Structural Graph-based Metamodel Matching

Data integration has been, and still is, a challenge for applications processing multiple heterogeneous data sources. Across the domains of schemas, ontologies, and metamodels, this imposes the need for mapping specifications, i.e. the task of discovering semantic correspondences between elements. Support for the development of such mappings has been researched, producing matching systems that automatically propose mapping suggestions. However, especially in the context of metamodel matching the result quality of state of the art matching techniques leaves room for improvement. Although the traditional approach of pair-wise element comparison works on smaller data sets, its quadratic complexity leads to poor runtime and memory performance and eventually to the inability to match, when applied on real-world data. The work presented in this thesis seeks to address these shortcomings. Thereby, we take advantage of the graph structure of metamodels. Consequently, we derive a planar graph edit distance as metamodel similarity metric and mining-based matching to make use of redundant information. We also propose a planar graph-based partitioning to cope with large-scale matching. These techniques are then evaluated using real-world mappings from SAP business integration scenarios and the MDA community. The results demonstrate improvement in quality and managed runtime and memory consumption for large-scale metamodel matching

Automatic Generation of Trace Links in Model-driven Software Development

Traceability data provides the knowledge on dependencies and logical relations existing amongst artefacts that are created during software development. In reasoning over traceability data, conclusions can be drawn to increase the quality of software. The paradigm of Model-driven Software Engineering (MDSD) promotes the generation of software out of models. The latter are specified through different modelling languages. In subsequent model transformations, these models are used to generate programming code automatically. Traceability data of the involved artefacts in a MDSD process can be used to increase the software quality in providing the necessary knowledge as described above. Existing traceability solutions in MDSD are based on the integral model mapping of transformation execution to generate traceability data. Yet, these solutions still entail a wide range of open challenges. One challenge is that the collected traceability data does not adhere to a unified formal definition, which leads to poorly integrated traceability data. This aggravates the reasoning over traceability data. Furthermore, these traceability solutions all depend on the existence of a transformation engine. However, not in all cases pertaining to MDSD can a transformation engine be accessed, while taking into account proprietary transformation engines, or manually implemented transformations. In these cases it is not possible to instrument the transformation engine for the sake of generating traceability data, resulting in a lack of traceability data. In this work, we address these shortcomings. In doing so, we propose a generic traceability framework for augmenting arbitrary transformation approaches with a traceability mechanism. To integrate traceability data from different transformation approaches, our approach features a methodology for augmentation possibilities based on a design pattern. The design pattern supplies the engineer with recommendations for designing the traceability mechanism and for modelling traceability data. Additionally, to provide a traceability mechanism for inaccessible transformation engines, we leverage parallel model matching to generate traceability data for arbitrary source and target models. This approach is based on a language-agnostic concept of three similarity measures for matching. To realise the similarity measures, we exploit metamodel matching techniques for graph-based model matching. Finally, we evaluate our approach according to a set of transformations from an SAP business application and the domain of MDSD

Synthesis of Model Transformations from Metamodels and Examples

Model transformations are central elements of model-driven engineering (MDE). However, model transformation development requires a high level of expertise in particular model transformation languages, and model transformation specifications are often difficult to manually construct, due to the lack of tool support, and the dependencies involved in transformation rules.In this thesis, we describe techniques for automatically or semi-automatically synthesising transformations from metamodels and examples, in order to reduce model transformation development costs and time, and improve model transformation quality.We proposed two approaches for synthesising transformations from metamodels. The first approach is the Data Structure Similarity Approach, an exhaustive metamodel matching approach, which extracts correspondences between metamodels by only focusing on the type of features. The other approach is the Search-based Optimisation Approach, which uses an optimisation algorithm to extract correspondences from metamodels by data structure similarity, name syntax similarity, and name semantic similarity. The correspondence patterns between the classes and features of two metamodels are extracted by either of these two methods. To enable the production of specifications in multiple model transformation languages from correspondences, we introduced an intermediate language which uses a simplified transformation notation to express transformation specifications in a language-independent manner, and defined the mapping rules from this intermediate language to different transformation languages.We also investigated Model Transformation by Examples Approach. We used machine learning techniques to learn model transformation rules from datasets of examples, so that the trained model could generate target model from source model directly.We evaluated our approaches on a range of cases of different kinds of transformation, and compared the model transformation accuracy and quality of our versions to the previously-developed manual versions of these cases.Key words: model transformation, model-driven engineering, transformation syn-thesis, metamodel matching, model transformation by example

