Papers by Hugo Bruneliere
SAC '25: Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing, 2025
Fog Computing consists in decentralizing the Cloud by geographically distributing computation, st... more Fog Computing consists in decentralizing the Cloud by geographically distributing computation, storage, network resources, and related services. Among other benefits, it allows reducing bandwidth usage, limiting latency, or minimizing data transfers. However, Fog systems engineering remains challenging and quite often error-prone. Following best practices in software engineering, verification tasks can be performed before such systems are concretely deployed. Works already exist on verifying non-functional properties of Fog systems at different previous steps of the life cycle. This paper goes one step further and presents the VeriFogOps approach. This approach allows to automatically select deployment tools, based on expressed Quality of Service (QoS) requirements, and then generate relevant CI/CD pipelines supporting the deployment of Fog systems. We implemented and validated our approach via two realistic use cases, considering different QoS solutions and deployment tools. This work, developed in direct collaboration with our industrial partner Smile, goes towards the direction of a more comprehensive support for the entire life cycle of Fog systems, from design to actual deployment and execution.
Fog Computing is a paradigm decentralizing the Cloud by geographically distributing computation, ... more Fog Computing is a paradigm decentralizing the Cloud by geographically distributing computation, storage, network resources and related services. It provides benefits such as reducing the number of bottlenecks, limiting unwanted data movements, etc. However, managing the size, complexity and heterogeneity of the Fog systems to be engineered is challenging and can quickly become costly. According to best practices in software engineering, verification tasks could be performed on a system design prior to its implementation and deployment. We propose a generic model-based approach for verifying Fog systems at design time, also enabling the automatic generation of corresponding deployment configuration files. Named VeriFog, this approach is notably based on a customizable Fog Modeling Language (FML). We experimented in practice by modeling three use cases, from three different application domains, and by considering three main types of non-functional properties to be verified. From this modeling and verification effort, we show that we are able to automatically generate usable deployment configuration files for different deployment tools. In direct collaboration with our industrial partner Smile, the approach and underlying language presented in this paper are necessary steps towards a more global model-based support for the complete life cycle of Fog systems.
17th ACM SIGPLAN International Conference on Software Language Engineering (SLE’24), 2024
In the Model-Driven Engineering (MDE) of complex systems, multiple models represent various syste... more In the Model-Driven Engineering (MDE) of complex systems, multiple models represent various systems' aspects. In practice, these models are often unconnected and specified using different modeling languages. Model view solutions can be employed to automatically combine such models. However, writing model view definitions is not trivial. When modeling languages are semantically distant and/or have a large number of concepts, it can quickly become difficult to manually identify the language elements to be selected, associated, or queried to build a model view. As a solution, this paper proposes an in-context Large Language Model (LLM)-based approach to assist engineers in writing model-view definitions. Notably, we rely on LLMs and Prompt Engineering techniques to automatically generate drafts of model-view definitions by providing as input only minimal information on the modeling languages to be combined. We implemented our approach by integrating the EMF Views solution for model views with the LangChain framework for LLM-based applications. To this end, we tailored LangChain to handle EMF metamodels. We validated our approach and implementation on a set of model views originally specified either in VPDL, the ViewPoint Definition Language of EMF Views, or as ATL model-to-model transformations. We compared these original model view definitions with the ones we automatically generated. The obtained results show the feasibility and applicability of our approach.
The increasing complexity of modern systems poses numerous challenges at all stages of system dev... more The increasing complexity of modern systems poses numerous challenges at all stages of system development and operation. Continuous software and system engineering processes, e.g., DevOps, are increasingly adopted and spread across organizations. In parallel, many leading companies have begun to apply artificial intelligence (AI) principles and techniques, including Machine Learning (ML), to improve their products. However, there is no holistic approach that can support and enhance the growing challenges of DevOps. In this paper, we propose a software architecture that provides the foundations of a model-based framework for the development of AI-augmented solutions incorporating methods and tools for continuous software and system engineering and validation. The key characteristic of the proposed architecture is that it allows leveraging the advantages of both AI/ML and Model Driven Engineering (MDE) approaches and techniques in a DevOps context. This architecture has been designed, developed and applied in the context of the European large collaborative project named AIDOaRt. In this paper, we also report on the practical evaluation of this architecture. This evaluation is based on a significant set of technical solutions implemented and applied in the context of different real industrial case studies coming from the AIDOaRt project. Moreover, we analyse the collected results and discuss them according to both architectural and technical challenges we intend to tackle with the proposed architecture.
