Our research on dependability of software intensive systems has the vision of software engineering principles and methods integrated into systems engineering to systematically model and analyse software-intensive systems. This results in two major research lines: On the one hand we work on a scientific foundation of software design in an engineering sense: we should be able to predict the consequences on design decisions prior to realization. Therefore, we work on software architecture quality analysis, which includes architecture-based simulators for performance and reliability and architecture-based analyses of confidentiality, vulnerability but also maintainability. On the other hand, we research on the extension of software engineering based approaches to handle complexity to make them applicable to non-software domains, such as meta-modelling, model and view-based development and view, version and variant consistency management. Both research lines are specialized for automotive and mobility applications as well as for the Industry 4.0 domain.
- List of publications of DSiS members
- Research groups at DSiS
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- Karlsruhe Series on Software Design and Quality (Dissertations)
These are the current research projects at DSiS. See the projects page for a full list of current and former projects.
The digitization of industry (Industry 4.0) enacts ad-hoc cooperation between organizations in supply and production chains that goes beyond rigid hierarchical processes and increases efficiency and individualization of end-products. The high level of heterogeneity and complexity make these systems different from traditional systems as they introduce a high level of uncertainty. The uncertainty collides with the traditional access control, where decisions are sharp and fully determined. We are addressing this by considering uncertainty in design-time static analysis. We develop approaches that can classify uncertainty and consider it in the input and structure of the system. For the first type, we develop a trust model to specify the trust in access control properties. For the second one, we develop a variation model to analyze different instances of a system. Our project partner (Charles University Prague) investigates the runtime aspects of uncertainty. This is a joint Czech-German project.Fluid Trust Project Homepage
The research project RESPOND has been started in March 2019. The goal of RESPOND is a flexible and dynamic production system in the Industrial Internet of Things (IIoT) that monitors its own state and can react to errors and problems. The socio-technical production system carries out processes dynamically. The solution orchestrates IIoT nodes such as machines, sensors and edge devices and also integrates people with different roles into the Cyber-Physical Production System (CPPS). Among other things, flexibility is achieved by extending existing methods and tools for modeling and executing processes so that IIoT-capable devices can be used as generalized process resources with capabilities and self-description independent of the concrete application. The system can thus react resiliently at runtime to changes, uncertainties and errors in the spatial, temporal and interaction context.RESPOND Project Homepage
The research group Dependability of Software-intensive Systems is involved in the joint project Software-Defined Car through a total of four research topics. First, we address the anonymization of vehicle data at the level of software architecture. In this context, we provide techniques to analyze whether concrete anonymization procedures provide sufficient data protection. Second, we are researching the conception of an operationalized conceptual model for the joint handling of software variants and versions. Based on the Vitruvius approach, we develop a methodology for maintaining consistency of variants and versions consisting of heterogeneous artifacts. Third, we investigate typical modeling and programming languages with respect to common and different language features. On this basis, we develop a methodology for adapting and combining languages by configuring and composing language components. Fourth, we address the derivation of delta-based changes from views in software development. To this end, we provide a methodology for bidirectional consistency preservation of heterogeneous views.
The Palladio research project aims at the development of methods and tools for systematically constructing component based software architectures with predictable quality attributes. For predicting the quality of service of software architectures we utilise and enhance existing prediction models, such as stochastic Petri nets, queuing models and Markov models in general is a special modeling language targeted at model-driven performance predictions. The PCM is accompanied by several model transformations, which derive stochastic regular expressions, queuing network models, or Java source code from a software design model. Software architects can use the results of the analytical models to evaluate the feasibility of performance requirements, identify performance bottlenecks, and support architectural design decisions quantitatively.Palladio Project Homepage
During the development of large software-intensive systems, developers use several modeling languages and tools to describe a system from different viewpoints. Model-driven and view-based technologies have made it easier to define domain-specific languages and transformations. Nevertheless, using several languages leads to fragmentation of information, to redundancies in the system description, and eventually to inconsistencies. Inconsistencies have negative impacts on the system’s quality and are costly to fix. The Vitruvius approach adresses this issue with view-based methods for consistency modeling and preservation, and a model-driven development process. Vitruvius is implemented prototypically using the Eclipse Modeling Framework.Vitruvius Project Homepage