Correct-by-Construction Development of Dynamic Topology Control Algorithms

Wireless devices are influencing our everyday lives today and will even more so in the future. A wireless sensor network (WSN) consists of dozens to hundreds of small, cheap, battery-powered, resource-constrained sensor devices (motes) that cooperate to serve a common purpose. These networks are applied in safety- and security-critical areas (e.g., e-health, intrusion detection). The topology of such a system is an attributed graph consisting of nodes representing the devices and edges representing the communication links between devices. Topology control (TC) improves the energy consumption behavior of a WSN by blocking costly links. This allows a mote to reduce its transmission power. A TC algorithm must fulfill important consistency properties (e.g., that the resulting topology is connected). The traditional development process for TC algorithms only considers consistency properties during the initial specification phase. The actual implementation is carried out manually, which is error prone and time consuming. Thus, it is difficult to verify that the implementation fulfills the required consistency properties. The problem becomes even more severe if the development process is iterative. Additionally, many TC algorithms are batch algorithms, which process the entire topology, irrespective of the extent of the topology modifications since the last execution. Therefore, dynamic TC is desirable, which reacts to change events of the topology. In this thesis, we propose a model-driven correct-by-construction methodology for developing dynamic TC algorithms. We model local consistency properties using graph constraints and global consistency properties using second-order logic. Graph transformation rules capture the different types of topology modifications. To specify the control flow of a TC algorithm, we employ the programmed graph transformation language story-driven modeling. We presume that local consistency properties jointly imply the global consistency properties. We ensure the fulfillment of the local consistency properties by synthesizing weakest preconditions for each rule. The synthesized preconditions prohibit the application of a rule if and only if the application would lead to a violation of a consistency property. Still, this restriction is infeasible for topology modifications that need to be executed in any case. Therefore, as a major contribution of this thesis, we propose the anticipation loop synthesis algorithm, which transforms the synthesized preconditions into routines that anticipate all violations of these preconditions. This algorithm also enables the correct-by-construction runtime reconfiguration of adaptive WSNs. We provide tooling for both common evaluation steps. Cobolt allows to evaluate the specified TC algorithms rapidly using the network simulator Simonstrator. cMoflon generates embedded C code for hardware testbeds that build on the sensor operating system Contiki

Model consistency management for systems engineering

Um der Komplexität der interdisziplinären Entwicklung moderner technischer Systeme Herr zu werden, findet die Entwicklung heutzutage meist modellbasiert statt. Dabei werden zahlreiche verschiedene Modelle genutzt, die jeweils unterschiedliche Gesichtspunkte berücksichtigen und sich auf verschiedenen Abstraktionsebenen befinden. Wenn die hierbei auftretenden Inkonsistenzen zwischen den Modellen ungelöst bleiben, kann dies zu Fehlern im fertigen System führen. Modelltransformations- und -synchronisationstechniken sind ein vielversprechender Ansatz, um solche Inkonsistenzen zu erkennen und aufzulösen. Existierende Modellsynchronisationstechniken sind allerdings nicht mächtig genug, um die komplexen Beziehungen in so einem Entwicklungsszenario zu unterstützen. In dieser Arbeit wird eine neue Modellsynchronisationstechnik präsentiert, die es erlaubt, Modelle verschiedener Sichten und Abstraktionsebenen zu synchronisieren. Dabei werden Metriken zur Erhöhung des Automatisierungsgrads eingesetzt, die Expertenwissen abbilden. Der Ansatz erlaubt unterschiedliche Grade an Benutzerinteraktion, von vollautomatischer Funktionsweise bis zu feingranularen manuellen Entscheidungen.The development of complex mechatronic systems requires the close collaboration of different disciplines, like mechanical engineering, electrical engineering, control engineering, and software engineering. To tackle the complexity of such systems, such a development is heavily based on models. Engineers use several models on different abstraction levels, for different purposes and with different view-points. Usually, a discipline-spanning system model is developed during the first, interdisciplinary system design phase. For the implementation phase, the disciplines use different models and tools to develop the discipline-specific aspects of the system. During such a model-based development, inconsistencies between the different discipline-specific models and the discipline-spanning system model are likely to occur, because changes to discipline-specific models may affect the discipline-spanning system model and models of other disciplines. These inconsistencies lead to increased development time and costs if they remain unresolved. Model transformation and synchronization are promising techniques to detect and resolve such inconsistencies. However, existing model synchronization solutions are not powerful enough to support the complex consistency relations of such an application scenario. In this thesis, we present a novel model synchronization technique that allows for synchronized models with multiple views and abstraction levels. To minimize the information loss and improve automation during the synchronization, it employs metrics to encode expert knowledge. The approach can be customized to allow different amounts of user interaction, from full automation to fine-grained manual decisions.Tag der Verteidigung: 24.10.2014Paderborn, Univ., Diss., 201

