Providing automated support for model selection is a significant research challenge in model management. Organizations maintain vast growing repositories of analytical models, typically in the form of spreadsheets. Effective reuse of these models could result in significant cost savings and improvements in productivity. However, in practice, model reuse is severely limited by two main challenges: (1) lack of relevant information about the models maintained in the repository, and (2) lack of end user knowledge that prevents them from selecting appropriate models for a given problem solving task. This study built on the existing model management literature to address these research challenges. First, this research captured the relevant meta-information about the models. Next, it identified the features based on which models are selected. Finally, it used Analytic Hierarchy Process (AHP) to select the most appropriate model for any specified problem. AHP is an established method for multi-criteria decision-making that is suitable for the model selection task. To evaluate the proposed method for automated model selection, this study developed a simulated prototype system that implemented this method and tested it in two realistic end-user model selection scenarios based on previously benchmarked test problems.

Models and modelling plays an important role in science and ontology. Focus of the thesis is Management accounting in the perspective of a model representation. Research is based upon the empirical data from Czech biggest Top 200 (Volume of sales) non-financial subjects. Examined are basic characteristics of management accounting from present science papers or basic literature. Work also point out some problems with quantitative measuring of nonquantitative variables from a high variable respondent sample.

Model integration that allows multiple models to work together for solving a sophisticated problem has been an important research issue in the management of decision models. The recent development of the service-oriented architecture (SOA) has provided an opportunity to apply this new technology to support model integration. This is particularly critical when more and more models are delivered as web services. A web-services-based approach to model management is useful in providing effective decision support. In the past, existing literature has adopted the approach that treated a model as a service. Model integration can be thought of as a composition of web services. In the composition process, proper components and their relationships must be properly identified. This requires accurate model definition and reasoning. In the research, we propose a semantic-based approach for developing such as system. The approach uses DAML-S to describe the capability of a service. Then the system can discover proper services for a particular requirement by using semantic matching on these DAML-S documents. When suitable web services are found, the system uses BPEL4WS to composite them together. The resulting composite web service can be applied to decision support. A prototype that demonstrates the feasibility of the proposed approach is implemented in Java.

In large-scale model-based development, developers periodically need to combine collections of interrelated models. These models may capture different features of a system, describe alternative perspectives on a single feature, or express ways in which different features alter one another's structure or behaviour. We refer to the process of combining a set of interrelated models as "model fusion". A number of factors make model fusion complicated. Models may overlap, in that they refer to the same concepts, but these concepts may be presented differently in each model, and the models may contradict one another. Models may describe independent system components, but the components may interact, potentially causing undesirable side effects. Finally, models may cross-cut, modifying one another in ways that violate their syntactic or semantic properties. In this thesis, we study three instances of the fusion problem for "behavioural models", motivated by real-world applications. The first problem is combining "partial" models of a single feature with the goal of creating a more complete description of that feature. The second problem is maintenance of "variant" specifications of individual features. The goal here is to combine the variants while preserving their points of difference (i.e., variabilities). The third problem is analysis of interactions between models describing "different" features. Specifically, given a set of features, the goal is to construct a composition such that undesirable interactions are absent. We provide an automated tool-supported solution to each of these problems and evaluate our solutions. The main novelties of the techniques presented in this thesis are (1) preservation of semantics during the fusion process, and (2) applicability to large and evolving collections of models. These are made possible by explicit modelling of partiality, variability and regularity in behavioural models, and providing semantic-preserving notions for relating these models.

