Model-driven Engineering Techniques Research Articles

Towards a GDPR-compliant cloud architecture with data privacy controlled through sticky policies.

Data privacy is one of the biggest challenges facing system architects at the system design stage. Especially when certain laws, such as the General Data Protection Regulation (GDPR), have to be complied with by cloud environments. In this article, we want to help cloud providers comply with the GDPR by proposing a GDPR-compliant cloud architecture. To do this, we use model-driven engineering techniques to design cloud architecture and analyze cloud interactions. In particular, we develop a complete framework, called MDCT, which includes a Unified Modeling Language profile that allows us to define specific cloud scenarios and profile validation to ensure that certain required properties are met. The validation process is implemented through the Object Constraint Language (OCL) rules, which allow us to describe the constraints in these models. To comply with many GDPR articles, the proposed cloud architecture considers data privacy and data tracking, enabling safe and secure data management and tracking in the context of the cloud. For this purpose, sticky policies associated with the data are incorporated to define permission for third parties to access the data and track instances of data access. As a result, a cloud architecture designed with MDCT contains a set of OCL rules to validate it as a GDPR-compliant cloud architecture. Our tool models key GDPR points such as user consent/withdrawal, the purpose of access, and data transparency and auditing, and considers data privacy and data tracking with the help of sticky policies.

Using model-driven engineering to automate software language translation

The porting or translation of software applications from one programming language to another is a common requirement of organisations that utilise software, and the increasing number and diversity of programming languages makes this capability as relevant today as in previous decades. Several approaches have been used to address this challenge, including machine learning and the manual definition of direct language-to-language translation rules, however the accuracy of these approaches remains unsatisfactory. In this paper we describe a new approach to program translation using model-driven engineering techniques: reverse-engineering source programs into specifications in the UML and OCL formalisms, and then forward-engineering the specifications to the required target language. This approach can provide assurance of semantic preservation, and additionally has the advantage of extracting precise specifications of software from code. We provide an evaluation based on a comprehensive dataset of examples, including industrial cases, and compare our results to those of other approaches and tools. Our specific contributions are: (1) Reverse-engineering source programs to detailed semantic models of software behaviour, to enable semantically-correct translations and reduce re-testing costs; (2) Program abstraction processes defined by precise and explicit rules, which can be edited and configured by users; (3) A set of reusable OCL library components appropriate for representing program semantics, and which can also be used for OCL specification of new applications; (4) A systematic procedure for building program abstractors based on language grammars and semantics.

A DSL-based Approach for Code Generation and Navigation Process Management in a Single Page Application

Single page applications (SPAs) are web applications that offer a fast and responsive user experience, but also pose some challenges in terms of navigation process management and platform compatibility. In this paper, we propose a DSL-based approach for code generation and management of SPA navigation process, based on the visual vocabulary proposed by Garrett. We use a Domain-Specific Language (DSL) to describe the elements of the SPA, such as pages, connectors, and transitions, in a concise and abstract way. We also propose a metamodel for Garrett vocabulary, which defines the concepts and relationships of the DSL. Then, we apply a Model-Driven Engineering (MDE) technique to transform the DSL specification into a platform-specific project architecture and basic code for an SPA. We present a case study of using our DSL to generate an Angular SPA and evaluate the benefits of our approach in terms of productivity, maintainability, and reusability.

A Graph-Based Approach for Modelling Quantum Circuits

A crucial task for the systematic application of model-driven engineering techniques in the development of quantum software is the definition of metamodels, as a first step towards automatic code generation and integration with other tools. The importance is even greater when considering recent work where the first extensions to UML for modelling quantum circuits are emerging and the characterisation of these extensions in terms of their suitability for a model-driven approach becomes unavoidable. After reviewing the related work, this article proposes a unified metamodel for modelling quantum circuits, together with five strategies for its use and some examples of its application. The article also provides a set of constraints for using the identified strategies, a set of procedures for transforming the models between the strategies, and an analysis of the suitability of each strategy for performing common tasks in a model-driven quantum software development environment. All of these resources will enable the quantum software community to speak the same language and use the same set of abstractions, which are key to furthering the development of tools to be built as part of future model-driven quantum software development frameworks.