32nd International Conference on Information Systems Development (ISD 2024), 2024
Business-IT alignment (BITA) remains a challenging topic for enterprise architects, and especiall... more Business-IT alignment (BITA) remains a challenging topic for enterprise architects, and especially operational BITA that focus on the alignment between business processes and IT applications. A major challenge is determining the level of alignment between these Business and IT layers. Some approaches propose to assess this alignment, but they are often context-specific. Moreover, no approach intends to combine various assessment means for a more in-depth alignment evaluation. Thus, we propose an alignment assessment approach combining different means (metrics, consistency rules, anti-patterns). We also provide a methodology that integrates this approach by relying on an established cartography expressing the current state of alignment. This cartography is composed of Business and IT models, and of explicit links between them. The proposed methodology and assessment approach are illustrated on the SoftSlate case study, an open-source Java E-commerce solution. In the reported experiment, we considered four metrics, two consistency rules, and four anti-patterns.
INFormatique des ORganisations et Systèmes d'Information et de Décision (INFORSID 2024), 2024
Les systèmes d'information ont pour rôle de contribuer à l'efficacité des organisations. L'aligne... more Les systèmes d'information ont pour rôle de contribuer à l'efficacité des organisations. L'alignement opérationnel des applications avec le métier est un élément clé de la cohérence de ces systèmes. Dans cet article, nous nous intéressons à la détection de potentielles incohérences dans l'alignement entre le métier, plus précisément des processus métier, et les applications qui les implémentent. Nous proposons de détecter de manière automatisée des anti-patrons d'alignement publiés dans la littérature à travers des règles de détection. L'approche est implantée en Archimate dans l'outil Archi et avec le langage de script jArchi. Nous illustrons la démarche complète d'alignement sur l'exemple SoftSlate, un progiciel d'eCommerce. L'ensemble constitue une proposition outillée qui peut être appliquée dans d'autres contextes.
The Journal of Object Technology (JOT) - Special Issue "The 20th European Conference on Modelling Foundations and Applications (ECMFA 2024)", Jul 2024
Model-driven engineering (MDE) supports the engineering of complex systems via multiple models re... more Model-driven engineering (MDE) supports the engineering of complex systems via multiple models representing various aspects of the system. These interrelated models are usually heterogeneous and specified using complementary modeling languages. Thus, model-view solutions can be employed to federate these models more transparently. Inter-model links in model views can sometimes be automatically computed via explicitly written matching rules. However, in some cases, matching rules would be too complex (or even impossible) to write, but inter-model links may be inferred by analyzing previous examples instead. In this paper, we propose a Machine Learning (ML)-backed approach for expressing and computing such model views. Notably, we aim at making the use of ML in this context as simple as possible. To this end, we refined and extended the ViewPoint Definition Language (VPDL) from the EMF Views model-view solution to integrate the use of dedicated Heterogeneous Graph Neural Networks (HGNNs). These view-specific HGNNs are trained with appropriate sets of contributing models before being used for inferring links to be added to the views. We validated our approach by implementing a prototype combining EMF Views with PyEcore and PyTorch Geometric. Our experiments show promising results regarding the ease-of-use of our approach and the relevance of the inferred inter-model links.
