European industry faces stiff competition on the global arena. Electronic Components and Systems become more and more complex, thus calling for modern engineering practices to be applied in order to better tackle both productivity and quality. Model-based technologies promise significant productivity gains, which have already been proven in several studies and applications. However, these technologies still need more enhancements to scale up for real-life industrial projects and to provide more benefits in different contexts. The ultimate objective of improving productivity, while reducing costs and ensuring quality in development, integration and maintenance, can be achieved by using techniques integrating seamlessly design time and runtime aspects. Industrial scale system models, which are usually multi-disciplinary, multi-teams and serving to several product lines have to be be exploited at runtime, e.g. by advanced tracing and monitoring, thus boosting the overall quality of the final system and providing lessons-learnt for future product generations. MegaM@Rt brings model-based engineering to the next level in order to help European industry reducing development and maintenance costs while reinforcing both productivity and quality. To achieve that, MegaM@Rt will create a framework incorporating methods and tools for continuous development and runtime validation to significantly improve productivity, quality and predictability of large and complex industrial systems. MegaM@Rt addresses the scalability challenges with advanced megamodelling and traceability approaches, while runtime aspects will be tackled via so-called “models@runtime”, online testing and execution traces analysis. MegaM@Rt brings together a strong international consortium involving experts from France, Spain, Italy and Finland. The partners cover the whole value chain from research organizations to tool providers, including 9 end-users with large industrial case studies for results validation.

There is an ever increasing complexity of the systems we engineer in modern society, which includes facing the convergence of the embedded world and the open world. This complexity creates increasing difficulty with providing assurance for factors including safety, security and performance - particularly for safety critical systems such as the transportation, aerospace and the industrial control domains. In this project we will focus on the following: • Safety/Security/Performance to be considered together, during the overall life cycle of our products. • Flexibility across domains. • Consolidate the industrial market by reducing costs and increasing system quality and maintaining compliance with more and more exacting standards. • Improved tool features and capabilities

Embedded systems have significantly increased in technical complexity towards open, interconnected systems. This has exacerbated the problem of ensuring dependability in the presence of human, environmental and technological risks. The rise of complex Cyber-Physical Systems (CPS) has led to many initiatives to promote reuse and automation of labor-intensive activities. Two large-scale projects are OPENCOSS and SafeCer, which dealt with assurance and certification of software-intensive critical systems using incremental and model-based approaches. OPENCOSS defined a Common Certification Language (CCL), unifying concepts from different industries to build a harmonized approach to reduce time and cost overheads, via facilitating the reuse of certification assets. SafeCer developed safety-oriented process lines, a component model, contract-based verification techniques, and process/product-based model-driven safety certification for compositional development and certification of CPSs. AMASS will create and consolidate a de-facto European-wide assurance and certification open tool platform, ecosystem and self-sustainable community spanning the largest CPS vertical markets. We will start by combining and evolving the OPENCOSS and SafeCer technological solutions towards end-user validated tools, and will enhance and perform further research into new areas not covered by those projects. The ultimate aim is to lower certification costs in face of rapidly changing product features and market needs. This will be achieved by establishing a novel holistic and reuse-oriented approach for architecture-driven assurance (fully compatible with standards e.g. AUTOSAR and IMA), multi-concern assurance (compliance demonstration, impact analyses, and compositional assurance of security and safety aspects), and for seamless interoperability between assurance/certification and engineering activities along with third-party activities (external assessments, supplier assurance).

The aim of the INTO-CPS project is to create an integrated tool chain for comprehensive model-based design of Cyber-Physical Systems (CPSs). The tool chain will support the multidisciplinary, collaborative modelling of CPSs from requirements, through design, down to realisation in hardware and software. This will enable traceability at all stages of the development. INTO-CPS will support the holistic modelling of CPSs, allowing system models to be built and analysed that would otherwise not be possible using standalone tools. We will integrate existing industry-strength tools with high Technology Readiness Levels (TRL 6–9) in their application domains. The solution will be based centrally around Functional Mockup Interface (FMI)-compatible co-simulation. The project focuses on the pragmatic integration of these tools, making extensions in areas where a need has been recognised. The tool chain will be underpinned by a well-founded semantic foundations that ensures the results of analysis can be trusted. The tool chain will provide powerful analysis techniques for CPSs, including connection to SysML; generation and static checking of FMI interfaces; model checking; Hardware-in-the-Loop (HiL) and Software-in-the-Loop (SiL) simulation, supported by code generation. The tool chain will allow for both Test Automation (TA) and Design Space Exploration (DSE) of CPSs. The INTO-CPS technologies will be accompanied by a comprehensive set of method guidelines that describe how to adopt the INTO-CPS approach, lowering entry barriers for CPS development. The tool chain will be tested with case studies in railways, agriculture, building and automotive. The consortium has 4 academic and 7 industrial partners. The industrial partners comprise both tool vendors and case study owners. The INTO-CPS technology will enable experimenting with design alternatives enabling radical innovation where the overall concept is right first time, even when hardware prototypes does not yet exists.

The project idea is focusing on AI-augmented automation supporting modeling, coding, testing, and monitoring as part of a continuous development in Cyber-Physical Systems (CPSs). The growing complexity of CPS poses several challenges throughout all software development and analysis phases, but also during their usage and maintenance. Many leading companies have started envisaging the automation of tomorrow to be brought about by Artificial Intelligence (AI) tech. While the number of companies that invest significant resources in software development is constantly increasing, the use of AI in the development and design techniques is still immature. The project targets the development of a model-based framework to support teams during the automated continuous development of CPSs by means of integrated AI-augmented solutions. The overall AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, along with software models and measurements. The infrastructure is intended to operate within the DevOps process combining software development and information technology (IT) operations. Moreover, AI technological innovations have to ensure that systems are designed responsibly and contribute to our trust in their behaviour (i.e., requiring both accountability and explainability). AIDOaRT aims to impact organizations where continuous deployment and operations management are standard operating procedures. DevOps teams may use the AIDOaRT framework to analyze event streams in real-time and historical data, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection.