The MDE Diploma: first international postgraduate specialization in model-driven engineering

During the last decade, Model Driven Engineering (MDE) has been proposed for supporting the development, maintenance and evolution of software systems. Model Driven Architecture (MDA), Software Factories and Eclipse Modeling Framework (EMF) are among the most representatives MDE approaches. Nowadays, it is well recognized that model transformation is at the heart of MDE approaches and, consequently represents one of the most important operations in MDE. However, despite the multitude of model transformation language proposals emerging from academic world and industry, these transformations are often manually specified; which is a tedious and error-prone task, and therefore an expensive process. Matching operation between metamodels is the keystone toward a (semi-)automatic transformation process. In this paper, the authors review metamodel matching techniques of the literature and then analyze their pros and cons in order to show how they can be useful for a semi-automatic transformation process. The result is a comparison of metamodel matching techniques, highlighting their similarities and differences in terms of information used for matching, demonstrating significant similarities between these techniques. Next, the authors compare four well-known metamodel matching techniques namely Similarity flooding, SAMT4MDE+ (extended Semi-Automatic Matching Tool for Model Driven Engineering), ModelCVS and AML (AtlanMod Matching Language) on ten couples of metamodels. For this comparison, the authors define a set of six criteria inspired from the database schema matching. One among these criteria is relevant to the quality of matching and for which we define a quality measure metrics. Furthermore, the authors develop a plug-in under Eclipse to support our comparison using ten couples of metamodels.

In this study, we investigate the usability of Model-Driven Engineering (MDE) through interviews with fifteen practitioners from diverse roles (e.g., developers, researchers, architects) and domains, and with a range of expertise levels across academic and industrial software sectors, capturing in-depth perspectives on its practical application. Participants emphasized MDE’s benefits in enhancing project robustness, reliability, development speed, and system organization. However, they also identified challenges such as a steep learning curve, technological constraints, organizational resistance, and a shortage of skilled professionals. To address these issues, participants recommended simplifying tools and language, improving consistency and flexibility, enhancing integration with existing workflows, and raising awareness of MDE. These insights provide valuable guidance for improving MDE usability and encouraging broader MDE adoption.

The integration of domain-specific concepts in a model-driven engineering (MDE) approach raises a number of interesting research questions. There are two possibilities to represent these concepts. The first one focuses on models that contain domain-specific concepts only, i.e. domain-specific modelling languages (DSML). The second one advocates the integration of domain-specific concepts in general-purpose models, using what we will refer to in this paper as domain-specific modelling annotation languages (DSMAL). In this position paper, we argue that each approach is particularly suited for specific activities and specific actors, and show how they can be developed and used together. We also highlight the challenges created by the use of two representations, such as the evaluation of models OCL constraints and the synchronisation between the two representations. As an illustration, we present rbacUML, our approach for integrating role-based access control (RBAC) concepts into an MDE approach.

Hardware-in-the-loop (HIL) testing is an integral part of the development of power system automation solutions. HIL test beds facilitate system-level testing and validation of controllers against their specifications. The information required for HIL test bed configurations is typically scattered across different tools used in the development of power system automation solutions. These tools often have different formats and naming schemes. This implies that a significant effort is required for consolidating data from the tools and for creating valid test configurations from the consolidated data. This paper presents a Model-Driven Engineering (MDE) approach for creating HIL test configurations in a tool-, platform-, and protocol-agnostic manner. It shows how the MDE approach can be applied in practice to derive test configurations based on the information originating from different tools in a semi-automated fashion.

The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.

Large-scale Model-Driven Engineering of web user interaction: The WebML and WebRatio experience

Nowadays, Web Applications (WAs) are complex software sys- tems, used by multiple users with different roles and often devel- oped to support and manage business processes. Due to the chang- ing nature of the supported processes, WAs need to be easily and quickly modified, to adapt and align them to the processes they support. In recent years, Model Driven Engineering (MDE) ap- proaches have been proposed and used to develop and evolveWAs. However, the definition of appropriate MDE approaches for the de- velopment of flexible process-centric WAs is still limited. In par- ticular, (flexible) workflow models have never been integrated with the models (e.g., presentation, information models) used in MDE approaches to develop this type of applications. In this paper, we present M3D (Model Driven Development with Declare), a tool for developingWAs that integrates three MDE metamodels used to represent the main components of aWA with the metamodel of De- clare, a declarative language to model business processes. The tool exploits and combines the declarative nature of Declare and the ad- vantages of MDE to get an efficient roundtrip engineering support to develop and evolve flexible process-centric WAs.

The specific requirements of developing Internet of Things (IoT) software for public transportation systems should be considered in addition to the problems always observed in IoT system development. After defining the problems encountered in the development of IoT-based public transport systems, the current model-driven engineering (MDE) approaches for IoT development are examined and their applicability for public transport systems is questioned in this paper. Several points of view are given about what new MDE approaches specific to this field should include in order to eliminate the identified deficiencies. Moreover, it is indicated that new MDE approaches should be designed including round-trip engineering to provide high mobility, use of special standards, in-vehicle communication networks and support for different system-on-chips in these public transportation systems.