Lessons learned from applying model-driven engineering in 5 domains: The success story of the MontiGem generator framework

We report on our success stories in developing and using Model-Driven Engineering (MDE) tools for information systems on real-world projects within different application domains. It is necessary that we ensure the extensibility and adaptability of code generators if we want to reuse them for different domains. Up to now, research on reusing software has been mainly conducted in the software product line community but rarely discussed in the context of code generators. This paper introduces the generation framework MontiGem and shows how it has been used and evolved within five different research and industry projects in the domains of financial management, IoT, energy management, privacy policy, and wind turbine engineering. We have developed the code generator within the first project and further refined it with each of the following projects. This paper describes the projects, shows how MDE helped us in the software engineering process, and discusses the lessons we learned. These examples show how MDE techniques can be successfully applied to the development of information systems in practice, although further requirements have been met over time.

Natural Language–Based Conceptual Modelling Frameworks: State of the Art and Future Opportunities

Identifying requirements for an information system is an important task and conceptual modelling is the first step in this process. Conceptual modelling plays a critical role in the information system design process and usually involves domain experts and knowledge engineers who brainstorm together to identify the required knowledge to build an information system. The conceptual modelling process starts with the collection of necessary information from the domain experts by the knowledge engineers. Afterwards, the knowledge engineers use traditional model driven engineering techniques to design the system based on the collected information. Natural language–based conceptual modelling frameworks or systems are used to help domain experts and knowledge engineers in eliciting requirements and building conceptual models from a natural language text. In this article, we discuss the state of the art of some recent conceptual modelling frameworks that are based on natural language. We take a closer look at how these frameworks are built, in particular at the underlying motivation, architecture, types of natural language used (e.g., restricted vs. unrestricted), types of the conceptual model generated, verification support of the requirements specifications as well as the conceptual models, and underlying knowledge representation formalism. We also discuss some future research opportunities that these frameworks offer.

Model-Driven Engineering Techniques and Tools for Machine Learning-Enabled IoT Applications: A Scoping Review.

This paper reviews the literature on model-driven engineering (MDE) tools and languages for the internet of things (IoT). Due to the abundance of big data in the IoT, data analytics and machine learning (DAML) techniques play a key role in providing smart IoT applications. In particular, since a significant portion of the IoT data is sequential time series data, such as sensor data, time series analysis techniques are required. Therefore, IoT modeling languages and tools are expected to support DAML methods, including time series analysis techniques, out of the box. In this paper, we study and classify prior work in the literature through the mentioned lens and following the scoping review approach. Hence, the key underlying research questions are what MDE approaches, tools, and languages have been proposed and which ones have supported DAML techniques at the modeling level and in the scope of smart IoT services.

Towards an integrated automatic design process for robot swarms.

Background: The specification of missions to be accomplished by a robot swarm has been rarely discussed in the literature: designers do not follow any standardized processes or use any tool to precisely define a mission that must be accomplished. Methods: In this paper, we introduce a fully integrated design process that starts with the specification of a mission to be accomplished and terminates with the deployment of the robots in the target environment. We introduce Swarm Mission Language (SML), a textual language that allows swarm designers to specify missions. Using model-driven engineering techniques, we define a process that automatically transforms a mission specified in SML into a configuration setup for an optimization-based design method. Upon completion, the output of the optimization-based design method is an instance of control software that is eventually deployed on real robots. Results: We demonstrate the fully integrated process we propose on three different missions. Conclusions: We aim to show that in order to create reliable, maintainable and verifiable robot swarms, swarm designers may benefit from following standardised automatic design processes that will facilitate the design of control software in all stages of the development.

Engineering the development of quantum programs: Application to the Boolean satisfiability problem

The development of quantum programs is becoming a reality due to the rapid advancement of quantum computing. Over the past few years, a multitude of hardware platforms, algorithms, and programming languages have emerged to support this paradigm. By the very nature of Quantum Mechanics principles, there is an enormous change of philosophy when building quantum programs, which operate in a probabilistic space, unlike the deterministic behaviour shown by classical programming languages. These conceptual differences can be overcome by using techniques and tools of Software Engineering. In this paper, we apply Model-Driven Engineering techniques in a systematic way to ease the generation of quantum programs and we apply it to solve the satisfiability problem, very important in many engineering domains like verification of discrete systems and test of integrated circuits. To that aim, we contribute with a metamodel for representing quantum circuits and a model-to-text transformation to generate working IBM Qiskit code. This model-driven infrastructure is employed to automatically generate quantum programs from SAT equations through a model-to-model transformation that embeds Grover’s algorithm. Besides, we provide formulas for calculating the number of required quantum elements from SAT equations, crucial in the current context of limited quantum resources. The interoperability with other tools and the extensibility to target additional quantum platforms is guaranteed thanks to the use of a model-based toolchain. We cover several usage scenarios to validate the approach, providing exemplary SAT equations, the generated Qiskit code and the results of executing this code in IBM Quantum infrastructure.

