Model-driven Engineering Approach Research Articles

Lean requirements traceability automation enabled by model-driven engineering.

BackgroundThe benefits of requirements traceability, such as improvements in software product and process quality, early testing, and software maintenance, are widely described in the literature. Requirements traceability is a critical, widely accepted practice. However, very often it is not applied for fear of the additional costs associated with manual efforts or the use of additional tools.MethodsThis article presents a “low-cost” mechanism for automating requirements traceability based on the model-driven paradigm and formalized by a metamodel for the creation and monitoring of traces and an integration process for traceability management. This approach can also be useful for information fusion in industry insofar that it facilitates data traceability.ResultsThis article extends an existing model-driven development methodology to incorporate traceability as part of its development tool. The tool has been used successfully by several companies in real software development projects, helping developers to manage ongoing changes in functional requirements. One of those projects is cited as an example in the paper. The authors’ current work leads them to conclude that a model-driven engineering approach, traditionally used only for the automatic generation of code in a software development process, can also be used to successfully automate and integrate traceability management without additional costs. The systematic evaluation of traceability management in industrial projects constitutes a promising area for future work.

Low-code development and model-driven engineering: Two sides of the same coin?

The last few years have witnessed a significant growth of so-called low-code development platforms (LCDPs) both in gaining traction on the market and attracting interest from academia. LCDPs are advertised as visual development platforms, typically running on the cloud, reducing the need for manual coding and also targeting non-professional programmers. Since LCDPs share many of the goals and features of model-driven engineering approaches, it is a common point of debate whether low-code is just a new buzzword for model-driven technologies, or whether the two terms refer to genuinely distinct approaches. To contribute to this discussion, in this expert-voice paper, we compare and contrast low-code and model-driven approaches, identifying their differences and commonalities, analysing their strong and weak points, and proposing directions for cross-pollination.

Model-driven engineering for mobile robotic systems: a systematic mapping study

Mobile robots operate in various environments (e.g. aquatic, aerial, or terrestrial), they come in many diverse shapes and they are increasingly becoming parts of our lives. The successful engineering of mobile robotics systems demands the interdisciplinary collaboration of experts from different domains, such as mechanical and electrical engineering, artificial intelligence, and systems engineering. Research and industry have tried to tackle this heterogeneity by proposing a multitude of model-driven solutions to engineer the software of mobile robotics systems. However, there is no systematic study of the state of the art in model-driven engineering (MDE) for mobile robotics systems that could guide research or practitioners in finding model-driven solutions and tools to efficiently engineer mobile robotics systems. The paper is contributing to this direction by providing a map of software engineering research in MDE that investigates (1) which types of robots are supported by existing MDE approaches, (2) the types and characteristics of MRSs that are engineered using MDE approaches, (3) a description of how MDE approaches support the engineering of MRSs, (4) how existing MDE approaches are validated, and (5) how tools support existing MDE approaches. We also provide a replication package to assess, extend, and/or replicate the study. The results of this work and the highlighted challenges can guide researchers and practitioners from robotics and software engineering through the research landscape.

Model-driven round-trip engineering for TinyOS-based WSN applications

Wireless Sensor Network (WSN) applications working on TinyOS operating system is widely used in various areas. However, the requirement of managing the power constraints makes TinyOS different from ordinary systems and hence building WSNs with TinyOS can be a challenging and time-consuming task. As successfully applied in many other domains, model-driven engineering (MDE) can facilitate the design and implementation of such applications. Within this context, the researchers have performed noteworthy studies on deriving various MDE approaches and tools. However, these studies do not support the synchronization between TinyOS application models and the generated programs especially when any change is made in the programs. Hence, in this paper, we introduce a model-driven round-trip engineering (RTE) methodology in which both the MDE of TinyOS applications and synchronization between TinyOS instance models and corresponding code are provided with the use of a toolchain. A domain-specific modeling language, called DSML4TinyOS is used for the MDE of such applications while existing TinyOS programs can be reverse engineered in an environment, called RE4TinyOS. Models retrieved from the existing programs can be automatically processed again with DSML4TinyOS. Evaluation results showed that it is possible to obtain the configurations of the TinyOS applications completely just modeling with DSML4TinyOS whereas the same process leads the automatic creation of almost half of the module parts of these applications. Moreover, the time required for developing such systems from scratch decreased approximately to its half. The results also showed that both model-code synchronization and the integration of existing TinyOS applications which do not have system models previously, into the proposed MDE are possible with using RE4TinyOS. RE4TinyOS succeeded in the reverse engineering of all main parts of the TinyOS applications taken from the official TinyOS Github repository and generated models were able to be visually processed in the MDE environment for further modifications.