Über die Pragmatik der Graphischen Modellierung

Graphical models help to understand complex systems. However, with the user interaction paradigms established today, activities such as creating, maintaining or browsing graphical models can be very tedious. This thesis presents an approach to enhance productivity by focusing on the pragmatics of model-based design. The contribution includes an interpretation of the notion of pragmatics, orthogonal to syntax and semantics in Model-Driven Engineering (MDE). A proposal on pragmatics-aware modeling is given, employing sophisticated automated layout algorithms to close the gap between MDE and graph drawing theory. Thus, a view management logic presents customized views on models. These concepts get illustrated with the open source Kiel Integrated Environment for Layout Eclipse Rich Client (KIELER) with multiple applications including editing and simulation and shows how view management helps to tame complexity

Alignment of viewpoint heterogeneous design models: Emergency Department Case Study

International audienceGenerally, various models can be used to describe a given application domain on different aspects and thus give rise to several views. To have a complete view of the application domain, heterogeneous models need to be unified, which is a hard task to do. To tackle this problem, we have proposed a method to relate partial models without combining them in a single model. In our approach, partial models are organized as a network of models through a virtual global model called M1C (Model of correspondences between models) which conforms to a ubiquitous language based on a Meta-Model of Correspondences (MMC). This paper presents an application of our method to an “Emergency Department” case study. It has been performed as a collaborative process involving model designers and a supervisor. The focus is put on the building of the M1C model from 3 partial models

Search-based system architecture development using a holistic modeling approach

This dissertation presents an innovative approach to system architecting where search algorithms are used to explore design trade space for good architecture alternatives. Such an approach is achieved by integrating certain model construction, alternative generation, simulation, and assessment processes into a coherent and automated framework. This framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN), and feature model. The resultant holistic model can not only capture the structural, behavioral, and dynamic aspects of a system, allowing simulation and strong analysis methods to be applied, it can also specify the architectural design space. Both object-oriented analysis and design (OOA/D) and domain engineering were exploited to capture design variables and their domains and define architecture generation operations. A fully realized framework (with genetic algorithms as the search algorithm) was developed. Both the proposed framework and its suggested implementation, including the proposed holistic modeling approach and architecture alternative generation operations, are generic. They are targeted at systems that can be specified using object-oriented or process-oriented paradigm. The broad applicability of the proposed approach is demonstrated on two examples. One is the configuration of reconfigurable manufacturing systems (RMSs) under multi-objective optimization and the other is the architecture design of a manned lunar landing system for the Apollo program. The test results show that the proposed approach can cover a huge number of architecture alternatives and support the assessment of several performance measures. A set of quality results was obtained after running the optimization algorithm following the proposed framework --Abstract, page iii

Enabling collaborative modelling for a multi-site model-driven software development approach for electronic control units.

An important aspect of support for distributed work is to enable users at different sites to work collaboratively, across different sites, even different countries but where they may be working on the same artefacts. Where the case is the design of software systems, design models need to be accessible by more than one modeller at a time allowing them to work independently from each other in what can be called a collaborative modelling process supporting parallel evolution. In addition, as such design is a largely creative process users are free to create layouts which appear to better depict their understanding of certain model elements presented in a diagram. That is, that the layout of the model brings meaning which exceed the simple structural or topological connections. However, tools for merging such models tend to do so from a purely structural perspective, thus losing an important aspect of the meaning which was intended to be conveyed by the modeller. This thesis presents a novel approach to model merging which allows the preservation of such layout meaning when merging. It first presents evidence from an industrial study which demonstrates how modellers use layout to convey meanings. An important finding of the study is that diagram layout conveys domain-specific meaning and is important for modellers. This thesis therefore demonstrates the importance of diagram layout in model-based software engineering. It then introduces an approach to merging which allows for the preservation of domain-specific meaning in diagrams of models, and finally describes a prototype tool and core aspects of its implementation