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Astract: AutomationML provides a versatile modeling environment for the description of production systems. However, when starting a new AutomationML project, or when serializing existing data with the AutomationML format, there are no rules on how to structure these models in a meaningful way. In this work, we present an approach for structuring AutomationML models, based on the IEC 62264 standard. In our approach we are implementing the process of serializing IEC 62264 information declaratively, by leveraging the power of model transformations, as they are applied in the context of model-driven (software) engineering.

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Astract: Current trends in manufacturing lead to more intelligent products, produced in global supply chains in shorter cycles, taking more and complex requirements into account. To manage this increasing complexity, cognitive decision support systems, building on data analytic approaches and focusing on the product life cycle, stages seem a promising approach. With two high-tech companies (world market leader in their domains) from Austria, we are approaching this challenge and jointly develop cognitive decision support systems for three real world industrial use cases. Within this position paper, we introduce our understanding of cognitive decision support and we introduce three industrial use cases, focusing on the requirements for cognitive decision support. Finally, we describe our preliminary solution approach for each use case and our next steps

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Astract: IoT systems are becoming an increasingly important component of the civil and industrial infrastructure. With the growth of these IoT ecosystems, their complexity is also growing exponentially. In this paper we explore the problem of testing and evaluating large scale IoT systems at design time. To this end we employ simulated sensors with the physical and geographical characteristics of real sensors. Moreover, we propose Sensyml, a simulation environment that is capable of generating big data from cyber-physical models and real-world data. To the best of our knowledge it is the first approach to use a hybrid integration of real and simulated sensor data, that is also capable of being integrated into existing IoT systems. Sensyml is a cloud based Infrastructure-as-a-Service (IaaS) system that enables users to test both functionality and scalability of their IoT applications.

Keywords: Massive Open Online Courses, MOOCs, eLearning, Computer-based Training, Open and Distance-Learning
Astract: Massive open online courses are a fast growing learning eco-system with a wide distribution all over the world. The Vienna University of Technology hasn’t released any MOOC yet, but is planning to do so. Two courses are currently under development, both offered by the Faculty of Informatics. The choice of an appropiate plattform is very important for the success of a MOOC, so this work evaluates the best suitable platform for the Vienna University of Technology. During the work a list of requirements was created with the objective to check if the researched platform is suitable for the planned courses. The requirements do not only focus on the courses themselves but also consider the university’s current resources and goals, such as focusing on non-profit and Open Source distributions. Beside of an overview of different platforms also the historical development of MOOCs is described. For the purpose of this master’s thesis a prototype of MOOC was created on the basis of an Open Source MOOC platform distribution. Outcome of the analysis is that the platform edX is the best choice for implementation in the long-term. As a short-term objective the best choice is an implementation with the university’s own Moodle distribution TUWEL. Also the publishing via the Austrian MOOC Platform iMooX seems to be the best choice taking into account the university’s tight budget and resources. Due to the fact that most stakeholders for this project are mother tongue German, the whole work is written in their native language.

Keywords: Java annotations, UML profiles, Model-based software engineering, Forward engineering, Reverse engineering
Astract: The capability of UML profiles to serve as annotation mechanism has been recognized in both research and industry. Today’s modeling tools offer profiles specific to platforms, such as Java, as they facilitate model-based engineering approaches. However, considering the large number of possible annotations in Java, manually developing the corresponding profiles would only be achievable by huge development and maintenance efforts. Thus, leveraging annotation-based modeling requires an automated approach capable of generating platform-specific profiles from Java libraries. To address this challenge, we present the fully automated transformation chain realized by Jump, thereby continuing existing mapping efforts between Java and UML by emphasizing on annotations and profiles. The evaluation of Jump shows that it scales for large Java libraries and generates profiles of equal or even improved quality compared to profiles currently used in practice. Furthermore, we demonstrate the practical value of Jump by contributing profiles that facilitate reverse engineering and forward engineering processes for the Java platform by applying it to a modernization scenario.

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Astract: Modern cloud computing environments support a relatively high degree of automation in service provisioning, which allows cloud service customers (CSC) to dynamically acquire services required for deploying cloud applications. Cloud modeling languages (CMLs) have been proposed to address the diversity of features provided by cloud computing environments and support different application scenarios, e.g., migrating existing applications to the cloud, developing new cloud applications, or optimizing them. There is, however, still much debate in the research community on what a CML is and what aspects of a cloud application and its target cloud computing environment should be modeled by a CML. Furthermore, the distinction between CMLs on a fine-grained level exposing their modeling concepts is rarely made. In this article, we investigate the diverse features currently provided by existing CMLs. We classify and compare them according to a common framework with the goal to support CSCs in selecting the CML which fits the needs of their application scenario and setting. As a result, not only features of existing CMLs are pointed out for which extensive support is already provided but also in which existing CMLs are deficient, thereby suggesting a research agenda.

Keywords: Graphical Models, Diagrams, Model Review, Visualizations for Model Reviews
Astract: Code reviews are used today in several software projects to check changes before they are merged. The aim of code reviews is to identify and prevent mistakes introduced by changed artifacts before they are merged into the actual software project. Therefore, several tools exist to support developers with the reviewing process. Such tools usually allow to mark, comment and discuss parts of the code that are considered to be problematic, as well as track the history of the reviewed changes. Of course they also support approval and rejection of changes. As source code is usually text based, these tools focus on source code or text-based artifacts. However, like almost every artifact in a software development project, models also change over time. This also includes diagrams, or models with a graphical syntax, which may not necessarily have a textual representation that is understandable by the average user. Papyrus Unified Modeling Language (UML) Diagrams are an example for such models. Therefore the techniques and visualizations of existing tools are usually considered to be unsatisfactory for such models by developers. So developers have to combine the code review tool with comparison tools that support the given model types, but do not support the review process. However, this adds additional overhead and complexity that may affect the review negatively. This thesis provides visualizations and interaction techniques that support developers who need to handle diagrams as well as models with a graphical syntax during the review process. These visualizations and techniques are obtained by analyzing existing methods for model comparison, code review and related techniques that might support the review process. A case study is presented using a prototype implementation utilizing frameworks based on the Eclipse Modeling Framework to prove the value of the proposed visualizations and techniques.

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