Design pattern oriented development of model transformations

Since its emergence in 2009, DevOps has significantly advanced software development. Numerous studies have explored the evolution of DevOps and its related methodologies. Some of this research has investigated how model-driven engineering (MDE) can enhance the adoption and implementation of CI/CD practices, commonly known as DevOps pipelines. MDE, originating in the 1980s, offers a distinct approach to software development compared to the traditional “code is the model” mindset. This paper examines the potential synergies between MDE and DevOps, specifically reviewing existing studies on the key artifacts of DevOps pipelines. Our findings indicate that current efforts have not yet sufficiently generalized or formalized reusable transformation rules for a DevOps pipeline model and its corresponding meta-model. These elements are crucial for a successful MDE approach. Therefore, this study proposes an application of the model transformation concept to the DevOps pipeline model. Furthermore, it conceptualizes a reusable model transformation solution capable of generating both the DevOps pipeline model and its resulting code from a software architecture model. The broad research presented here identifies requirements for a potentially groundbreaking future DevOps solution.

Today's Web Applications (WAs) are complex multi-user and multi-tenant software systems, used by users with different roles and often developed to support and manage complex business processes. Due to the changing nature of such processes, WAs need to be easily and quickly modified, to be adapted and aligned to the processes they support. In recent years, Model Driven Engineering (MDE) approaches have been used to support the development and the evolution of WAs. However, the definition of appropriate MDE approaches for the development of flexible process-centric WAs is still limited. In particular, flexible workflow models have never been integrated with the models used in MDE approaches to develop this type of applications. This paper proposes an MDE approach for the development and the evolution of flexible process-centric WAs that integrates four MDE metamodels used to represent the main components of a WA with the metamodel of Declare, a declarative language to model business processes. A case study, carried out to validate the feasibility, the correctness and the effectiveness of the proposed approach is presented and discussed.

Search‐based Software Engineering stands for an important area of research which involves finding optimal solutions for software engineering problems according to a set of conflicting objectives. One of these problems is improving the software quality such as usability of user interfaces following the model‐driven engineering (MDE) paradigm. Transforming models consist of a set of transformation rules that describe how a component from a source model can be transformed into one or several target models. Although alternative target models may be equivalent from the functional viewpoint, they may differ from the non‐functional perspectives. Besides, they do not fulfil the same usability aspects. In this context, search‐based algorithms aim to identify which alternative transformation will produce a highly‐usable target model. This study addresses this issue by combining the power of model transformations engine and search‐based techniques . Specifically, the proposed approach defines model transformation as a usability optimisation problem. It allows the search of the optimal alternative transformation from a large search space taking into account a set of required usability attributes and using an evolutionary algorithm.

Defining low power design intent for a system-on-chip (SoC) consists in specifying its power management architecture and strategy according to specific low power techniques such as power gating and multi-voltage scaling requirements. Choosing the most-energy efficient power intent for a final system contributes widely to reduce its overall power consumption. At Transaction-Level, a rapid exploration of different power intent alternatives can be made. In this paper, we present a Model Driven Engineering (MDE) approach to automate low power design intent specifications and accelerate Low Power Design Intent Space Exploration (LPDISE) using a Transaction-Level power-aware design methodology. This MDE approach mainly relies on a high level abstraction of the Unified Power Format (UPF) standard concepts that fit a TLM approach use. Then, the MDE approach is applied to automatically generate a UPF code defining the most energy-efficient power intent and being a reference file for Register Transfer Level (RTL) design team. This task focuses on a smart deduction of adequate UPF commands from the high level abstraction semantics. The effectiveness of the proposed MDE approach is illustrated by an example.

Model-driven engineering (MDE) promises faster and more reliable software development processes. A key factor of MDE is the transformation of models, allowing a software engineer to use the most appropriate modeling notation for a particular task. The earlier transformations can be applied during software development, the greater the potential cost savings. To that effect, we report on the transformation of aspect-oriented models for reactive systems development, i.e., from a scenario-based requirements model into a UML-based design model. We use Aspect-oriented Use Case Maps (AoUCM) as the requirements notation and Reusable Aspect Models (RAM) as the design notation. While AoUCM is ideally suited for the specification of the system workflow comprised of interactions between the environment and the system, RAM excels in providing a design view of system structure and defining the data dimension of the system including inputs and outputs. As the more abstract AoUCM models are transformed into more concrete RAM models, MDE ensures that the AoUCM workflow specifications do not have to be modeled again in RAM, thus avoiding a duplication of effort. We present transformation algorithms to show that an AoUCM-to-RAM mapping is indeed feasible and report on initial tool support for the transformation.

The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by feedback loops. The engine often describes the adaptation by runtime models representing the adaptable software and by activities such as analysis and planning that use these models. To systematically address the interplay between runtime models and adaptation activities, runtime megamodels have been proposed. A runtime megamodel is a specific model capturing runtime models and adaptation activities. In this article, we go one step further and present an executable modeling language for ExecUtable RuntimE MegAmodels (EUREMA) that eases the development of adaptation engines by following a model-driven engineering approach. We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular feedback loops. Megamodels are kept alive at runtime and by interpreting them, they are directly executed to run feedback loops. Additionally, they can be dynamically adjusted to adapt feedback loops. Thus, EUREMA supports development by making feedback loops explicit at a higher level of abstraction and it enables solutions where multiple feedback loops interact or operate on top of each other and self-adaptation co-exists with offline adaptation for evolution.