Advances and Challenges for Model and Data Engineering

Advances and Challenges for Model and Data Engineering

CARMEN: A framework for the verification and diagnosis of the specification of security requirements in cyber-physical systems

In the last years, cyber-physical systems (CPS) are receiving substantial mainstream attention especially in industrial environments, but this popularity has been accompanied by serious security challenges. A CPS is a complex system that includes hardware and software components, with different suppliers and connection protocols, forcing complex data management and storage. For this reason, the construction, verification and diagnosis of security CPS become a major challenge, which involves a correct specification of security requirements, the verification of the correct system configurations, and if necessary, the diagnosis to detect the features to be modified to obtain a security configuration. In this paper, we propose a framework for the verification and diagnosis of security requirements, according to the possible correct configurations of the CPS. The framework is based on the specification of the security requirements and their analysis supported by Model-Driven Engineering and Software Product Line Engineering (SPLE) approaches. To illustrate the usefulness, the proposal has been applied to the security requirements in an Agriculture 4.0 scenario based on automated hydroponic cultivation.

MEGDroid: A model-driven event generation framework for dynamic android malware analysis

The tremendous growth of Android malware in recent years is a strong motivation for the vast endeavor in detection and analysis of malware apps. A prominent approach for this purpose is dynamic analysis in which providing complex interactions with the samples under analysis is a need. Event generation tools are almost used to provide such interactions, but they have deficiencies for effective malware analysis. For example, anti-static and anti-dynamic analysis techniques employed by the malware prevent event generators to extract sufficient information for generating appropriate events. As a result, they fail to trigger malicious payloads or obtain high code coverage in most cases. In this paper, we aim to present a new framework to improve the event generation process for dynamic analysis of Android malware. We propose MEGDroid, a Model Driven Engineering (MDE) framework in which malware-related information is automatically extracted and represented as a domain-specific model. This model, then is used to generate appropriate events for malware analysis using model-to-model and model-to-code transformations. The proposed model-driven artifacts also provide required facilities to put the human in the loop for properly taking his/her knowledge into account. The proposed framework has been realized as an Eclipse plugin and we performed extensive practical analysis on a set of malware samples selected from the AMD dataset. The experimental results showed that MEGDroid considerably increases the number of triggered malicious payloads as well as the execution code coverage compared with Monkey and DroidBot, as two state of the art general-purpose and malware specific event generators respectively. The proposed MDE approach, enhances the event generation process through both automatic event generation and analyzer user involvement who can efficiently direct the process to increase the effectiveness of the generated events considering small amount of information that is extractable from the malware code.

Computer-aided design for building multipurpose routing processes in discrete event simulation models

Good domain-modeling enables an appropriate separation of concerns that improves quality properties in the simulation models, such as modifiability and maintainability. In this paper, the interplay of abstraction and concreteness in advancing the theory and practice of Modelling and Simulation is improved using the Model-Driven Engineering levels for building simulation models devoted to routing processes. The definition of this type of processes is detailed as a domain-model conceived as an abstraction defined in a graph model. Such abstraction turns into a set of formal simulation models that are (later) translated into an executable implementation. The final simulation models are specified using Routed DEVS formalism. The methodological proposal is accomplished with the development of a Modelling and Simulation graphical software tool that uses the set of models (defined in terms of the Model-Driven Engineering approach) as the core of its operation. This graphical software tool is developed as a plug-in for Eclipse Integrated Development Environment with aims to take advantage of existent Modeling and Simulation software. Therefore, the usefulness of graphical modeling for supporting the development of the simulation models is empowered with a Model-Driven Engineering process. The main benefit obtained when the Model-Driven Engineering approach is used for modeling an abstraction of the final simulation model is a clear reduction of formalization and implementation times.

