Feature models are the de facto standard for modelling variabilities and commonalities. Concrete models in different domains exist;however, many are in private or sparse repositories or belong to discontinued projects...
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CONTEXT: Versioning allows users to efficiently create and evolve artifacts, not only but especially in the domain of model-driven engineering. Due to collaboration tools, the place and time where users jointly work a...
CONTEXT: Versioning allows users to efficiently create and evolve artifacts, not only but especially in the domain of model-driven engineering. Due to collaboration tools, the place and time where users jointly work at their artifacts do not play an important role anymore. Objective: We systematically elaborated a classification framework for collaboration and versioning tools. The intention is threefold: First, it should be possible to classify existing approaches. Second, deriving from user goals requirements to be met, and capabilities to be supported by a new tool. Third, given a set of capabilities, highlight which user goals can be achieved. Method: According to Kang and Lee, we systematically elaborated a problem space and a solution space and created mappings between both spaces and their sub-spaces. To demonstrate the applicability, we classified existing VCS like git, Google Docs, and several MDE-specific approaches. Results: The created feature diagram covers 238 features and contains about 87 constraints. Conclusion: The developed framework supports researchers and developers in classifying their tools, revealing new opportunities to improve their tools, and guiding the development of new tools.
Joint safety and security analysis of cyber-physical systems is a necessary step to correctly capture inter-dependencies between these properties. Attack-Fault Trees represent a combination of dynamic Fault Trees and ...
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Selection of insulation material and determination of its thickness are the two most important parameters that prevent heat loss. Too much thickness complicates the price and use. The low coefficient of thermal conduc...
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A method for determining the probability of occurrence of a critical combination of events for the three-element minimum cross-sections of attributes of the characteristics of the software quality model of intelligent...
A method for determining the probability of occurrence of a critical combination of events for the three-element minimum cross-sections of attributes of the characteristics of the software quality model of intelligent decision support systems is proposed.
Autonomous Systems (AS) enable systems to adapt to drastic and unprecedented environmental changes, a capability that can be enhanced through the utilization of Digital Twins (DTs). However, the additional capabilitie...
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ISBN:
(数字)9798350389760
ISBN:
(纸本)9798350389777
Autonomous Systems (AS) enable systems to adapt to drastic and unprecedented environmental changes, a capability that can be enhanced through the utilization of Digital Twins (DTs). However, the additional capabilities of AS come at the cost of explainability, as the expanding adaptation space complicates the reasoning about the system's behavior. For certain types of systems, it is crucial to ensure that specific properties are upheld despite the system's autonomous behavior. To facilitate the monitoring of these properties, we propose the use of Runtime Verification (RV). This tutorial demonstrates the integration of RV tools into the Digital Twins as a Service (DTaaS) platform to monitor and verify the behavior of AS in real-time. By exploring various methods to incorporate RV tools within a DT context, the tutorial aims to advance the application of RV technologies in autonomic computing and self-adaptive system design. Specifically, we demonstrate how the behavior of a self-configuring DT can be verified utilizing RV. This is accomplished through the DTaaS platform, which supports seamless deployment of DT-based AS.
The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition ...
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Context: Cyber-physical systems (CPS) are increasingly self-adaptive, i.e. they have the ability to introspect and change their behavior. This self-adaptation process must be considered when modeling the safety and se...
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There are many research papers devoted to the state identification problem of finite state machines (FSMs) which are widely used for analysis of discrete event systems. A deterministic complete reduced FSM always has ...
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作者：
Mucahit SoyluResul DasInonu University
Department of Organized Industrial Zone Vocational School Computer Programming Malatya Turkiye Firat University
Faculty of Technology Department of Software Engineering 23119 Elazig Turkiye
This study proposes a hybrid approach for visualizing cyberattacks by combining the deep learning-based GAT model with JavaScript-based graph visualization tools. The model processes large, heterogeneous data from the...
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This study proposes a hybrid approach for visualizing cyberattacks by combining the deep learning-based GAT model with JavaScript-based graph visualization tools. The model processes large, heterogeneous data from the UNSW-NB15 dataset to generate dynamic and meaningful graphs. In the data cleaning phase, missing and erroneous data were removed, unnecessary columns were discarded, and the data was transformed into a format suitable for modeling. Then, the data was converted into homogeneous graphs, and heterogeneous structures were created for analysis using the GAT model. GAT prioritizes relationships between nodes in the graph with an attention mechanism, effectively detecting attack patterns. The analyzed data was then converted into interactive graphs using tools like SigmaJS, with attacks between the same nodes grouped to reduce graph complexity. Users can explore these dynamic graphs in detail, examine attack types, and track events over time. This approach significantly benefits cybersecurity professionals, allowing them to better understand, track, and develop defense strategies against cyberattacks.
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