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Collaborative technologies are continuously evolving to address existing problems and introduce innovative features for enhancing collaboration in the landscape of model-driven software engineering (MDSE). Different collaborative MDSE technologies (CMTs) provide different solutions to facilitate collaboration, making it hard for practitioners to choose the technology that best suits their needs. This study aims to investigate the landscape of CMTs and to provide a list of recommended technologies tailored to specific use case scenarios in the context of MDSE. We compiled a comprehensive list of CMTs using a systematic search complemented with snowballing, investigating both academic and grey literature. The technologies were selected through a set of inclusion and exclusion criteria and eventually analyzed through an in-depth analysis focusing on model management, collaboration, and communication. The findings of our study reveal that the current landscape of CMTs is characterized by a relatively narrow range of capabilities offered by different technologies. Consequently, practitioners often have to become proficient in combining several different technologies in order to meet their needs. While various CMTs offer distinct collaboration approaches, the current landscape could be richer in terms of capabilities. Our research provides a comprehensive description of recommended CMTs, enabling practitioners to make informed decisions and improve collaboration in their MDSE processes.

Model-Driven Engineering (MDE) has been widely adopted across various industrial sectors due to its ability to manage the complexity of modern engineering products. However, traditional modeling languages and tools are often limited to a single, specific concrete syntax, which poses challenges for the diverse stakeholders involved in the modeling process.. To address these limitations, the emerging field of blended modeling introduces the use of multiple concrete syntaxes, and in some cases, even multiple abstract syntaxes, for representing the same information. In this expert perspective, we present generalized, technology-agnostic concepts developed within a European research and development project focused on blended modeling. Specifically, we contribute a standardized terminology and ontology for blended modeling, along with a methodology for creating blended modeling environments. These concepts were developed through collaboration between academic and industrial partners, who aligned on the motivations and benefits of this approach. The insights gained from this project are not only relevant to blended MDE but also can be applied to traditional MDE practices.

ROS2 is an increasingly popular middleware framework for developing robotic applications. A ROS2 application is composed of nodes that run concurrently, coordinate with each other through asynchronous interfaces, and can be deployed in a distributed manner. Rebeca is an actor-based language for modelling asynchronous and concurrent systems. Timed Rebeca adds timing features to deal with timing requirements of real-time systems. The similarities in concurrency and message-based asynchronous interactions of reactive nodes, and the ability of modelling timed behaviours justify using Timed Rebeca models to assist the development and verification of ROS2 applications. Model-based development and model-checking techniques allow faster prototyping and earlier detection of system errors before developing the entire real system. However, there are challenges in bridging the gap between continuous behaviours of robotic systems and discrete states in a model for automatic verification, and between complex robotic computations and inequivalent programming facilities in a modelling language like Timed Rebeca. We investigated the problem systematically and have succeeded in modelling a realistic multiple autonomous mobile robots (AMR) system using Timed Rebeca, creating corresponding ROS2 demo code, and showing the match between the model and the program. Based on experiments, we demonstrated the value of the model in development and automatic formal verification of correctness properties (target reachability, collision freedom, and deadlock freedom). Our model-checking results show that certain system problems are not always detected through simulation. The modelling principles, modelling and implementation techniques that are created and used in this work can be generalized for many other cases. 

Canonical software and systems modelling regards only models that conform to modelling languages and that are created in modelling tools. In practice, these models are often supplemented with free-form activities such as sketching and informal diagramming. Flexible modelling has been proposed to benefit from the combination of free-form activities, from relaxed to no conformance to modelling languages, and canonical modelling with more or less strict conformance of diagrammatic elements to modelling languages. Various tools and approaches have proposed mechanisms to support flexible modelling. In this paper, we report on a systematic literature review of these tools and approaches. We present an analysis of the existing body of knowledge in this area and discuss open research challenges that can help the modelling community identify promising next steps in this area.

In software engineering practice, models created for communication and documentation are often informal. This limits the applicability of powerful model-driven engineering mechanisms. Understanding the motivations and use of informal diagrams can improve modelling techniques and tools, by bringing together the benefits of both informal diagramming and modelling using modelling languages and modelling tools. In this paper, we report on an initial exploration effort to investigate the use of informal diagramming in both open-source software repositories and industrial software engineering practices. We carried out a repository mining study on open-source software repositories seeking informal diagrams and classified them according to what they represent and how they are used. Additionally, we describe industrial practices that rely to some extent on informal diagramming, as gathered through unstructured interviews with practitioners. We compare the findings from these data sources and discuss how informal diagrams are used in practice.

Collaborative model-driven software engineering fosters efficient cooperation among stakeholders who collaborate on shared models. Yet, the involvement of multiple parties brings forth valid concerns about the confidentiality and integrity of shared information. Unrestricted access to such information, especially when not pertinent to individual responsibilities, poses significant risks, including unauthorized information exposure and potential harm to information integrity. This work proposes a dual-layered solution implemented as an open-source Eclipse plugin that leverages the role-based access control policy to ensure the confidentiality and integrity of model information in collaborative modeling environments. The first layer limits stakeholders' access to the shared model based on their specific roles, while the second layer refines this access by restricting manipulations to individual model elements. By ensuring that stakeholders access only the information pertinent to their roles and are authorized to manipulate such information in accordance with their expertise and responsibilities, this approach ensures the confidentiality and integrity of shared model information. Furthermore, it alleviates information overload for stakeholders by enabling them to focus only on the model information relevant to their specific roles, thereby enhancing the collaborative efforts. 

Scientists without specific software programming skills are increasingly required to express their problems in terms of software to exploit the computational power of heterogeneous parallel hardware. Producing software for this hardware is very cumbersome for the experienced programmer; for the novice, it is just impracticable. We aim to grant scientists across disciplines access to heterogeneous hardware via a model-driven holistic approach. Via proper software modelling, we suppress the need to write resource-specific software functions and complex offloading and communication code; we will do this by devising a comprehensive modelling language that implicitly underpins multiple execution semantics (sequential, data-/task-parallel). Current code generators neglect model semantics while compilers expect in input too detailed software descriptions; we will devise an innovative semantics-aware model compiler with automatic parallelization. Overall, we aim at giving researchers and practitioners better tools to focus more on the problem to solve than learning how to master complex techniques and languages to describe it in terms of software. Moreover, the learning curve and technological hindrances for beginners approaching hybrid software will be pushed down dramatically.

Software-intensive systems in most domains, from autonomous vehicles to health, are becoming predominantly parallel to efficiently manage large amount of data in short (even real-) time. There is an incredibly rich literature on languages for parallel computing, thus it is difficult for researchers and practitioners, even experienced in this very field, to get a grasp on them. With this work we provide a comprehensive, structured, and detailed snapshot of documented research on those languages to identify trends, technical characteristics, open challenges, and research directions. In this article, we report on planning, execution, and results of our systematic peer-reviewed as well as grey literature review, which aimed at providing such a snapshot by analysing 225 studies.

Blended modelling is an emerging trend in Model-Driven Engineering for complex software architectures. It enables the modelling of diverse architectural aspects through multiple editing notations seamlessly, interchangeably, and collaboratively. Blended modelling is expected to significantly improve productivity and user experience for multiple stakeholders. To manually architect and build a blended modelling environment is not trivial. To support architects in this task, in the scope of the ITEA3 BUMBLE project, we have designed and developed a blended modelling framework that aids architects in designing and semi-automatically generating blended modelling environments for architecting software.