The space domain, as many other engineering sectors, is actively considering novel methods and tools based on artificial intelligence, Digital Twins, virtual design and testing, and other Industry 4.0 concepts, in order to manage the increased complexity of the design of upcoming satellites. Nevertheless, especially from the satellite on-board software engineering point of view, these technologies require a solid ground to be built upon. First of all, the computational power of the hardware platform must meet the needs of the advanced algorithms running on top of it. The software layer too must both allow an efficient use of the hardware resources and at the same time guarantee non-functional properties such as dependability in compliance with ECSS standards. Finally, the design methods need to adapt to the specific challenges posed by both the increased complexity of the hardware/software layers and the Industry 4.0 concepts. The METASAT vision is that a design methodology based on Model-Based engineering jointly with the use of open architecture hardware constitutes that solid ground. To reach its vision, METASAT will leverage existing software virtualisation layers (e.g., hypervisors), that already provide guarantees in terms of standards compliance, on top of high-performance computing platforms based on open hardware architectures. The focus of the project will be on the development of a toolchain to design software modules for this hardware/software layer. Without such measures the time and cost of developing new systems could become prohibitive as system complexity grows, reducing competitiveness, innovation, and potentially dependability across the industry. A high quality and complementary consortium comprising knowledge generators (IKL, BSC and ALES), plus an SME technology integrator (FEN) and an end user from the space sector (OHB), will be able to test in a real scenario the new design toolchain that will enable the runtime deployment of software module

The SEC-AIRSPACE project aims to enable a more resilient ATM, by focusing on reducing the risks of virtualization and increased data-sharing between all components of the ATM infrastructure and the relevant stakeholders. The project will enhance the state-of-the-art security risk assessment methodology(ies) currently adopted in ATM with prominent cyber security components. Further, the project will investigate the potential of applying the concept of People Analytics (PA) to increase cyber security awareness in ATM organizations. The project results will be validated and demonstrated through two realistic use cases, involving relevant stakeholders.

The reliable application of LLM-based agents to SE requires a tremendous increase in their accuracy and minimisation of their bias. While LLMs continue increasing in size and performance, it seems that phenomena like hallucinations of a single agent are substantially inevitable, since they are linked to the fundamental inference mechanism in generative models. On the other hand, evidence starts accumulating about the possibility of achieving the required performance by collaboration and debate among groups of agents. As it happens among humans, quality of work increases with specialisation of workers on tasks, organised collaboration, and discussion among workers with different backgrounds. Differently from humans, the instantiation of multiple required AI agents, and the collaboration and discussion among them, are very fast and cheap, making this approach particularly convenient. MOSAICO proposes the theoretical and technical framework to implement this approach and to scale it to very large groups of collaborating agents, i.e. AI-agent communities. The developed solutions are composed into an integrated MOSAICO platform, handling communication, orchestration, governance, quality assessment, benchmarking and reuse of AI agents. MOSAICO is integrated with existing development environments, to present the results to software engineers, and allow expert users to intervene in the AI decisions. The performance and reliability of MOSAICO technologies and tools to achieve given software engineering tasks are assessed within 4 different use cases scenarios coming from immersive technologies, bank/financing, aerospace and Internet of Things sectors. The long-term adoption of MOSAICO results and technologies will be ensured by open sourcing the code and fostering an open collaboration, such as open-source initiatives, to enhance user engagement in the MOSAICO community.