A Reference Architecture for Data-Driven and Adaptive Internet-Delivered Psychological Treatment Systems: Software Architecture Development and Validation Study.

BackgroundInternet-delivered psychological treatment (IDPT) systems are software applications that offer psychological treatments via the internet. Such IDPT systems have become one of the most commonly practiced and widely researched forms of psychotherapy. Evidence shows that psychological treatments delivered by IDPT systems can be an effective way of treating mental health morbidities. However, current IDPT systems have high dropout rates and low user adherence. The primary reason is that the current IDPT systems are not flexible, adaptable, and personalized as they follow a fixed tunnel-based treatment architecture. A fixed tunnel-based architecture follows predefined, sequential treatment content for every patient, irrespective of their context, preferences, and needs. Moreover, current IDPT systems have poor interoperability, making it difficult to reuse and share treatment materials. There is a lack of development and documentation standards, conceptual frameworks, and established (clinical) guidelines for such IDPT systems. As a result, several ad hoc forms of IDPT models exist. Consequently, developers and researchers have tended to reinvent new versions of IDPT systems, making them more complex and less interoperable.ObjectiveThis study aimed to design, develop, and evaluate a reference architecture (RA) for adaptive systems that can facilitate the design and development of adaptive, interoperable, and reusable IDPT systems.MethodsThis study was conducted in collaboration with a large interdisciplinary project entitled INTROMAT (Introducing Mental Health through Adaptive Technology), which brings together information and communications technology researchers, information and communications technology industries, health researchers, patients, clinicians, and patients’ next of kin to reach its vision. First, we investigated previous studies and state-of-the-art works based on the project’s problem domain and goals. On the basis of the findings from these investigations, we identified 2 primary gaps in current IDPT systems: lack of adaptiveness and limited interoperability. Second, we used model-driven engineering and Domain-Driven Design techniques to design, develop, and validate the RA for building adaptive, interoperable, and reusable IDPT systems to address these gaps. Third, based on the proposed RA, we implemented a prototype as the open-source software. Finally, we evaluated the RA and open-source implementation using empirical (case study) and nonempirical approaches (software architecture analysis method, expert evaluation, and software quality attributes).ResultsThis paper outlines an RA that supports flexible user modeling and the adaptive delivery of treatments. To evaluate the proposed RA, we developed an open-source software based on the proposed RA. The open-source framework aims to improve development productivity, facilitate interoperability, increase reusability, and expedite communication with domain experts.ConclusionsOur results showed that the proposed RA is flexible and capable of adapting interventions based on patients’ needs, preferences, and context. Furthermore, developers and researchers can extend the proposed RA to various health care interventions.

Model-driven system-level validation and verification on the space software domain

The development process of on-board software applications can benefit from model-driven engineering techniques. Model validation and model transformations can be applied to drive the activities of specification, requirements definition, and system-level validation and verification according to the space software engineering standards ECSS-E-ST-40 and ECSS-Q-ST-80. This paper presents a model-driven approach to completing these activities by avoiding inconsistencies between the documents that support them and providing the ability to automatically generate the system-level validation tests that are run on the Ground Support Equipment and the matrices required to complete the software verification. A demonstrator of the approach has been built using as a proof of concept a subset of the functionality of the software of the control unit of the Energetic Particle Detector instrument on-board Solar Orbiter.

Towards an integrated automatic design process for robot swarms

Background: The specification of missions to be accomplished by a robot swarm has been rarely discussed in the literature: designers do not follow any standardized processes or use any tool to precisely define a mission that must be accomplished. Methods: In this paper, we introduce a fully integrated design process that starts with the specification of a mission to be accomplished and terminates with the deployment of the robots in the target environment. We introduce Swarm Mission Language (SML), a textual language that allows swarm designers to specify missions. Using model-driven engineering techniques, we define a process that automatically transforms a mission specified in SML into a configuration setup for an optimization-based design method. Upon completion, the output of the optimization-based design method is an instance of control software that is eventually deployed on real robots. Results: We demonstrate the fully integrated process we propose on three different missions. Conclusions: We aim to show that in order to create reliable, maintainable and verifiable robot swarms, swarm designers need to follow standardised automatic design processes that will facilitate the design of control software in all stages of the development.

