Rewriting history: more power to creative people
Proceedings of the 23rd Australian Computer-Human Interaction Conference
A posteriori operation detection in evolving software models
Journal of Systems and Software
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Search-based refactoring detection
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Bridging state-based differencing and co-evolution
Proceedings of the 6th International Workshop on Models and Evolution
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In recent years, models are increasingly used throughout the entire lifecycle in software development projects. In effect, the need for collaborating on these models emerged, requiring change tracking and versioning. However, many researchers have shown that existing methods and tools for Version Control (VC) do not work well on graph-like models, such as UML, SysML or domain-specific modeling languages. To alleviate this, alternative techniques and methods have been proposed which can be classified into state-based and operation-based approaches. Existing research shows advantages of operation-based over state-based approaches in selected use cases, such as conflict detection or merging. However, there are only few results available on the advantages of operation-based approaches in the most common use case of a VC system: review and understand change. In this paper, we present and discuss both approaches and their use cases. Moreover, we present the results of an empirical study to compare a state-based with an operation-based approach for the use case of reviewing and understanding change. For this study, we have mined an operation-based model repository and interviewed users to assess their understanding of randomly selected changes. Our results indicate that users better understand complex changes in the operation-based representation.