Synthesis-Based Engineering of Supervisory Controllers for Autonomous Robotic Navigation

When mobile robots are employed in transportation tasks involving contact with humans, their control software shall guarantee that in every possible circumstance safety and, in general, task requirements are guaranteed. When control models are manually translated into an executable implementation, it becomes cumbersome to provide such guarantees. Model-driven engineering approaches provide an answer to such a problem. Domain specific models are automatically translated into an executable implementation. Some model-driven engineering approaches exist that are specific to robotics. However, formal guarantees on correctness of the model and the generated implementation with respect to the requirements are, often, not provided. This paper investigates how a general purpose modelling language for supervisory controller synthesis can be used to formally model plants and requirements for a robotic navigation task and can generate an executable implementation that can be integrated into a leading middleware for robotic applications. The starting point is the modelling of the interface provided by existing navigation components available in the targeted middleware. We demonstrate, with simulations and real-life experiments, that the generated supervisory controller is suitable for real-time deployment and guarantees correctness of the model with respect to the requirements of the navigation task at hand. Results on the reaction time of the supervisory controller show that such reaction time is about twenty times smaller than the one of the same supervisory controller implemented with a conventional framework.

Model-Driven Engineering Tools and Languages for Cyber-Physical Systems–A Systematic Literature Review

The development of Cyber-physical Systems (CPS) draws more interest from both researchers and industrial practitioners considering the opportunities they offer in almost all areas of industry. However, the engineering and management of CPS are challenging tasks due to their inherent heterogeneity and complexity characteristics. Regarding the development of CPS, there currently exists no standard methodology owing to the complexity of the domain. One of the key approaches to reduce the development complexity for CPS is Model-driven Engineering (MDE), which is frequently used in many industrial domains for software development to increase the level of platform abstraction. Nevertheless, it is always almost challenging, especially for the new researchers in this field, to determine the appropriate tools and languages to perform a particular MDE activity during CPS development. To the best of our knowledge, there is no guideline that demonstrates which language(s)/tool(s) to use for the various MDE techniques/phases for the development of CPS. This paper presents a Systematic Literature Review (SLR) study that focuses on identifying and classifying the recent research practices pertaining to CPS development by applying MDE approaches. With the objective of providing a general overview of the field, the study evaluates 140 research papers published during 2010–2018. Accordingly, a precise view of the various MDE tools and languages used in the development life-cycle of CPS, addressed MDE techniques/activities, and targeted CPS components is presented. We believe that the conducted study will guide researchers and practitioners to identify appropriate tools and languages according to the system requirements. It may also help in getting an overall understanding of the research trends for further research and development on the MDE of CPS.

Model-Driven Simulation of Elastic OCCI Cloud Resources

Abstract Deploying a cloud configuration in a real cloud platform is mostly cost- and time- consuming, as large number of cloud resources have to be rented for the time needed to run the configuration. Thereafter, cloud simulation tools are used as a cheap alternative to test cloud configuration. However, most of the existing cloud simulation tools require extensive technical skills and do not support simulation of any kind of cloud resources. In this context, using a model-driven approach can be helpful as it allows developers to efficiently describe their needs at a high level of abstraction. To do, we propose, in this article, a model-driven engineering approach based on the Open Cloud Computing Interface(OCCI) standard metamodel and CloudSim toolkit. We firstly extend OCCI metamodel for the supporting simulation of any kind of cloud resources. Afterward, to illustrate the extensibility of our approach, we enrich the proposed metamodel by new simulation capabilities. As proof of concept, we study the elasticity and pricing strategies of Amazon Web Services (AWS). This article benefits from OCCIware Studio to design an OCCI simulation extension and to provide a simulation designer for designing cloud configurations to be simulated. We detail the approach process from defining an OCCI simulation extension until the generation and the simulation of the OCCI cloud configurations. Finally, we validate the proposed approach by providing a realistic experimentation to study its usability, the resources coverage rate and the cost. The results are compared with the ones computed from AWS.

