In this paper we present MicroBuilder, the tool used for the specification of a software architecture that follows REST microservice design principles. MicroBuilder comprises MicroDSL and MicroGenerator modules. The MicroDSL module provides the MicroDSL domain-specific language used for the specification of REST microservice software architecture. In this paper we present MicroDSL meta-model, specified in Ecore, together with textual and graphical concrete syntaxes, specified using Xtext and Sirius frameworks respectively. The MicroGenerator module is used to generate executable program code based on MicroDSL specification. In this paper we also present results of the MicroBuilder tool evaluation, alongside the case study which illustrates a usage of MicroBuilder.

Industry 4.0 aims to establish highly flexible production, enabling effective and efficient mass customisation of products. Modelling techniques and simulation of production processes are among the core techniques of the manufacturing industry that facilitate flexibility and automation of a shop floor in the era of Industry 4.0. In this paper, we present an approach to support production process modelling and process model management. The approach is based on Model-Driven (MD) principles and comprises a Domain-Specific Modelling Language (DSML) named Multi-Level Production Process Modelling Language (MultiProLan). MultiProLan uses a set of concepts to specify production process models suitable for automatic instruction generation and execution of the instructions in a simulation or on a shop floor. By using MultiProLan, process designers may create process models independent of the specific production system. Such process models can either be automatically enriched by matching and scheduling algorithms or manually enriched by a process designer via MultiProLan’s modelling tool. In this paper, we also present an application of our approach in the assembly industry to showcase its dynamic resource management, generation of production documentation, error handling and process monitoring.

Technological advances and increasing customer need for highly customized products have triggered a fourth industrial revolution. A digital revolution in the manufacturing industry is enforced by introducing smart devices and knowledge bases to form intelligent manufacturing information systems. One of the goals of the digital revolution is to allow flexibility of smart factories by automating shop floor changes based on the changes in input production processes and ordered products. In order to make this possible, a formal language to describe production processes is needed, together with a code generator for its models and an engine to execute the code on smart devices. Existing process modeling languages are not usually tailored to model production processes, especially if models are needed for automatic code generation. In this paper we propose a research on Industry 4.0 manufacturing using a Domain-Specific Modeling Language (DSML) within a Model-Driven Software Development (MDSD) approach to model production processes. The models would be used to generate instructions to smart devices and human workers, and gather a feedback from them during the process execution. A pilot comparative analysis of three modeling languages that are commonly used for process modeling is given with the goal of identifying supported modeling concepts, good practices and usage patterns.

Reengineering is one of the key concepts in software maintenance and evolution. It generally includes some form of reverse engineering followed by some form of forward engineering or restructuring. In the paper we focus on database reverse engineering. Model-driven software engineering promotes the idea of abstracting implementation details by focusing on: models as first class entities and automated generation of models or code from other models. In the approach meta-models are used to define the modeling languages. A database reverse engineering process can benefit of integrating meta-modeling and meta-models in the process. The plethora of models related to databases points out to the need and importance of model-to-model transformations between these models at different abstraction levels. These transformations are based on meta-models that are conformed by the source and target models of the transformations. A database reverse engineering process can be performed through a chain of model-to-model transformations based on a set of meta-models. In the paper we discuss the importance of meta-modeling in the context of database reverse engineering and present a case study illustrating an approach to database reverse engineering.