Abstract. Software evolution and the resulting need to continuously adapt the software is one of the main challenges for software engineering. The model-driven development movement therefore aims at improving the longevity of software by keeping the development artifacts more consistent and better changeable by employing models and to a certain degree automated model operations. Another trend are systems that tackle the challenge at runtime by being able to adapt their structure and behavior to be more flexible and operate in more dynamic environments (e.g., context-aware software, autonomic computing, self-adaptive software). Finally, models at runtime, where the benefits of model-driven development are employed at runtime to support adaptation capabilities, today lead towards a unification of both ideas. In this paper, we present graph transformations and show that they can be employed to engineer solutions for all three outlined cases. Furthermore, we will even be able to demonstrate that graph transformation based technology has the potential to also unify all three cases in a single scenario where models at runtime and runtime adaptation is linked with classical MDE. Therefore, we at first provide an introduction in graph transformations, then present the related techniques of Story Pattern and Triple Graph Grammars, and demonstrate how with the help of both techniques model transformations, adaptation behavior and runtime model framework work. In addition, we show that due to the formal underpinning analysis becomes possible and report about a number of successful examples.
Abstract. Systems of Systems (SoS) have started to emerge as a consequence of the general trend toward the integration of beforehand isolated systems. To unleash the full potential, the contained systems must be able to operate as elements in open, dynamic, and deviating SoS architectures and to adapt to open and dynamic contexts while being developed, operated, evolved, and governed independently. We name the resulting advanced SoS to be smart as they must be self-adaptive at the level of the individual systems and self-organizing at the SoS level to cope with the emergent behavior at that level. In this paper we analyze the open challenges for the envisioned smart SoS. In addition, we discuss our ideas for tackling this vision with our SMARTSOS approach that employs open and adaptive collaborations and models at runtime. In particular, we focus on preliminary ideas for the construction and assurance of smart SoS.
In the recent years, improvements in robotic hardware have not been matched by advancements in robotic software and the gap between those two areas has been widening. To cope with the increasing complexity of novel robotic embedded systems an integrated and continuous software development process is required supporting different development activities and stages being integrated into an overall development methodology, supported by libraries, elaborated tools and toolchains. For an efficient development of robotic systems a seamless integration between different activities and stages is required. In the domain of automotive systems, such an overall development methodology, consisting of different development activities/stages and supported by elaborated libraries, tools and toolchains, already exists. In this paper, we show how to adapt an existing methodology for the development of automotive embedded systems for being applicable on robotic systems.
The AUTomotive Open System ARchitecture (AUTOSAR) is the emerging standard for the development of real-time embedded automotive systems. Several tools exist that support the development as well as the analysis of AUTOSAR systems. Simulation environments use models or generated source code for testing and scenario-based simulation purposes. Unfortunately, there is a lack of methods and tools supporting the early timing analysis of AUTOSAR systems. In this work, we show how to automatically transform a given AUTOSAR architecture to an interconnected set of timed automata that represents the state-based timing behavior of the system. The derived timed automata models are used for analyzing the timing behavior in an early development stage. Furthermore, we show how to analyze the resulting timing behavior supporting abstract and incomplete AUTOSAR systems using the tool UPPAAL.
Recently, due to an increasing demand on functionality and flexibility, beforehand isolated systems have become interconnected to gain powerful adaptive System of Systems (SoS) solutions with an overall robust, flexible and emergent behavior. The adaptive SoS comprises a variety of different system types ranging from small embedded to adaptive cyber-physical systems. On the one hand, each system is independent, follows a local strategy and optimizes its behavior to reach its goals. On the other hand, systems must cooperate with each other to enrich the overall functionality to jointly perform on the SoS level reaching global goals, which cannot be satisfied by one system alone. Due to difficulties of local and global behavior optimizations conflicts may arise between systems that have to be solved by the adaptive SoS.This thesis proposes a modeling language that facilitates the description of an adaptive SoS by considering the adaptation capabilities in form of feedback loops as first class entities. Moreover, this thesis adopts the Models@runtime approach to integrate the available knowledge in the systems as runtime models into the modeled adaptation logic. Furthermore, the modeling language focuses on the description of system interactions within the adaptive SoS to reason about individual system functionality and how it emerges via collaborations to an overall joint SoS behavior. Therefore, the modeling language approach enables the specification of local adaptive system behavior, the integration of knowledge in form of runtime models and the joint interactions via collaboration to place the available adaptive behavior in an overall layered, adaptive SoS architecture.Beside the modeling language, this thesis proposes analysis rules to investigate the modeled adaptive SoS, which enables the detection of architectural patterns as well as design flaws and pinpoints to possible system threats. Moreover, a simulation framework is presented, which allows the direct execution of the modeled SoS architecture. Therefore, the analysis rules and the simulation framework can be used to verify the interplay between systems as well as the modeled adaptation effects within the SoS. This thesis realizes the proposed concepts of the modeling language by mapping them to a state of the art standard from the automotive domain and thus, showing their applicability to actual systems. Finally, the modeling language approach is evaluated by remodeling up to date research scenarios from different domains, which demonstrates that the modeling language concepts are powerful enough to cope with a broad range of existing research problems.-I - Zusammenfassung
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