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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.

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. [ABSTRACT FROM AUTHOR]

Model-driven game development (MDGD) introduces model-driven methodology to the computer game domain, shifting the focus of game development from coding to modeling to make game development faster and easier. The research on MDGD is concerned with both the general model-driven software development methodology and the particular characteristics of game development. People in the MDGD community have proposed several approaches in the past decades, addressing both the technology and the development process in the context of MDGD. This article presents the state-of-art of MDGD research based on a literature review of 26 approaches in the field. The review is structured around five perspectives: target game domains, domain frameworks, modelling languages, tooling, and evaluation methods. The article also includes reflections and a discussion of the challenges within MDGD [ABSTRACT FROM AUTHOR]

An important challenge in parallel computing is the mapping of parallel algorithms to parallel computing platforms. This requires several activities such as the analysis of the parallel algorithm, the definition of the logical configuration of the platform and the implementation and deployment of the algorithm to the computing platform. However, in current parallel computing approaches very often only conceptual and idiosyncratic models are used which fall short in supporting the communication and analysis of the design decisions. In this article, we present ParDSL, a domain-specific language framework for providing explicit models to support the activities for mapping parallel algorithms to parallel computing platforms. The language framework includes four coherent set of domain-specific languages each of which focuses on an activity of the mapping process. We use the domain-specific languages for modeling the design as well as for generating the required platform-specific models and the code of the selected parallel algorithm. In addition to the languages, a library is defined to support systematic reuse. We discuss the overall architecture of the language framework, the separate DSLs, the corresponding model transformations and the toolset. The framework is illustrated for four different parallel computing algorithms. [ABSTRACT FROM AUTHOR]

Highlights • A framework for the development of DSLs for data mining democratisation (DMDLs). • Development costs of these DMDLs reduces by 50%. • Development costs of DMDLs decrease by promoting reuse. Abstract Companies have an increasing interest in employing data mining to take advantage of the vast amounts of data their systems store nowadays. This interest confronts two problems: (1) business experts usually lack the skills required to apply data mining techniques, and (2) the specialists who know how to use these techniques are a scarce and valuable asset. To help democratise data mining, we proposed, in a previous work, the development of domain-specific languages (DSLs) that hide the complexity of data mining techniques. The objective of these DSLs is to allow business experts to specify analysis processes by using high-level primitives and terminology from the application domain. These specifications would then be automatically transformed into a low-level, executable form. Although these DSLs might offer a promising solution to the aforementioned problems, their development from scratch requires a considerable effort and, consequently, they are costly. In order to make these languages affordable, we present FLANDM, an ecosystem devised for the rapid development of DSLs for data mining democratisation. FLANDM provides a base infrastructure that can be easily customised for the particularities of each domain, enabling controlled and systematic reuse of previously developed artefacts. By using FLANDM, new DSLs for data mining democratisation can be defined achieving a 50% of reduction in their development costs. [ABSTRACT FROM AUTHOR]

Models are widely used not only in computer science field, but also in other fields. They are an effective way to show relevant information in a convenient way. Model-driven software development uses models and transformations as first-class citizens. That makes software development phases more related to each other, those links later help to make changes or modify software product more freely. At the moment there are a lot of methods and techniques to create those models and transform them into each other. Since 2004, authors have been developing the so called 2HMD approach to bridge the gap between problem domain and software components by using models and model transformation. The goal of this research is to compare different methods positioned for performing the same tasks as the 2HMD approach and to understand the state of the art in the area of model-driven software development.

Developing high quality, reliable and on time software systems is challenging due to the increasing size and complexity of these systems. Traditional software development approaches are not suitable for dealing with such challenges, so several approaches have been introduced to increase the productivity and reusability during the software development process. Two of these approaches are Component-Based Software Engineering (CBSE) and Model-Driven Software Development (MDD) which focus on reusing pre-developed code and using models throughout the development process respectively. There are many research studies that show the benefits of using software components and model-driven approaches. However, in many cases the development process is either ad-hoc or not well-defined. This paper proposes a new software development process model that merges CBSE and MDD principles to facilitate software development. The model is successfully tested by applying it to the development of an e-learning system as an exemplar case study.

Mobile app development is an activity predominantly performed by software developers. Domain experts and future users are merely considered in early development phases as source of requirements or consulted for evaluating the resulting product. In the domain of business apps, many cross-platform programming frameworks exist but approaches also targeted at non-technical users are rare. Existing graphical notations for describing apps either lack the simplicity to be understandable by domain experts or are not expressive enough to support automated processing. The MAML framework is proposed as model-driven approach for describing mobile apps in a platform-agnostic fashion not only for software developers but also for process modelers and domain experts. Data, views, business logic, and user interactions are jointly modeled from a process perspective using a graphical domain-specific language. To aggregate multiple use cases and provide advanced modeling support, an inference mechanism is utilized to deduce a global data model. Through model transformations, native apps are then automatically generated for multiple platforms without manual programming. Our approach is compared to the IFML notation in an observational study, with promising results regarding readability and usability. [ABSTRACT FROM AUTHOR]

The project Autonomous Terrain-based Optical Navigation (ATON) at the German Aerospace Center (DLR) is developing an optical navigation system for future landing missions on celestial bodies such as the moon or asteroids. Image data obtained by optical sensors can be used for autonomous determination of the spacecraft’s position and attitude. Camera-in-the-loop experiments in the Testbed for Robotic Optical Navigation (TRON) laboratory and flight campaigns with unmanned aerial vehicle (UAV) are performed to gather flight data for further development and to test the system in a closed-loop scenario. The software modules are executed in the C++ Tasking Framework that provides the means to concurrently run the modules in separated tasks, send messages between tasks, and schedule task execution based on events. Since the project is developed in collaboration with several institutes in different domains at DLR, clearly defined and well-documented interfaces are necessary. Preventing misconceptions caused by differences between various development philosophies and standards turned out to be challenging. After the first development cycles with manual Interface Control Documents (ICD) and manual implementation of the complex interactions between modules, we switched to a model-based approach. The ATON model covers a graphical description of the modules, their parameters and communication patterns. Type and consistency checks on this formal level help to reduce errors in the system. The model enables the generation of interfaces and unified data types as well as their documentation. Furthermore, the C++ code for the exchange of data between the modules and the scheduling of the software tasks is created automatically. With this approach, changing the data flow in the system or adding additional components (e.g., a second camera) have become trivial. [ABSTRACT FROM AUTHOR]

Pest control is a major issue in agricultural management due to crop yield losses caused by pests. In this context, integrated pest management aims to suppress pest populations below an action threshold to minimize their impact. This paper presents the development of a web tool based on the Spanish regulations for the integrated pest management of table grapes; this provides decision support for evaluating when a particular pest action threshold has been crossed thus affecting table grape crops. The tool was built using a model-driven software development approach that enables software system generation from the problem's knowledge model. The design of the knowledge bases which contain the system's decision rules is also described. It is divided into knowledge bases that contain general knowledge related to the table grape crop as well as several specific knowledge bases (one per pest) containing the reasoning model that deduces the risk associated with a particular pest. The software has been designed by applying the model-driven development method thus making the system flexible, easy to evolve and adaptable whenever a new pest has to be incorporated into the software. [ABSTRACT FROM AUTHOR]