26th International Conference on Enterprise Information Systems (ICEIS 2024), 2024
Business-IT Alignment (BITA) is an important mean of evaluating the performance of IT systems ope... more Business-IT Alignment (BITA) is an important mean of evaluating the performance of IT systems operating within a business organisation. The software architects' need for representing, analysing and interpreting the alignment situations remains among the main challenges. Despite different initiatives in the last two decades, available solutions remain too diverse and limited. As a consequence, more methodological guidelines are still needed to improve the support for BITA. In this paper, we address Core Operational BITA (COBITA) as a subset of BITA which targets the operational integration of business and application artefacts. To this end, we first propose two types of COBITA links between the business layer and the application one. We propose then an approach for establishing these links and evaluating them. The objective is to provide indicators for domain experts and software architects to assess the quality of the alignement between the two layers. We decided to choose Archimate, a standard language, to model the business and application layers. Then, we specify the two types of COBITA links to establish a mapping between the business and applications layers. Finally, we rely on the obtained cartography to evaluate the alignment via a set of proposed metrics and consistency rules. An initial version of the approach has been implemented in the Archi tool, and we experimented with it on the SoftSlate system.
The 18th Annual IEEE International Systems Conference (SYSCON 2024), 2024
Designing modern Cyber-Physical Systems (CPSs) is posing new challenges to both industrial practi... more Designing modern Cyber-Physical Systems (CPSs) is posing new challenges to both industrial practitioners and academics. In this context, adopting cutting-edge paradigms, such as Model-Based Systems Engineering (MBSE), DevOps, and Artificial Intelligence (AI), can offer new opportunities for improving CPS design automation. While such paradigms are already jointly used in the research community to support system design activities, there is a need to fill the gap between academia and industrial practitioners. Indeed, system specification is still mainly performed manually in many industrial projects. In this paper, we present a collaboration between industrial and academic partners of the AIDOaRt European project towards a model-based approach for CPS engineering applied in one of the project use cases. We identify key challenges and corresponding solutions to enhance the automation of CPS design processes. Notably, we consider a combination of prescriptive modeling, model transformations, model views, modeling process mining, and AIbased modeling recommendations. As an initial evaluation, the proposed approach is applied to a practical industrial case study.
ACM/IEEE 26th International Conference on Model-Driven Engineering Languages and Systems (MODELS 2023), 2023
The Doctoral Symposium of the ACM/IEEE 26th International Conference on Model Driven Engineering ... more The Doctoral Symposium of the ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS 2023) was held in Västerås, Sweden, on October 3, 2023. The symposium aims to provide an international forum for doctoral students to interact with their fellow students and faculty mentors working in research areas relevant to MODELS. Most importantly, the symposium provides doctoral students with constructive feedback about their studies and research works. This is ensured by the attendance of prominent experts in the field as mentors, in addition to the peer-review process.
SAC '24: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024
Model-driven engineering (MDE) supports the engineering of complex systems via multiple models re... more Model-driven engineering (MDE) supports the engineering of complex systems via multiple models representing various systems' aspects. These interrelated models are usually heterogeneous and often specified using complementary modeling languages. Whenever needed, model view solutions can be employed to federate these models in a more transparent way. To do so, the required inter-model links can sometimes be automatically computed via explicitly written matching rules. However, in some cases, matching rules would be too complex (or even impossible) to write. Thus, some inter-model links may be inferred by analyzing previous examples instead. In this paper, we introduce a Machine Learning (ML)backed approach for expressing and computing such model views. Notably, we aim at making the use of ML as simple as possible in this context. To this end, we propose to refine and extend the ViewPoint Definition Language (VPDL) from the EMF Views model view solution to integrate the use of dedicated Heterogeneous Graph Neural Networks (HGNNs). These view-specific HGNNs can be trained with appropriate sets of contributing models before being used for inferring links to be added to the views.
SAC '24: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024
Fog Computing is a paradigm aiming to decentralize the Cloud by geographically distributing away ... more Fog Computing is a paradigm aiming to decentralize the Cloud by geographically distributing away computation, storage, network resources and related services. It provides several benefits such as reducing the number of bottlenecks, limiting unwanted data movements, etc. However, managing the size, complexity and heterogeneity of Fog systems to be designed, developed, tested, deployed, and maintained, is challenging and can quickly become costly. According to best practices in software engineering, verification tasks could be performed on system design prior to its actual implementation and deployment. Thus, we propose a generic model-based approach for verifying Fog systems at design time. Named VeriFog, this approach is notably based on a customizable Fog Modeling Language (FML). We experimented with our approach in practice by modeling three use cases, from three different application domains, and by considering three main types of non-functional properties to be verified. In direct collaboration with our industrial partner Smile, the approach and underlying language presented in this paper are necessary steps towards a more global model-based support for the complete life cycle of Fog systems.
