Model-to-Model Transformation in Meta-Modeled CINCO Domains

In this paper we present an approach to transform models of concrete domains specified with CINCO, a meta-modeling suite, into other CINCO domains. This procedure is demonstrated by transforming Webstory models to DIME applications. The model-to-model transformation increases benefits gained from domain-specific solutions, as shown with the DIME to web application generator, ultimately allowing for Webstories to be deployed and run as web applications

DSL-based Interoperability and Integration in the Smart Manufacturing Digital Thread

In the industry 4.0 ecosystem, a Digital Thread connects the data and processes for smarter manufacturing. It provides an end to end integration of the various digital entities thus fostering interoperability, with the aim to design and deliver complex and heterogeneous interconnected systems. We develop a service oriented domain specific Digital Thread platform in a Smart Manufacturing research and prototyping context. We address the principles, architecture and individual aspects of a growing Digital Thread platform. It conforms to the best practices of coordination languages, integration and interoperability of external services from various platforms, and provides orchestration in a formal methods based, low-code and graphical model driven fashion. We chose the Cinco products DIME and Pyrus as the underlying IT platforms for our Digital Thread solution to serve the needs of the applications addressed: manufacturing analytics and predictive maintenance are in fact core capabilities for the success of smart manufacturing operations. In this regard, we extend the capabilities of these two platforms in the vertical domains of data persistence, IoT connectivity and analytics, to support the basic operations of smart manufacturing. External native DSLs provide the data and capability integrations through families of SIBs. The small examples constitute blueprints for the methodology, addressing the knowledge, terminology and concerns of domain stakeholders. Over time, we expect reuse to increase, reducing the new integration and development effort to a progressively smaller portion of the models and code needed for at least the most standard application

Hybrid Universality Model Development and Air Shower Reconstruction for the Pierre Auger Observatory

Cosmic rays have been studied for more than 100 years, providing valuable information on the measured spectrum and theories to particle propagation and interaction. Potential sources, which could also serve possible acceleration mechanisms, include active galactic nuclei, gamma-ray bursts and supernova shock fronts. Due to our increased understanding of cosmic ray physics and technological improvements on a detector level, measurements have progressed towards even higher energies than before. To understand their origin, it is pertinent to understand their mass composition, energy spectrum and arrival direction. Laboratory-based particle accelerators and low energy cosmic ray experiments have elucidated our understanding of particle interaction, providing insight on possible acceleration and propagation models. However, ultra-high cosmic rays at $10^{20}$ eV are significantly above the highest energies achievable by the LHC (about two orders of magnitude between the center-of-mass energies). They are also very rare; with an incident flux of 1 particle per $km^{2}$ per century at $10^{20}$ eV. Accelerator-based models can be extrapolated to the highest energies. However, it is pertinent for large-scale detectors to be able to measure unique properties of cosmic rays interacting with the detection medium. The Auger is the largest cosmic ray detector to date, covering an area of more than 3000 ${km^{2}}$. It utilizes surface, underground and fluorescence techniques to measure the macroscopic properties of extensive air showers (initiated by a cosmic ray particle interacting with a nucleus in the atmosphere). Through the fluorescence technique the longitudinal profile can be directly observed. From its maximum, $X_{\text{max}}$, the cosmic ray mass can be inferred. However, due to specific operational conditions it has a duty cycle of $\approx15$%, limiting the statistics of more energetic events. The surface and underground detectors can measure data with a duty cycle of $\approx100$%. Most surface detectors are distributed in a triangular grid with a spacing of 1500 m. A small fraction is distributed in an infilled grid with a spacing of 750 m. Furthermore, each surface detector in the filled grid is paired with an underground detector. Their combined information provides another mass composition sensitive parameter -the muon content. Air shower universality capitalizes on the universal shape of the longitudinal profile, irrespective of primary or hadronic model. It encapsulates the underlying shower physics and allows for a reconstruction based on mass-composition sensitive shower parameters (the shower maximum $X_{\text{max}}$, maximum of muon production depth $X^{\mu}_{\text{max}}$ and relative muon content $R_{\mu}$) seen through unique features in the time and signal distributions. The universality approach allows for a highly modular reconstruction algorithm, set as a function of primary energy, mass and geometry. The major focus of this work was the development of the a new signal and time model for secondary particles at ground seen by the WCD and MD, as well as dedicated efforts to effectively process large quantities of simulated air showers. Reconstructed air shower simulations were studied and compared for contemporary high energy hadronic interaction models. In this work, I show how I could successfully model the signal in the detector corresponding to air showers between $10^{17}$ eV and $10^{20}$ eV with uncertainties below the 5% level. The temporal distribution is also successfully modelled, mostly within the 3% level. A novelty, the maximum muon production depth, $X^{\mu}_{\text{max}}$, has been successfully introduced into the MD universality models. With the newly obtained WCD and MD, I could prove that the muon content, $R_{\mu}$, is a global shower variable. Furthermore, first analysis was performed on hybrid reconstructions for the infilled detector setup. Preliminary resolutions of the shower parameters $X_{\text{max}}$ and $X^{\mu}_{\text{max}}$ are of the order 40 ${g cm^{-2}}$ and 50 ${g cm^{-2}}$ respectively, which can be further enhanced. Also, the quality of $R_{\mu}$ has greatly improved, with an uncertainty of only 10%. This work sets an important basis for future analyses (mass composition and shower physics) with data from the WCD and MD. Results obtained in this work could also be used for new detector systems, such as the SSD (part of the AugerPrime upgrade)

Heavy meta: model-driven domain-specific generation of generative domain-specific modeling tools

Software is so prevalent in all areas of life that one could expect we have come up with more simple and intuitive ways for its creation by now. However, software development is still too complicated to easily and efficiently cope with individual demands, customizations, and changes. Model-based approaches promise improvements through a more comprehensible layer of abstraction, but they are rarely fully embraced in practice. They are perceived as being overly complex, imposing additional work, and lacking the flexibility required in the real world. This thesis presents a novel approach to model-driven software engineering that focuses on simplicity through highly specialized tools. Domain experts are provided with development tools tailored to their individual needs, where they can easily specify the intent of the software using their known terms and concepts. This domain specificity (D) is a powerful mechanism to boil down the effort of defining a system to relevant aspects only. Many concepts are set upfront, which imposes a huge potential for automated generation. However, the full potential of domain-specific models can only unfold, if they are used as primary artifacts of development. The presented approach thus combines domain specificity with full generation (F) to achieve an overall pushbutton generation that does not require any round-trip engineering. Furthermore, service orientation (S) introduces a ‘just use’ philosophy of including arbitrarily complex functionality without needing to know their implementation, which also restores flexibility potentially sacrificed by the domain focus. The unique combination of these three DFS properties facilitates a focused, efficient, and flexible simplicity-driven way of software development. Key to the approach is a holistic solution that in particular also covers the simplicity-driven development of the required highly specialized DFS tools, as nothing would be gained if the costs of developing such tools outweighed the resulting benefits. This simplicity is achieved by applying the very same DFS concepts to the domain of tool development itself: DFS modeling tools are fully generated from models and services specialized to the (meta) domain of modeling tools. The presented Cinco meta tooling suite is a first implementation of such a meta DFS tool. It focuses on the generation of graphical modeling tools for graph structures comprising of various types of nodes and edges. Cinco has been very successfully applied to numerous industrial and academic projects, and thus also serves as a proof of concept for the DFS approach itself. The unique combination of the three DFS strategies and Cinco's meta-level approach towards their realization in practice lay the foundation for a new paradigm of software development that is strongly focused on simplicity