Software Ecosystem (SECO) has emerged as a crucial concept, which represents a collaborative and interconnected environment in which a variety of actors engage in developing software systems. SECOs play a key role in the development of Cyber-Physical Systems (CPSs), that present a myriad of challenges, primarily due to the need for real-time responsiveness, reliability, security, and interoperability. The implications of leveraging SECOs for developing CPSs are profound in both research and practice. This paper aims to understand the collaboration between industry and academia within SECOs for the development of CPSs, identifying potential challenges and providing insights and guidelines for the proper management of these collaborations. We conducted a systematic literature review (SLR), complemented by empirical evidence collected through an opinion survey administered to the partners of the European collaborative project AIDOaRt, a concrete example of a SECO, which worked on the development of CPSs. From these findings we discuss the identified challenges, and potential effects on collaboration, in addition to our lessons learned in the AIDOaRt project and SECO.

In this article, we discuss how we can facilitate the growing need for early validation and verification (V&V) of system behaviour in Model-Based Systems Engineering (MBSyE). Several aspects, such as reducing cost and time to market, push companies towards integration of V&V methods earlier in development to support effective decision-making. One foundational methodology seeing increased attention in industry is the use of MBSyE, which brings benefits of models with well-defined syntax and semantics to support V&V activities, rather than relying on natural language text documentation. Despite their promise, industrial adoption of these practices is still challenging. This article presents a vision for readily available early V&V . We present a summary of the literature on early V&V in MBSyE and position existing challenges regarding potential solutions and future investigations towards this vision. We elaborate our vision by means of challenges with a specific emphasis on early V&V of system behaviour . We identify three specific challenge areas: Creating and managing Models , Organisational systems engineering aspects, and early V&V Methods . Finally, we outline a road-map to address these categories of challenges, in which we propose the transfer of established best practices from the software engineering domain to support emerging technologies in the systems engineering domain.

Summary Cyber‐physical systems (CPSs) are increasing in developmental complexity. Several emerging technologies, such as Model‐based engineering, DevOps, and Artificial intelligence, are expected to alleviate the associated complexity by introducing more advanced capabilities. The AIDOaRt research project investigates how the aforementioned technologies can assist in developing complex CPSs in various industrial use cases. In this paper, we discuss the experiences of industry and academia collaborating to improve the development of complex CPSs through the experiences in the research project. In particular, the paper presents the results of two working groups that examined the challenges of developing complex CPSs from an industrial and academic perspective when considering the previously mentioned technologies. We present five identified challenge areas from developing complex CPSs and discuss them from the perspective of industry and academia: data, modeling, requirements engineering, continuous software and system engineering, as well as intelligence and automation. Furthermore, we highlight practical experience in collaboration from the project via two explicit use cases and connect them to the challenge areas. Finally, we discuss some lessons learned through the collaborations, which might foster future collaborative efforts.

In the Systems Engineering (SE) domain there has been a paradigm shift from document-based to model-based system development artefacts; in fact, new methodologies are emerging to meet the increasing complexity of current systems and the corresponding growing need of digital workflows. In this regard, Model-Based Systems Engineering (MBSE) is considered as a key enabler by many central players of the SE community. MBSE has reached an adequate level of maturity, and there exist documented success stories in its adoption in industry. In particular, one significant benefit of utilising MBSE when compared to the traditional manual and document-centric workflows is that models are available from early phases of systems development; these enable a multitude of analyses prior any implementation effort together with other relevant capabilities, like the automation of development tasks. Nonetheless, it is noticeable there is a lack of a common understanding for how formal analyses for the verification and validation (V&V) of systems behaviour, specifically in the early phases of development, could be placed in an MBSE setting. In this article, we report on the planning, execution, and results of a systematic literature review regarding the early V&V of systems behaviour in the context of model-based systems engineering. The review aims to provide a structured representation of the state of the art with respect to motivations, proposed solutions, and limitations. From an initial set of potentially relevant 701 peer-reviewed publications we selected 149 primary studies, which we analysed according to a rigorous data extraction, analysis, and synthesis process. Based on our results, early V&V has usually the goal of checking the quality of a system design to avoid discovering flaws when parts are being concretely realised; SysML is a de facto standard for describing the system under study, while the solutions for the analyses tend to be varied; also V&V analyses tend to target varied properties with a slight predominance of functional concerns, and following the variation mentioned so far the proposed solutions are largely context specific; the proposed approaches are usually presented without explicit limitations, while when limitations are discussed, readiness of the solutions, handling of analyses simplifications/assumptions, and languages/tools integration are among the most frequently mentioned issues. Based on the survey results and the standard SE practices, we discuss how the current state-of-the-art MBSE supports early V&V of systems behaviour with a special focus on industrial adoption and identify relevant challenges to be researched further.

Model-Based Systems Engineering (MBSE) has emerged as a de facto standard practice for complex systems development. However, despite standard frameworks, methods, and tools, the MBSE practices in industrial contexts are far from mature. This is particularly true for traditionally hardware-intensive industrial systems and complex products such as heavy construction machinery. This paper outlines a lightweight MBSE methodology developed within the construction equipment domain. The approach is based on customizing a general MBSE methodology, such as RFLP, guided by a core ontology for architecture modeling. The ontology defines the main architecture concepts and corresponding modeling views to develop an architecture baseline for the corresponding system model. The initial architecture baseline is developed bottom-up instead of a traditional top-down approach. As we demonstrate in this paper, the minimalist approach paves the way for faster deployment of MBSE in industrial contexts with low modeling experience and legacy development silos across electronics, software, and hardware domains.