Model-driven Interoperability Research Articles

Applying static code analysis for domain-specific languages

The use of code quality control platforms for analysing source code is increasingly gaining attention in the developer community. These platforms are prepared to parse and check source code written in a variety of general-purpose programming languages. The emergence of domain-specific languages enables professionals from different areas to develop and describe problem solutions in their disciplines. Thus, source code quality analysis methods and tools can also be applied to software artefacts developed with a domain-specific language. To evaluate the quality of domain-specific language code, every software component required by the quality platform to parse and query the source code must be developed. This becomes a time-consuming and error-prone task, for which this paper describes a model-driven interoperability strategy that bridges the gap between the grammar formats of source code quality parsers and domain-specific text languages. This approach has been tested on the most widespread platforms for designing text-based languages and source code analysis. This interoperability approach has been evaluated on a number of specific contexts in different domain areas.

Cross-disciplinary engineering with AutomationML and SysML

Abstract AutomationML (AML) is an emerging standard in the automation domain to represent and exchange artifacts between heterogeneous engineering tools used in different disciplines, such as mechanical and electrical engineering. The Systems Modeling Language (SysML) is a modeling standard influenced by software modeling languages, such as UML, typically adopted in the early phases of engineering processes. This paper investigates commonalities and differences of the structural modeling parts of AML (CAEX) and SysML (block diagrams) in support of establishing tool-independent interoperability. This support for cross-disciplinary modeling is facilitated by a bridge between AML and SysML built on model-driven interoperability techniques. We demonstrate the interoperability between AML and SysML with a case study concerning a lab-sized production system.

Model-driven interoperability: engineering heterogeneous IoT systems

Interoperability remains a significant burden to the developers of Internet of Things systems. This is because resources and APIs are dynamically composed; they are highly heterogeneous in terms of their underlying communication technologies, protocols and data formats, and interoperability tools remain limited to enforcing standards-based approaches. In this paper, we propose model-based engineering methods to reduce the development effort towards ensuring that complex software systems interoperate with one another. Lightweight interoperability models can be specified in order to monitor and test the execution of running software so that interoperability problems can be quickly identified, and solutions put in place. A graphical model editor and testing tool are also presented to highlight how a visual model improves upon textual specifications. We show using case-studies from the FIWARE Future Internet Service domain that the software framework can support non-expert developers to address interoperability challenges.

Sustaining interoperability of networked liquid-sensing enterprises: A complex systems perspective

The emerging Liquid-Sensing Enterprise (LSE) concept provides manufacturing industrial networks with the required enablers to seamless interoperate and sustain its interoperability along the operational life cycle. Actually, the actual domain of enterprise information systems interoperability prospects the need for a new paradigm able to manage the network dynamics, facilitating adaptation along the lifecycle of an enterprise and the LSE network. The theory of complex systems provides a set of heuristics that can be applied to support the formalization of the LSE industrial network and its dynamics, demonstrating how they can be enabled and at the same time controlled to keep the overall level of interoperability stable. Hence, today there is technology suitable to implement such systems, capable to realize the LSE real, digital and virtual worlds. However, isolated, this technology cannot deliver the requirements for a self-sustainable LSE network. The authors propose a novel metaphor from complexity as a framework to model and implement the mechanism for sustaining interoperability in such networked environments. They identify the motivations for sustaining interoperability of networked liquid-sensing enterprises, having complex and adaptive systems as a vehicle to model and understand the relationships between enterprises and enterprise information systems in networked environments. Then, existing technology such as model-driven interoperability, agent-based or service oriented architectures, and knowledge management, is proposed to detail the conceptual solution for the sustainability of interoperability. An instantiation of the concept proposed is presented, which details the prototypal application elaborated in a real manufacturing scenario, implemented and validated during the European Project Factories of the Future IMAGINE.

Dynamic Adaptors to Support Model-Driven Interoperability and Enhance Sensing Enterprise Networks

In an increasingly complex environment, the enterprises of the future should become Sensing Enterprises, evidencing intelligent, dynamic and self-organizing capabilities for understanding and responding to the shifts that impact the networks they belong to. Reconfiguration and reprioritization of industrial processes, information models, and even terminology is now seen as a requirement for survivability, which means that software systems need to become more agile. Hence, software adaptor technologies such as the ATLAS Transformation Language (ATL) are gaining momentum due to the potential to define and regulate peer-to-peer communication among networks of enterprise systems. At present, ATL is the de facto standard for transformations within the framework of model-driven interoperability (MDI), nonetheless it lacks the dynamism required to streamline complex systems, which demand adaptors to be frequently redesigned whenever information models change. This paper presents a novel solution, which aims to reduce the setbacks that arise from this lack of dynamism.