Method for Attack Tree Data Transformation and Import Into IT Risk Analysis Expert Systems

Information technology (IT) security risk analysis preventatively helps organizations in identifying their vulnerable systems or internal controls. Some researchers propose expert systems (ES) as the solution for risk analysis automation since risk analysis by human experts is expensive and timely. By design, ES need a knowledge base, which must be up to date and of high quality. Manual creation of databases is also expensive and cannot ensure stable information renewal. These facts make the knowledge base automation process very important. This paper proposes a novel method of converting attack trees to a format usable by expert systems for utilizing the existing attack tree repositories in facilitating information and IT security risk analysis. The method performs attack tree translation into the Java Expert System Shell (JESS) format, by consistently applying ATTop, a software bridging tool that enables automated analysis of attack trees using a model-driven engineering approach, translating attack trees into the eXtensible Markup Language (XML) format, and using the newly developed ATES (attack trees to expert system) program, performing further XML conversion into JESS compatible format. The detailed method description, along with samples of attack tree conversion and results of conversion experiments on a significant number of attack trees, are presented and discussed. The results demonstrate the high method reliability rate and viability of attack trees as a source for the knowledge bases of expert systems used in the IT security risk analysis process.

Model-driven engineering and usability evaluation of self-adaptive user interfaces

Enes Yigitbas is a Senior Researcher at Paderborn University. In 2019, he got his doctoral degree in Computer Science under the advisory of Prof. Dr. Gregor Engels. During his doctorate, his research work was linked to various industrial projects in the Software Innovation Campus Paderborn (SICP). In this context, he was significantly involved in the implementation and management of various projects related to model-driven and human-centered software engineering, self-adaptive software systems, and human-computer interaction. His work on engineering adaptive user interfaces received a late-breaking results award at the ACM SIGCHI Symposium on Engineering Interactive Computing Systems. In addition to project and teaching activities, he is actively involved in various committee activities as well as serves as a reviewer for various international conferences and journals in the areas of Software Engineering and HCI. In his thesis, supervised by Prof. Dr. Gregor Engels (Paderborn University), he focused on the engineering and usability evaluation of self-adaptive user interfaces. Self-adaptive user interfaces (SAUIs) have been promoted as a solution for context variability due to their ability to automatically detect context changes and adapt to the current context-of-use at runtime. In the course of his thesis work, he developed a model-driven engineering approach which supports modeling, transformation, and execution of self-adaptive user interfaces. Furthermore, a novel on-the-fly usability testing solution for SAUIs has been introduced which allows to evaluate the end-user satisfaction of SAUIs by combining context monitoring together with collection of instant user feedback.

Model Driven Engineering for MPSoC Design Space Exploration

This paper presents a Model Driven Engineering approach for MPSoC Design Space Exploration (DSE) to deal with the ever-growing challenge of designing complex embedded systems. This approach allows the designer to automatically select the most adequate modeling solution for application, platform, and mapping between application and platform, in an integrated and simultaneous way and at a very early design stage, before system synthesis and code generation have been performed. The exploration is based on high-level estimates of physical characteristics of each candidate solution. In an experimental setting, the DSE tool automatically performs four design activities: it selects the number of processors, maps tasks to processors, allocates processors to bus segments, and sets the voltage of each processor. Experimental results, extracted from a DSE scenario for a real application, show that the proposed estimation and exploration approach may find a suitable solution regarding the design requirements and constraints in a very short time, with an acceptable accuracy, without relying on costly synthesis-and-simulation cycles.

