Jens Kosiol, Steffen Zschaler
We present a nesting-free normal form for the formalism of nested conditions and constraints in the context of finite lattices of subgraphs.
Alexander Lauer, Jens Kosiol, Leen Lambers et al.
Conflict and dependency analysis is an important static analysis tool that provides an overview of the potential interactions of (graph) transformation rules. This analysis is based on critical pairs and initial conflicts, which represent conflicting transformations in a minimal context. However, the crucial information about a conflicting transformation pair is contained in much smaller structures, called disabling/conflict essences in existing research. Recently, we introduced disabling essences for rules with application conditions which contain the information on how an application condition can be violated by another rule. In this paper, we extend the notion of disabling essences to support not only application conditions in Alternating Quantifier Normal Form, but also arbitrary nested conditions. We introduce (symbolic) conflict essences that are constructed from disabling essences and which capture the interaction between two rules. We show that a transformation pair is parallel dependent if and only if a symbolic conflict essence can be embedded into it and relate symbolic conflict essences to initial conflicts for transformation rules with application conditions. We present our results for adhesive HLR categories, which includes several types of graph-like structures.
Lars Fritsche, Jens Kosiol, Adrian Möller et al.
Concurrent model synchronization is the task of restoring consistency between two correlated models after they have been changed concurrently and independently. To determine whether such concurrent model changes conflict with each other and to resolve these conflicts taking domain- or user-specific preferences into account is highly challenging. In this paper, we present a framework for concurrent model synchronization algorithms based on Triple Graph Grammars (TGGs). TGGs specify the consistency of correlated models using grammar rules; these rules can be used to derive different consistency restoration operations. Using TGGs, we infer a causal dependency relation for model elements that enables us to detect conflicts non-invasively. Different kinds of conflicts are detected first and resolved by the subsequent conflict resolution process. Users configure the overall synchronization process by orchestrating the application of consistency restoration fragments according to several conflict resolution strategies to achieve individual synchronization goals. As proof of concept, we have implemented this framework in the model transformation tool eMoflon. Our initial evaluation shows that the runtime of our presented approach scales with the size of model changes and conflicts, rather than model size.
Lars Fritsche, Jens Kosiol, Andy Schürr et al.
Model synchronization, i.e., the task of restoring consistency between two interrelated models after a model change, is a challenging task. Triple Graph Grammars (TGGs) specify model consistency by means of rules that describe how to create consistent pairs of models. These rules can be used to automatically derive further rules, which describe how to propagate changes from one model to the other or how to change one model in such a way that propagation is guaranteed to be possible. Restricting model synchronization to these derived rules, however, may lead to unnecessary deletion and recreation of model elements during change propagation. This is inefficient and may cause unnecessary information loss, i.e., when deleted elements contain information that is not represented in the second model, this information cannot be recovered easily. Short-cut rules have recently been developed to avoid unnecessary information loss by reusing existing model elements. In this paper, we show how to automatically derive (short-cut) repair rules from short-cut rules to propagate changes such that information loss is avoided and model synchronization is accelerated. The key ingredients of our rule-based model synchronization process are these repair rules and an incremental pattern matcher informing about suitable applications of them. We prove the termination and the correctness of this synchronization process and discuss its completeness. As a proof of concept, we have implemented this synchronization process in eMoflon, a state-of-the-art model transformation tool with inherent support of bidirectionality. Our evaluation shows that repair processes based on (short-cut) repair rules have considerably decreased information loss and improved performance compared to former model synchronization processes based on TGGs.