In large-scale model-based development, developers periodically need to combine collections of interrelated models. These models may capture different features of a system, describe alternative perspectives on a single feature, or express ways in which different features alter one another's structure or behaviour. We refer to the process of combining a set of interrelated models as "model fusion". A number of factors make model fusion complicated. Models may overlap, in that they refer to the same concepts, but these concepts may be presented differently in each model, and the models may contradict one another. Models may describe independent system components, but the components may interact, potentially causing undesirable side effects. Finally, models may cross-cut, modifying one another in ways that violate their syntactic or semantic properties. In this thesis, we study three instances of the fusion problem for "behavioural models", motivated by real-world applications. The first problem is combining "partial" models of a single feature with the goal of creating a more complete description of that feature. The second problem is maintenance of "variant" specifications of individual features. The goal here is to combine the variants while preserving their points of difference (i.e., variabilities). The third problem is analysis of interactions between models describing "different" features. Specifically, given a set of features, the goal is to construct a composition such that undesirable interactions are absent. We provide an automated tool-supported solution to each of these problems and evaluate our solutions. The main novelties of the techniques presented in this thesis are (1) preservation of semantics during the fusion process, and (2) applicability to large and evolving collections of models. These are made possible by explicit modelling of partiality, variability and regularity in behavioural models, and providing semantic-preserving notions for relating these models.

L'Ingénierie Dirigée par les Modèles (IDM) a suscité un grand intérêt grâce aux avantages qu'elle offre. Enparticulier, l'IDM vise à accélérer le processus de développement et à faciliter la maintenance des logiciels. Mais avecl'augmentation permanente de la taille des modèles et de leurs instances, l'exploitation des modèles et de leurs instances,en utilisant des outils classiques présente des insuffisances liées au passage à l'échelle. L'utilisation des bases de donnéesest une des solutions proposées pour répondre à ce problème. Dans ce contexte, deux approches ont été proposées. Lapremière consiste à équiper les outils de modélisation avec des bases de données dédiées au stockage de modèles,appelées model repositories (p. ex. EMFStore). Ces bases de données sont équipées de langages d'exploitation limitésseulement à l'interrogation des modèles et des instances. Par conséquent, ces langages n'offrent aucune capacité poureffectuer des opérations avancées sur les modèles telles que la transformation de modèles ou la génération de code. Ladeuxième approche, que nous suivons dans notre travail, consiste à définir des environnements persistants en base dedonnées dédiés à la méta-modélisation. Ces environnements sont appelés systèmes de méta-modélisation persistants(PMMS). Un PMMS consiste en (i) une base de données dédiée au stockage des méta-modèles, des modèles et de leursinstances, et (ii) un langage d'exploitation associé possédant des capacités de méta-modélisation et d'exploitation desmodèles. Plusieurs PMMS ont été proposés tels que ConceptBase ou OntoDB/OntoQL. Ces PMMS supportentprincipalement la définition de la sémantique structurelle et descriptive des méta-modèles et des modèles en terme de(méta-)classes, (méta-)attributs, etc. Par contre, ces PMMS fournissent des mécanismes limités pour définir la sémantiquecomportementale nécessaire à l'exploitation des modèles et des instances. En effet, la sémantique comportementalepourrait être utile pour calculer des concepts dérivés, effectuer des transformations de modèles, générer du code source,etc. Ainsi, nous proposons dans notre travail d'étendre les PMMS avec la possibilité d'introduire dynamiquement desopérations qui peuvent être implémentées en utilisant des mécanismes hétérogènes. Ces opérations peuvent ainsi utiliserdes mécanismes internes au système de gestion de base de données (p. ex. les procédures stockées) tout comme desmécanismes externes tels que les services web ou les programmes externes (p. ex. Java, C++). Cette extension permetd'améliorer les PMMS en leur donnant une plus large couverture de fonctionnalités et une plus grande flexibilité. Pourvalider notre proposition, elle a été implémentée sur le prototype OntoDB/OntoQ et a été mise en oeuvre dans troiscontextes différents : (1) pour calculer les concepts dérivés dans les bases de données à base ontologique, (2) pouraméliorer une méthodologie de conception de base de données à base ontologique et finalement (3) pour faire de latransformation et de l'analyse des modèles des systèmes embarqués temps réel.

