model at a certain point of time. We present concepts for an interactive graphical user interface to enable the user to efficiently interact with those models. We illustrate the application of these concepts on an industrial example of a next generation electrical fuse.