A model-driven approach for continuous performance engineering in microservice-based systems

Microservices are quite widely impacting on the software industry in recent years. Rapid evolution and continuous deployment represent specific benefits of microservice-based systems, but they may have a significant impact on non-functional properties like performance. Despite the obvious relevance of this property, there is still a lack of systematic approaches that explicitly take into account performance issues in the lifecycle of microservice-based systems.In such a context of evolution and re-deployment, Model-Driven Engineering techniques can provide major support to various software engineering activities, and in particular they can allow managing the relationships between a running system and its architectural model.In this paper, we propose a model-driven integrated approach that exploits traceability relationships between the monitored data of a microservice-based running system and its architectural model to derive recommended refactoring actions that lead to performance improvement. The approach has been applied and validated on two microservice-based systems, in the domain of e-commerce and ticket reservation, respectively, whose architectural models have been designed in UML profiled with MARTE.

MIKADO: a smart city KPIs assessment modeling framework

Smart decision making plays a central role for smart city governance. It exploits data analytics approaches applied to collected data, for supporting smart cities stakeholders in understanding and effectively managing a smart city. Smart governance is performed through the management of key performance indicators (KPIs), reflecting the degree of smartness and sustainability of smart cities. Even though KPIs are gaining relevance, e.g., at European level, the existing tools for their calculation are still limited. They mainly consist in dashboards and online spreadsheets that are rigid, thus making the KPIs evolution and customization a tedious and error-prone process. In this paper, we exploit model-driven engineering (MDE) techniques, through metamodel-based domain-specific languages (DSLs), to build a framework called MIKADO for the automatic assessment of KPIs over smart cities. In particular, the approach provides support for both: (i) domain experts, by the definition of a textual DSL for an intuitive KPIs modeling process and (ii) smart cities stakeholders, by the definition of graphical editors for smart cities modeling. Moreover, dynamic dashboards are generated to support an intuitive visualization and interpretation of the KPIs assessed by our KPIs evaluation engine. We provide evaluation results by showing a demonstration case as well as studying the scalability of the KPIs evaluation engine and the general usability of the approach with encouraging results. Moreover, the approach is open and extensible to further manage comparison among smart cities, simulations, and KPIs interrelations.

Model-Driven Engineering for End-Users in the Loop in Smart Ambient Systems

At the heart of cyber-physical and ambient systems, the user should permanently benefit from applications adapted to the situation and her/his needs. To do this, she/he must be able to configure her/his software environment and be supported as much as possible in that task. To this end, an intelligent “engine” assembles software components that are present in the ambient environment at the time and makes unanticipated applications emerge. The problem is to put the user “in the loop”, i.e., provide adapted and intelligible descriptions of the emerging applications, and present them so that the user can accept, modify or reject them. Besides, user feedback must be collected to feed the engine’s learning process. Our approach relies on Model-Driven Engineering (MDE). However, differently from the regular use of MDE tools and techniques by engineers to develop software and generate code, our focus is on end-users. Models of component assemblies are represented and made editable for them. Based on a metamodel that supports modeling and de- scription of component-based applications, a user interface provides multi-faceted representations of the emerging applications and captures user feedback. Our solution relies on several domain- specific languages and a transformation process, based on the established MDE tools (Gemoc studio, Eclipse Modeling Framework, EcoreTools, Sirius, Acceleo). It works in conjunction with the intelligent engine that builds the emerging applications and to which it provides learning data.

Specification, detection, and treatment of STRIDE threats for software components: Modeling, formal methods, and tool support

The existence of security threats in software designs can significantly impact the safe and reliable operation of systems. Threats need to be precisely specified before a tool can manipulate them, and though several approaches for threat specification have been proposed, they do not provide the scalability and flexibility required in practice. We take this problem towards an integrated approach for threat detection and treatment by means of security requirements, during the software architecture design time. The general idea of the approach is to: (1) specify threats as properties of a modeled system in a technology-independent specification language; (2) express conditions that reveal these threats in a suitable language with automated tool support for threat detection through model verification; and (3) suggest a set of security requirements to protect against detected threats. The formalized threats and security requirements are then provided as formal model libraries to foster reuse. To validate our work, we explore a set of representative threats from categories based on Microsoft’s STRIDE threat classification in the context of secure component-based software architecture development. In addition, we use model-driven engineering techniques for the development of a tool set to support our approach.

