Special section on uncertainty, modeling, CPSs and AI: honoring Prof. Antonio Vallecillo

This special section pays tribute to the distinguished career of Prof. Antonio Vallecillo, highlighting his significant contributions to software engineering, particularly in the areas of uncertainty, modeling, cyber-physical systems (CPSs), and artificial intelligence (AI). The article begins with a detailed summary of Vallecillo's professional journey, which spans both industry and academia, and his pioneering work in model-based software engineering. The core of the article is a collection of 17 peer-reviewed papers, each addressing a unique aspect of the overarching themes. These papers delve into the complexities of informal diagramming in software engineering, the historical evolution of Model-Driven Engineering (MDE) in tackling uncertainty, and the interaction of design variability and stochastic operational uncertainties in software-intensive systems. Additionally, the article explores innovative approaches to modeling and simulating the environment of medical devices' digital twins, defining test oracles for CPSs, and managing model obsolescence. The papers also cover the use of Domain-Specific Languages (DSLs) for maintaining consistency in long-lived enterprise language specifications, conceptual modeling of temporality and subjectivity, and the integration of smart contracts into the modeling paradigm. Furthermore, the article discusses the application of reinforcement learning in model-driven optimization, the use of large language models in model-driven engineering, and the potential of explainable AI in supporting software modelers. Each paper provides a deep dive into its respective topic, offering novel insights and practical applications that push the boundaries of current research. The article concludes with an acknowledgment of the reviewers who contributed to the refinement of the papers, underscoring the collaborative and rigorous nature of the research presented.