Avoiding Unnecessary Information Loss: Correct and Efficient Model Synchronization Based on Triple Graph Grammars

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.Comment: 33 pages, 20 figures, 3 table

Towards Consistency Management for a Business-Driven Development of SOA

The usage of the Service Oriented Architecture (SOA) along with the Business Process Management has emerged as a valuable solution for the complex (business process driven) system engineering. With a Model Driven Engineering where the business process models drive the supporting service component architectures, less effort is gone into the Business/IT alignment during the initial development activities, and the IT developers can rapidly proceed with the SOA implementation. However, the difference between the design principles of the emerging domainspecific languages imposes serious challenges in the following re-design phases. Moreover, enabling evolutions on the business process models while keeping them synchronized with the underlying software architecture models is of high relevance to the key elements of any Business Driven Development (BDD). Given a business process update, this paper introduces an incremental model transformation approach that propagates this update to the related service component configurations. It, therefore, supports the change propagation among heterogenous domainspecific languages, e.g., the BPMN and the SCA. As a major contribution, our approach makes model transformation more tractable to reconfigure system architecture without disrupting its structural consistency. We propose a synchronizer that provides the BPMN-to-SCA model synchronization with the help of the conditional graph rewriting

Development of Transformations from Business Process Models to Implementations by Reuse

This paper presents an approach for developing transformations from business process models to implementations that facilitates reuse. A transformation is developed as a composition of three smaller tasks: pattern recognition, pattern realization and activity transformation. The approach allows one to reuse the definition and implementation of pattern recognition and pattern realization in the development of transformations targeting different business process modeling and implementation languages. In order to decouple pattern recognition and pattern realization, the approach includes a pattern language to represent the output of the pattern recognition task, which forms the input of the pattern realization task

Category Theory and Model-Driven Engineering: From Formal Semantics to Design Patterns and Beyond

There is a hidden intrigue in the title. CT is one of the most abstract mathematical disciplines, sometimes nicknamed "abstract nonsense". MDE is a recent trend in software development, industrially supported by standards, tools, and the status of a new "silver bullet". Surprisingly, categorical patterns turn out to be directly applicable to mathematical modeling of structures appearing in everyday MDE practice. Model merging, transformation, synchronization, and other important model management scenarios can be seen as executions of categorical specifications. Moreover, the paper aims to elucidate a claim that relationships between CT and MDE are more complex and richer than is normally assumed for "applied mathematics". CT provides a toolbox of design patterns and structural principles of real practical value for MDE. We will present examples of how an elementary categorical arrangement of a model management scenario reveals deficiencies in the architecture of modern tools automating the scenario.Comment: In Proceedings ACCAT 2012, arXiv:1208.430

Neuronal Synchronization Can Control the Energy Efficiency of Inter-Spike Interval Coding

The role of synchronous firing in sensory coding and cognition remains controversial. While studies, focusing on its mechanistic consequences in attentional tasks, suggest that synchronization dynamically boosts sensory processing, others failed to find significant synchronization levels in such tasks. We attempt to understand both lines of evidence within a coherent theoretical framework. We conceptualize synchronization as an independent control parameter to study how the postsynaptic neuron transmits the average firing activity of a presynaptic population, in the presence of synchronization. We apply the Berger-Levy theory of energy efficient information transmission to interpret simulations of a Hodgkin-Huxley-type postsynaptic neuron model, where we varied the firing rate and synchronization level in the presynaptic population independently. We find that for a fixed presynaptic firing rate the simulated postsynaptic interspike interval distribution depends on the synchronization level and is well-described by a generalized extreme value distribution. For synchronization levels of 15% to 50%, we find that the optimal distribution of presynaptic firing rate, maximizing the mutual information per unit cost, is maximized at ~30% synchronization level. These results suggest that the statistics and energy efficiency of neuronal communication channels, through which the input rate is communicated, can be dynamically adapted by the synchronization level.Comment: 47 pages, 14 figures, 2 Table

Symmetries, Cluster Synchronization, and Isolated Desynchronization in Complex Networks

Synchronization is of central importance in power distribution, telecommunication, neuronal, and biological networks. Many networks are observed to produce patterns of synchronized clusters, but it has been difficult to predict these clusters or understand the conditions under which they form, except for in the simplest of networks. In this article, we shed light on the intimate connection between network symmetry and cluster synchronization. We introduce general techniques that use network symmetries to reveal the patterns of synchronized clusters and determine the conditions under which they persist. The connection between symmetry and cluster synchronization is experimentally explored using an electro-optic network. We experimentally observe and theoretically predict a surprising phenomenon in which some clusters lose synchrony while leaving others synchronized. The results could guide the design of new power grid systems or lead to new understanding of the dynamical behavior of networks ranging from neural to social

Effective representation of RT-LOTOS terms by finite time petri nets

The paper describes a transformational approach for the specification and formal verification of concurrent and real-time systems. At upper level, one system is specified using the timed process algebra RT-LOTOS. The output of the proposed transformation is a Time Petri net (TPN). The paper particularly shows how a TPN can be automatically constructed from an RT-LOTOS specification using a compositionally defined mapping. The proof of the translation consistency is sketched in the paper and developed in [1]. The RT-LOTOS to TPN translation patterns formalized in the paper are being implemented. in a prototype tool. This enables reusing TPNs verification techniques and tools for the profit of RT-LOTOS