Special Issue "The Future of Model-Driven Software Engineering"

A special issue of Software (ISSN 2674-113X).

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 2395

Special Issue Editors

Department of Management, Information and Production Engineering, University of Bergamo, Bergamo, Italy
Interests: formal methods; model-driven engineering; medical software certification; quality of medical software; robustness evaluation of NN
Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L'Aquila, Italy
Interests: Model-Driven Engineering; domain-specific modelling languages; model transformation; model differencing; modelling repositories; mining software repositories and communities

Special Issue Information

Dear Colleagues,

Model-driven engineering is a discipline that aims at abstracting and automating software development activities that support programmers through the entire development lifecycle. Nowadays, model-driven software systems have become common, and in addition, the application of machine learning (ML) algorithms within MDE has experienced moderate growth and is now rapidly increasing. At the same time, due to the complexity of AI systems, MDE techniques have been successfully applied to assist in the design of AI artifacts and systems.

In such a context, MDE will have to interact more and more frequently with AI techniques. In conclusion, we would like to investigate how this interaction is possible, how AI technologies improve the MDE development paradigm, and how MDE supports the development of AI systems.

Because the spread of adopting MDE techniques depends on the availability and reliability of tools, the development of such tools to support modeling activities has been an integral part of MDE research activities. In such a context, we are interested in understanding how the support of modeling tools facilities the adoption of MDE technologies. Moreover, we would like to understand the main challenges and obstacles for generating robust and reliable tools to support MDE activities.

Dr. Silvia Bonfanti
Dr. Juri Di Rocco
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Software is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • model-driven engineering
  • machine learning
  • artificial intelligence
  • MDE tools
  • modeling

Published Papers (1 paper)

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Evaluation of Compliance Rule Languages for Modelling Regulatory Compliance Requirements
Software 2023, 2(1), 71-120; https://doi.org/10.3390/software2010004 - 28 Jan 2023
Viewed by 1506
Compliance in business processes has become a fundamental requirement given the constant rise in regulatory requirements and competitive pressures that have emerged in recent decades. While in other areas of business process modelling and execution, considerable progress towards automation has been made (e.g., [...] Read more.
Compliance in business processes has become a fundamental requirement given the constant rise in regulatory requirements and competitive pressures that have emerged in recent decades. While in other areas of business process modelling and execution, considerable progress towards automation has been made (e.g., process discovery, executable process models), the interpretation and implementation of compliance requirements is still a highly complex task requiring human effort and time. To increase the level of “mechanization” when implementing regulations in business processes, compliance research seeks to formalize compliance requirements. Formal representations of compliance requirements should, then, be leveraged to design correct process models and, ideally, would also serve for the automated detection of violations. To formally specify compliance requirements, however, multiple process perspectives, such as control flow, data, time and resources, have to be considered. This leads to the challenge of representing such complex constraints which affect different process perspectives. To this end, current approaches in business process compliance make use of a varied set of languages. However, every approach has been devised based on different assumptions and motivating scenarios. In addition, these languages and their presentation usually abstract from real-world requirements which often would imply introducing a substantial amount of domain knowledge and interpretation, thus hampering the evaluation of their expressiveness. This is a serious problem, since comparisons of different formal languages based on real-world compliance requirements are lacking, meaning that users of such languages are not able to make informed decisions about which language to choose. To close this gap and to establish a uniform evaluation basis, we introduce a running example for evaluating the expressiveness and complexity of compliance rule languages. For language selection, we conducted a literature review. Next, we briefly introduce and demonstrate the languages’ grammars and vocabularies based on the representation of a number of legal requirements. In doing so, we pay attention to semantic subtleties which we evaluate by adopting a normative classification framework which differentiates between different deontic assignments. Finally, on top of that, we apply Halstead’s well-known metrics for calculating the relevant characteristics of the different languages in our comparison, such as the volume, difficulty and effort for each language. With this, we are finally able to better understand the lexical complexity of the languages in relation to their expressiveness. In sum, we provide a systematic comparison of different compliance rule languages based on real-world compliance requirements which may inform future users and developers of these languages. Finally, we advocate for a more user-aware development of compliance languages which should consider a trade off between expressiveness, complexity and usability. Full article
(This article belongs to the Special Issue The Future of Model-Driven Software Engineering)
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