SESep 13, 2020Code
Model-based analysis support for dependable complex systems in CHESSFelicien Ihirwe, Silvia Mazzini, Pierluigi Pierini et al.
The challenges related to dependable complex systems are heterogeneous and involve different aspects of the system. On one hand, the decision-making processes need to take into account many options. On the other hand, the design of the system's logical architecture must consider various dependability concerns such as safety, reliability, and security. Moreover, in case of high-assurance systems, the analysis of such concerns must be performed with rigorous methods. In this paper, we present the new development of CHESS, a cross-domain, model-driven, component-based, and open-source tool for the development of high-integrity systems. We focus on the new recently distributed version of CHESS, which supports extended model-based development and analyses for safety and security concerns. Finally, we present contributions of CHESS to several international research projects.
SESep 19, 2021
A domain-specific modeling and analysis environment for complex IoT applicationsFelicien Ihirwe, Davide Di Ruscio, Silvia Mazzini et al.
To cope with the complexities found in the Internet of Things domain, designers and developers of IoT applications demand practical tools. Several model-driven engineering methodologies and tools have been developed to address such difficulties, but few of them address the analysis aspects. In this extended abstract, we introduce CHESSIoT, a domain-specific modeling environment for complex IoT applications. In addition, the existing supported real-time analysis mechanism, as well as a proposed code generation approach, are presented
SEMay 28, 2021
Towards a modeling and analysis environment for industrial IoT systemsFelicien Ihirwe, Davide Di Ruscio, Silvia Mazzini et al.
The development of Industrial Internet of Things systems (IIoT) requires tools robust enough to cope with the complexity and heterogeneity of such systems, which are supposed to work in safety-critical conditions. The availability of methodologies to support early analysis, verification, and validation is still an open issue in the research community. The early real-time schedulability analysis can help quantify to what extent the desired system's timing performance can eventually be achieved. In this paper, we present CHESSIoT, a model-driven environment to support the design and analysis of industrial IoT systems. CHESSIoT follows a multi-view, component-based modelling approach with a comprehensive way to perform event-based modelling on system components for code generation purposes employing an intermediate ThingML model. To showcase the capability of the extension, we have designed and analysed an Industrial real-time safety use case.
PLMay 24, 2021
CHESSIoT support of event-based modeling for the Internet of Things applicationsFelicien Ihirwe
Internet of Things systems design and development suffers from heterogeneity in different aspects. The component behaviors also change due to events being internal or external and the system needs to take action subsequently. In this paper, we demo the event-based modeling capabilities of the CHESSIoT tool on a smart parking application. Different components was been decomposed with functional and behavioral specifications following the component-based approach. In the end, we have given a brief description of the future work.
SESep 3, 2020
Low-code Engineering for Internet of things: A state of researchFelicien Ihirwe, Davide Di Ruscio, Silvia Mazzini et al.
Developing Internet of Things (IoT) systems has to cope with several challenges mainly because of the heterogeneity of the involved sub-systems and components. With the aim of conceiving languages and tools supporting the development of IoT systems, this paper presents the results of the study, which has been conducted to understand the current state of the art of existing platforms, and in particular low-code ones, for developing IoT systems. By analyzing sixteen platforms, a corresponding set of features has been identified to represent the functionalities and the services that each analyzed platform can support. We also identify the limitations of already existing approaches and discuss possible ways to improve and address them in the future.