A Methodology for Digital Twin Modeling and Deployment for Industry 4.0

The digital twin (DT) is a virtual representation of a physical object, which has been proposed as one of the key concepts for Industry 4.0. The DT provides a virtual representation of products along their lifecycle that enables the prediction and optimization of the behavior of a production system and its components. A methodology design using model-driven engineering (MDE) is proposed that strives toward being both flexible and generic. This approach is presented at two levels: first, a DT is modeled as a composition of basic components that provide basic functionalities, such as identification, storage, communication, security, data management, human-machine interface (HMI), and simulation; second, an aggregated DT is defined as a hierarchical composition of other DTs. A generic reference architecture based on these concepts and a concrete implementation methodology are proposed using AutomationML. This methodology follows an MDE approach that supports most of the DT features currently proposed in the literature. A case study has been developed, the proposed ideas are being evaluated with industrial case studies, and some of the preliminary results are described in this article. With the case study, it is possible to verify that the proposed methodology supports the creation and the deployment process of a DT.

Integrated model‐driven engineering of blockchain applications for business processes and asset management

AbstractBlockchain has attracted broad interests to build decentralised applications. A typical class of applications uses blockchain for the management of cross‐organisational business processes as well as assets. However, developing such applications without introducing vulnerabilities is hard for developers, not the least because the deployed code is immutable and can be called by anyone with access to the network. Model‐driven engineering (MDE) helps to reduce those risks, by combining proven code snippets as per the model specification, which is easier to understand than source code. Therefore, in this article, we present an approach for integrated MDE across business processes and asset management (e.g., for settlement). Our approach includes methods for fungible/non‐fungible asset registration, escrow for conditional payment, and asset swap. The proposed MDE approach is implemented in a smart contract generation tool called Lorikeet, and evaluated in terms of feasibility, functional correctness, and cost effectiveness.

Challenges for the Adoption of Model-Driven Web Engineering Approaches in Industry.

Challenges for the Adoption of Model-Driven Web Engineering Approaches in Industry.

A framework for Model-Driven Engineering of resilient software-controlled systems

Emergent paradigms of Industry 4.0 and Industrial Internet of Things expect cyber-physical systems to reliably provide services overcoming disruptions in operative conditions and adapting to changes in architectural and functional requirements. In this paper, we describe a hardware/software framework supporting operation and maintenance of software-controlled systems enhancing resilience by promoting a Model-Driven Engineering (MDE) process to automatically derive structural configurations and failure models from reliability artifacts. Specifically, a reflective architecture developed around digital twins enables representation and control of system Configuration Items properly derived from SysML Block Definition Diagrams, providing support for variation. Besides, a plurality of distributed analytic agents for qualitative evaluation over executable failure models empowers the system with runtime self-assessment and dynamic adaptation capabilities. We describe the framework architecture outlining roles and responsibilities in a System of Systems perspective, providing salient design traits about digital twins and data analytic agents for failure propagation modeling and analysis. We discuss a prototype implementation following the MDE approach, highlighting self-recovery and self-adaptation properties on a real cyber-physical system for vehicle access control to Limited Traffic Zones.

A model-driven engineering approach for the service integration of IoT systems

With the development of IoT devices and web services, the objects of the real world are more interconnected, which allows applications to extend their characteristics in different fields, including industrial or home environments, among other possible examples such as health, trade, transport, or agriculture. However, this development highlights the challenge of interoperability, because devices are heterogeneous and use different communication protocols and different data formats. For this reason, we propose a model for point-to-point integration in three-layer IoT applications: (a) hardware, which corresponds to the physical objects (controller, sensor and actuator), (b) communication, which is the bridge that allows the exchange of data between a MQTT queue and REST web services, and (c) integration, which establishes a sequence of transactions to coordinate the components of the system. For this purpose, a metamodel, a graphic editor and a code generator have been developed that allow the developer to design IoT systems formed by heterogeneous components without having in-depth knowledge of every hardware and software platform. In order to validate our proposal, a smart home scenario has been developed, with a series of sensors and actuators that combined show a complex behavior.

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.