Transformation of Struts Model to Codeigniter Model

Abstract The frameworks are more and more used for the realization of information systems. A framework allows the design to be reused for an entire domain in order to reduce costs and improve the quality of software. The use of models, metamodel and models transformation is the center of the MDA approach. This research project aims to find a way to transform struts models, using the QVT-O transformation language and Model-driven Engineering Techniques, to Codeigniter models.

Leveraging Iterative Plan Refinement for Reactive Smart Manufacturing Systems

Industry 4.0 production systems must support flexibility in various dimensions, such as for the products to be produced, for the production processes to be applied, and for the available machinery. In this article, we present a novel approach to design and control smart manufacturing systems. The approach is reactive, that is responds to unplanned situations and implements an iterative refinement technique, that is, optimizes itself during runtime to better accommodate production goals. For realizing these advances, we present a model-driven methodology and we provide a prototypical implementation of such a production system. In particular, we employ Planning Domain Definition Language (PDDL) as our artificial intelligence environment for automated planning of production processes and combine it with one of the most prominent Industry 4.0 standards for the fundamental production system model: IEC 62264. We show how to plan the assembly of small trucks from available components and how to assign specific production operations to available production resources, including robotic manipulators and transportation system shuttles. Results of the evaluation indicate that the presented approach is feasible and that it is able to significantly strengthen the flexibility of production systems during runtime. Note to Practitioners —Smart production is an umbrella for a number of shifts and initiatives that deal with digitization of manufacturing/production systems and related issues and potentials. In this work, we present an approach for utilizing automated planning for creating production plans. This is in contrast to the traditional approach, where recipes are programmed into the production system ahead-of-time. However, automated planning relies on specific languages and tools that are hard to master by nonexperts, which is a factor that strongly limited the utilization of plan-driven approaches for industrial automation in practice. Thus, we propose to generate planning tasks automatically with model-driven engineering techniques. We are utilizing the industrial standard IEC 62264 for the description of the production system, and the academic standard Planning Domain Definition Language (PDDL) for planning. PDDL is handled completely transparent to the user, that is the user is shielded from its complexity by employing the IEC 62264 model as the sole frontend.

IDFML: A Meta Language for Heterogeneous DSMLs Coordination

The popularization of both Software Language Engineering (SLE) and Model Driven Engineering (MDE) as well as the increasing complexity of systems induce new implementation practices. Indeed, many teams of experts collaborate to implement a same system. Every team uses her own domain specific modeling language (DSML) to represent her concerns. Consequently, by the end of the modelling phase, we get many heterogeneous models elaborated using different DSMLs. These models need to be composed to get a whole view of systems, to be able to validate and simulate behaviors. However, many recent researches choose to compose modelling languages rather than models themselves, but until now there are no standard or generic techniques for that. Although, MDE and SLE provide tools and concepts for modeling, customizing and processing business concepts as single activities, in contrast they provide little support for coordinating between these activities. In this paper, authors propose an interface-based approach to coordinate DSMLS in order to compose and coordinate their respective models. They began by giving generic guidelines of DSMLs specification and composition aspects. Then, they introduce IDFML a Meta language for defining both DSMLs interfaces and coordination. Actually, the proposed Meta language gives a metamodeling background to coordination which enables to benefit from MDE tools and techniques. They finally demonstrate the applicability of the approach using a Connected Indoor Transport Service System to conclude by summarizing benefits of the proposed Methodology.

Automatic generation of Web of Things servients using Thing Descriptions

Similarly to the standardization effort initiated for the World Wide Web in the 1990s, the World Wide Web Consortium is currently working on the Web of Things (WoT) specification. This initiative aims to tackle current fragmentation in the so-called Internet of Things by using existing Web standards. The ultimate goal is to cope with the increasing number of devices that are being connected to the Internet and to enable interoperability among them. On the other hand, Model-Driven Engineering (MDE) approaches make use of models to raise the abstraction level with the objective of accelerating the software development process, enabling design and code reuse, and increasing software quality.This work proposes to apply MDE techniques to enable the efficient development of WoT servients. Based on the WoT Thing Description specification, this work proposes both a textual-based concrete syntax and a model-based abstract syntax—both fully compliant with the WoT specification—that enable the generation of WoT servients in C++ with CoAP communication capabilities. This proposal is implemented by a tool that covers the whole development process, which is publicly available under an open source license.