Context. Software systems, becoming larger and more complex day-by-day, have resulted in software development processes to become more complex to understand and manage. Many companies have started to adapt distributed software engineering practices that would allow them to work in distributed teams at different organizations and/or geographical locations. For example, model-driven engineering methods are being used in such global software engineering projects. Among the activities in model-based software development, consistency checking is one of the widely known ones. Consistency checking is concerned with consistent models; in particular, having a consistent group of multiple models for a whole system, e.g., multiple models produced by distributed teams. Objectives. This thesis aims to find out how ‘Global Consistency Checking (GCC)’ can be utilized for exploring inconsistency problems between distributed models; particularly among UML class diagram relationships (in terms of consistency), as well as how GCC can be scaled with large number of models and relationships. Thereby, these inconsistencies are also aimed to incrementally resolve in our approach. Methods. We made a review in distributed software development domain and model management, in particular, methods of consistency checking between ‘Distributed Models (DM)’. Next, we conducted two case studies in two problem domains in order to apply our ‘consistency checking methodology’. We concurrently constructed and implemented new consistency rules, most of which are gathered from literatures and brainstorming with our coordinators. Generally, the method contains implementing different models of the case studies with a tool support and trying to figure out overlaps, merging models and checking the merged model against the consistency rules, and evaluating the results of GCC. We mainly addressed issues focused on consistency checking of individual models and the mapping between them e.g., pair-wise consistency checking (PCC), which are incapable of fully addressing problems against any consistency rules encountered in distributed environments. Results. We have identified seven types of inconsistency, which are divided in two groups named ‘Global inconsistency’ and ‘Pair-wise inconsistency’. In the first case study, we have 94 global inconsistencies and 73 pair-wise. In the second one, 14 global and 25 pair-wise inconsistencies are resulted. During ‘Resolution approach’, we followed six steps as a ‘systematic procedure’ for resolving these inconsistencies and constructed new merged model in each iteration. The initial merged model (inconsistent model) as an input for the first step has 1267 elements, and the consistent merged model (the output) from the sixth step has 686 elements. ‘time duration’ and ‘required effort’ for checking consistency against each ‘consistency rule’ were recorded, analyzed and illustrated in Sections 4.1.5 and 4.2.4. Conclusions. We concluded that GCC enables us to explore the inconsistencies, inclusive of resolving them and therefore, refining the relationships between different models, which are difficult to detect by e.g., a pair-wise method. The most important issues are: The number of model comparisons conducted by PCC, The inability of PCC for identifying some inconsistencies, Model relationships refinement and classification based on PCC approach will not lead to a final consistent DM, whereas, GCC guarantees it. Consistency rules application, inconsistency identification and resolving them could be generalized to any UML class diagram model representing a problem domain within the fields of consistency checking in software engineering. / 0046760850792, 0046737749752

Radio frequency identification (RFID) technology is adopted in supply chain as it possesses high potential for optimization. However, the adoption is constrained with management and technological issues for certain domains. Applicability and profitability of the technology and implementation approaches as well as maturity of the technology and data integration are few of the concerns in this regard. Therefore, many enterprises are still skeptical about investment in RFID technology. Rightly, for instance, there are no appropriate approaches for management of the RFID system implementations at present that consider specific concerns of preparation of the food manufacturing enterprises. This research suggests a reference model for the purpose. The model is a result of extensive literature reviews and practice-oriented research aiming practical solutions to the problems of the respective domain. The model, which involves planning, organization and realization of RFID system implementation activities, considers multiple facets of RFID system implementations in order to increase understanding of RFID technology (i.e. knowledge development), ease decision making of an RFID implementation (i.e. willingness), and reduce cost and complexity of RFID system implementations (i.e. effectiveness and efficiency). It is an artifact of design-oriented information system research and includes a frame of reference, a process model, input and output templates, and tools and techniques. The model is applied in ‘real life context’ in order to achieve objectives of the involved enterprises. Similarly, the model aims effectiveness and efficiency in the future use, for example, by providing free of cost acquisition and appropriateness for manufacturing industries of food businesses of Saxony-Anhalt. However, adaptation efforts (e.g. by instantiation or specialization) may vary depending on the skills of users of individual enterprises. The reference model provides flexibility in terms of independence from specific vendors, openness by complying with available standards (e.g. PMBOK), and relationship to RFID system development artifacts during technical work realization.

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