In this paper, we report on our 7 years of practical experience designing, developing, deploying,... more In this paper, we report on our 7 years of practical experience designing, developing, deploying, using, and evolving an iterative Model-based Requirements Engineering (MBRE) approach and language in the context of five large European collaborative projects providing complex software-intensive solutions. Based on significant data sets collected both during project execution and via surveys realized afterward, we demonstrate that such a model-based approach can bring interesting benefits in terms of scalability (e.g., a large number of handled requirements), heterogeneity (e.g., partners with different types of RE background), adaptability and extensibility (e.g., to various project's needs), traceability (e.g., from the requirements to the software components), automation (e.g., documentation generation), consistency and quality (e.g., central model), and usefulness or usability (e.g., actual deployment and practical use). Along the way, we illustrate the application of our MBRE approach and language with concrete elements from these several European collaborative projects. More broadly, we discuss the general benefits and current limitations of using such a model-based approach and corresponding language, as well as the related lessons we learned during these past years.
31st International Conference on Information Systems Development (ISD 2023), 2023
In terms of competitiveness, Business-IT Alignment (BITA) is still a crucial challenge for busine... more In terms of competitiveness, Business-IT Alignment (BITA) is still a crucial challenge for business leaders and CIOs, especially in the context of Digital Transformation and time-to-market challenges. Core Operational BITA can be seen as a projection of BITA to the Enterprise Information System perimeter, i.e., the operational alignment between the business processes and supporting IT. It is a major source of issues (e.g., strong couplings, maintenance costs, technical debt, slow adaptation). These cause a misalignment and thus contribute to the well-known Business-IT Gap. In this paper, we review the current state of this operational alignment in the context of Enterprise Architecture (EA) i.e. between the Business Process layer and the Application layer. Our analysis focuses on the models used at the Business Process and Application layers, the existing or potential links between these layers, and the use of these links to carry out a core operational alignment and facilitate the detection of potential divergence points. As a result, we notably outline some current limitations, such as modelling disparities, misuse of links between the two layers and an under-coverage of real alignment processes. We also discuss some lessons learned and future challenges, mainly around modelling needs and consistency management between the two considered layers.
18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2023), 2023
Fog Computing is a paradigm aiming to decentralize the Cloud by geographically distributing away ... more Fog Computing is a paradigm aiming to decentralize the Cloud by geographically distributing away computation, storage and network resources as well as related services. This notably reduces bottlenecks and data movement. However, managing Fog resources is a major challenge because the targeted systems are large, geographically distributed, unreliable and very dynamic. Cloud systems are generally managed via centralized autonomic controllers automatically optimizing both application QoS and resource usage. To leverage the self-management of Fog resources, we propose to orchestrate a fleet of autonomic controllers in a decentralized manner, each with a local view of its own resources. In this paper, we present our SeMaFoR (Self-Management of Fog Resources) vision that aims at collaboratively operating Fog resources. SeMaFoR is a generic approach made of three cornerstones: an Architecture Description Language for the Fog, a collaborative and consensual decision-making process, and an automatic coordination mechanism for reconfiguration.
Microprocessors and Microsystems: Embedded Hardware Design, 2022
The advent of complex Cyber-Physical Systems (CPSs) creates the need for more efficient engineeri... more The advent of complex Cyber-Physical Systems (CPSs) creates the need for more efficient engineering processes. Recently, DevOps promoted the idea of considering a closer continuous integration between system development (including its design) and operational deployment. Despite their use being still currently limited, Artificial Intelligence (AI) techniques are suitable candidates for improving such system engineering activities (cf. AIOps). In this context, AIDOaRT is a large European collaborative project that aims at providing AI-augmented automation capabilities to better support the modelling, coding, testing, monitoring, and continuous development of CPSs. The project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable CPSs. The resulting framework will 1) enable the dynamic observation and analysis of system data collected at both runtime and design time and 2) provide dedicated AI-augmented solutions that will then be validated in concrete industrial cases. This paper describes the main research objectives and underlying paradigms of the AIDOaRt project. It also introduces the conceptual architecture and proposed approach of the AIDOaRt overall solution. Finally, it reports on the actual project practices and discusses the current results and future plans.
