Multi-Platform Generative Development of Component & Connector Systems using Model and Code Libraries

Component-based software engineering aims to reduce software development effort by reusing established components as building blocks of complex systems. Defining components in general-purpose programming languages restricts their reuse to platforms supporting these languages and complicates component composition with implementation details. The vision of model-driven engineering is to reduce the gap between developer intention and implementation details by lifting abstract models to primary development artifacts and systematically transforming these into executable systems. For sufficiently complex systems the transformation from abstract models to platform-specific implementations requires augmentation with platform-specific components. We propose a model-driven mechanism to transform platform-independent logical component & connector architectures into platform-specific implementations combining model and code libraries. This mechanism allows to postpone commitment to a specific platform and thus increases reuse of software architectures and components.Comment: 10 pages, 4 figures, 1 listin

Monitoring of Tool and Component Wear for Self-Adaptive Digital Twins: A Multi-Stage Approach through Anomaly Detection and Wear Cycle Analysis

In today’s manufacturing landscape, Digital Twins play a pivotal role in optimising processes and deriving actionable insights that extend beyond on-site calculations. These dynamic representations of systems demand real-time data on the actual state of machinery, rather than static images depicting idealized configurations. This paper presents a novel approach for monitoring tool and component wear in CNC milling machines by segmenting and classifying individual machining cycles. The method assumes recurring sequences, even with a batch size of 1, and considers a progressive increase in tool wear between cycles. The algorithms effectively segment and classify cycles based on path length, spindle speed and cycle duration. The tool condition index for each cycle is determined by considering all axis signals, with upper and lower thresholds established for quantifying tool conditions. The same approach is adapted to predict component wear progression in machine tools, ensuring robust condition determination. A percentage-based component state description is achieved by comparing it to the corresponding Tool Condition Codes (TCC) range. This method provides a four-class estimation of the component state. The approach has demonstrated robustness in various validation cases

Engineering a ROVER language in GEMOC STUDIO & MONTICORE: A comparison of language reuse support

Domain-specific languages (DSLs) improve engineering productivity through powerful abstractions and automation. To support the development of DSLs, the software language engineering (SLE) community has produced various solutions for the systematic engineering of DSLs that manifest in language workbenches. In this paper, we investigate the applicability of the language workbenches GEMOC STUDIO and MONTICORE to the MDETools’17 ROVER challenge. To this effect, we refine the challenge’s requirements and show how GEMOC STUDIO and MONTICORE can be leveraged to engineer a Rover-specific DSL by reusing existing DSLs and tooling of GEMOC STUDIO and MONTICORE. Through this, we reflect on the SLE state of the art, detail capabilities of the two workbenches focusing particularly on language reuse support, and sketch how modelers can approach ROVER programming with modern modeling tools

Code Generator Composition for Model-Driven Engineering of Robotics Component & Connector Systems

Engineering software for robotics applications requires multidomain and application-specific solutions. Model-driven engineering and modeling language integration provide means for developing specialized, yet reusable models of robotics software architectures. Code generators transform these platform independent models into executable code specific to robotic platforms. Generative software engineering for multidomain applications requires not only the integration of modeling languages but also the integration of validation mechanisms and code generators. In this paper we sketch a conceptual model for code generator composition and show an instantiation of this model in the MontiArc- Automaton framework. MontiArcAutomaton allows modeling software architectures as component and connector models with different component behavior modeling languages. Effective means for code generator integration are a necessity for the post hoc integration of applicationspecific languages in model-based robotics software engineering.Comment: 12 pages, 4 figures, In: Proceedings of the 1st International Workshop on Model-Driven Robot Software Engineering (MORSE 2014), York, Great Britain, Volume 1319 of CEUR Workshop Proceedings, 201

Supporting fine-grained generative model-driven evolution

In the standard generative Model-driven Architecture (MDA), adapting the models of an existing system requires re-generation and restarting of that system. This is due to a strong separation between the modeling environment and the runtime environment. Certain current approaches remove this separation, allowing a system to be changed smoothly when the model changes. These approaches are, however, based on interpretation of modeling information rather than on generation, as in MDA. This paper describes an architecture that supports fine-grained evolution combined with generative model-driven development. Fine-grained changes are applied in a generative model-driven way to a system that has itself been developed in this way. To achieve this, model changes must be propagated correctly toward impacted elements. The impact of a model change flows along three dimensions: implementation, data (instances), and modeled dependencies. These three dimensions are explicitly represented in an integrated modeling-runtime environment to enable traceability. This implies a fundamental rethinking of MDA

Blockchain for the IoT: Privacy-Preserving Protection of Sensor Data

An ever growing variety of smart, connected Internet of Things (IoT) devices poses completely new challenges for businesses regarding security and privacy. In fact, the adoption of smart products may depend on the ability of organizations to offer systems that ensure adequate sensor data integrity while guaranteeing sufficient user privacy. In light of these challenges, previous research indicates that blockchain technology could be a promising means to mitigate issues of data security arising in the IoT. Building upon the existing body of knowledge, we propose a design theory, including requirements, design principles, and features, for a blockchain-based sensor data protection system (SDPS) that leverages data certification. To support this, we designed and developed an instantiation of an SDPS (CertifiCar) in three iterative cycles intented to prevent the fraudulent manipulation of car mileage data. Following the explication of our SDPS, we provide an ex post evaluation of our design theory considering CertifiCar and two additional use cases in the areas of pharmaceutical supply chains and energy microgrids. Our results suggest that the proposed design ensures the tamper-resistant gathering, processing, and exchange of IoT sensor data in a privacy-preserving, scalable, and efficient manner

Industry Best Practices in Robotics Software Engineering

Robotics software is pushing the limits of software engineering practice. The 3rd International Workshop on Robotics Software Engineering held a panel on "the best practices for robotic software engineering". This article shares the key takeaways that emerged from the discussion among the panelists and the workshop, ranging from architecting practices at the NASA/Caltech Jet Propulsion Laboratory, model-driven development at Bosch, development and testing of autonomous driving systems at Waymo, and testing of robotics software at XITASO. Researchers and practitioners can build on the contents of this paper to gain a fresh perspective on their activities and focus on the most pressing practices and challenges in developing robotics software today.Comment: 10 pages, 0 figure