Future Generation Computer Systems, Jan 1, 2023
Fog Computing is a new paradigm aiming at decentralizing the Cloud by geographically distributing... more Fog Computing is a new paradigm aiming at decentralizing the Cloud by geographically distributing away computation, storage and network resources as well as related services. In order to design, develop, deploy, maintain and evolve Fog systems, languages are required for properly modeling both their entities (e.g., infrastructures, topologies, resources configurations) and their specific features such as the locality concept, QoS constraints applied on resources (e.g., energy, data privacy, latency) and their dependencies, the dynamicity of considered workloads, the heterogeneity of both applications and devices, etc. This paper provides a detailed overview of the current state-of-the-art in terms of Fog modeling languages. We relied on our long-term experience in Cloud Computing and Cloud Modeling to contribute a feature model describing what we believe to be the most important characteristics of Fog modeling languages. We also performed a systematic scientific literature search and selection process to obtain a list of already existing Fog modeling languages. Then, we evaluated and compared these Fog modeling languages according to the characteristics expressed in our feature model. As a result, we discuss in this paper the main capabilities of these Fog modeling languages and propose a corresponding set of open research challenges in this area. We expect the presented work to be helpful to both current and future researchers or engineers working on/with Fog systems, as well as to anybody genuinely interested in Fog Computing or more generally in distributed systems.
The paper presents the AIDOaRT project, a 3 years long H2020-ECSEL European project involving 32 ... more The paper presents the AIDOaRT project, a 3 years long H2020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in Cyber-Physical Systems (CPS). To this end, the project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable and reliable CPSs. This paper introduces the AIDOaRt project, its overall objectives, and used requirement engineering methodology. Based on that, it also focuses on describing the current plan regarding a set of tools intended to cover the modelbased capabilities requirements from the project.
40ème Congrès INFORSID (INFormatique des ORganisations et Systèmes d'Information et de Décision) 2022, 2022
Ce papier rapporte notre expérience pratique de proposition et d'application d'une approche et d'... more Ce papier rapporte notre expérience pratique de proposition et d'application d'une approche et d'un langage d'Ingénierie des Exigences basées sur les Modèles. La période concernée de 5 ans couvre trois grands projets collaboratifs européens, chacun d'entre eux fournissant diverses solutions logicielles complexes (e.g., frameworks, ensemble d'outils intégrés, etc.).
IFIP Conference on Advances in Production Management Systems (APMS 2021), 2021
Cyber-Physical Systems (CPS) are complex physical systems interacting with a considerable number ... more Cyber-Physical Systems (CPS) are complex physical systems interacting with a considerable number of distributed computing elements for monitoring, control and management. They are currently becoming larger as Cyber-Physical Systems of Systems (CPSoS), since many industrial companies are transitioning their complex systems of systems to software-intensive solutions in different domains such as production or manufacturing. Following the development and dissemination of DevOps approaches in the Software Engineering world, we propose the Twin-Driven Engineering (TDE) paradigm as a way to upgrade the role of Digital Twins (DT) to become a central point in all the engineering activities on the CPSoS, from design to decommissioning. Since CPSoS can be highly heterogeneous, we rather target the support for producing and maintaining a single integrated virtual representation of the CPSoS (i.e. a System of Twins) on which it is possible to perform global reasoning, analysis and verification. However, such a new paradigm comes with several open research challenges. We provide an overview of the state-of-the-art in key areas related to TDE. We identify under-investigated problems in related work and outline corresponding research directions.
Uploads
Papers by Hugo Bruneliere