Paper submission deadline: July 17, 2018
Some workshops may have an abstract submission deadline. Please check again at a later date.
Model-Driven Engineering (MDE) and Component-Based Software Engineering (CBSE) have been shown to effectively reduce software development complexity by (i) shifting the focus from source code to models and (ii) building software systems as composition of new and existing components. Moreover, the interplay of MDE and CBSE is gaining recognition as a very promising means to boost the development of software systems by reducing costs and risks and shorten time-to-market. In addition, most of the advancements in MDE techniques are of great interest for CBSE, and vice-versa. While several attempts to effectively combine MDE and CBSE have been documented, there are still unsolved clashes raising when exploiting this combination, mostly due to differences in their basic assumptions and focus.
The goal of ModComp’18 is to gather researchers and practitioners to share opinions, propose solutions to open challenges and generally explore the frontiers of intertwining between MDE and CBSE. ModComp’18 aims at attracting contributions related to the subject at different levels, from modelling to analysis, from componentization to composition, from consistency to versioning; foundational contributions as well as concrete applicative experiments are sought.
The complexity of adapting software during runtime has spawned interest in how models can be used to validate, monitor and adapt runtime behaviour. The use of models during runtime extends the use of modelling techniques beyond the design and implementation phases. The goal of this workshop is to look at issues related to developing appropriate model-driven approaches to managing and monitoring the execution of systems. We aim to continue the discussion of research ideas and proposals from researchers who work in relevant areas such as MDE, software architectures, reflection, and autonomic and self-adaptive systems, and provide a “state-of-the-art” research assessment expressed in terms of challenges and achievements. Although this is already the 13th edition of the workshop, the past years showed that the workshop is still well visited, has lively discussion and a good number of submissions.
Modeling started out with UML and its precursors as a graphical notation. Such visual representations enable direct intuitive capturing of reality, but they have weaknesses: for example, detailed visual representations bear the risk of becoming overcrowded faster than textual models and some of the visual features lack the level of precision required to create complete and unambiguous specifications. These weaknesses of graphical notations encouraged the development of text-based modeling languages that either integrate with or replace graphical notations for modeling. Typical examples of such languages are OCL, textual MOF, Epsilon, and Alloy. Textual modeling languages have their roots in formal language paradigms like logic, programming and databases.
The goal of this workshop is to create a forum where researchers and practitioners interested in building models using OCL or other kinds of textual languages can directly interact, report advances, share results, identify tools for language development, and discuss appropriate standards. In particular, the workshop will encourage discussions for achieving synergy from different modeling language concepts and modeling language use. The close interaction will enable researchers and practitioners to identify common interests and options for potential cooperation.
Length: full day
Over the last years, several modeling platforms have been developed to simplify and automate many steps of Model-Driven Engineering (MDE) processes. However, still several challenges have to be solved for enabling a wider adoption of MDE. One of the most important impediments in adopting MDE tools is related to the reduced flexibility of existing modeling platforms that do not permit to relax or enforce their rigidity depending on the stages of the applied development process. For instance, EMF does not permit to enter models which are not conforming to a metamodel. On one hand this allows only valid models to be defined, but on the other, it makes the corresponding pragmatics more difficult. Thus there is an increasing need for techniques supporting flexibility in a wide range of modeling activities, including metamodel, model, and model transformation development and reuse. The workshop aims at identifying the difficulties in the current practice of MDE related to the lack of flexibility, and soliciting contributions of ideas, concepts, and techniques also from other areas of software development which could be useful to revise certain MDE fundamental typing concepts, and to de ne agile model sketching techniques.
Executable models have the potential of bringing major benefits to the development of complex systems, as they provide abstractions of complex system behaviors and enable early analyses of that behavior. Despite the potential benefits of executable models, there are still many challenges to solve, such as the lack of maturity in the definition of and tooling for executable modeling languages, and the limited experience with executable modeling in much of the software and systems development industry. The objective of this workshop is to draw attention to the potentials and challenges of executable modeling and advance the state-of-the-art in executable modeling. We aim at bringing together researchers working towards overcoming challenges in executable modeling, as well as practitioners from different application domains and application contexts of executable modeling. The workshop intends to provide a forum for exchanging recent results, ideas, opinions, requirements, and experiences in executable modeling.
Collaborative modeling is gaining a growing interest in both academia and industry. However, several research challenges remain open, including scalability, support for multi-user modeling environments, model versioning, migration, comparison, merging and conflict management. Recently, scientific research contributions related to collaborative model-driven software engineering (MDSE) are emerging, each of them focusing on different and specific aspects of collaboration and modelling. Still, many of these studies are scattered across multiple research areas such as software engineering, model-driven engineering, model integrated computing, etc.
The goal of COMMitMDE 2018 is to bring together researchers and practitioners to explore (i) the impact of collaborative SE methods and principles on MDE practices and (ii) how MDE methods and techniques can support collaborative software engineering activities. Also, the workshop aims at assessing the state of the research and practice on Collaborative MDE, creating new synergies between tool vendors, researchers, and practitioners, informing the community about the new means for collaborative MDE, and identifying needs and research gaps in the collaborative MDE area.
The easy availability of high-quality tools that embed well into existing development contexts and come with effective supporting materials significantly increases the chances of adoption for any new software development approach. While there are many different significant obstacles to the development of such tools and materials, there is some evidence suggesting that the modeling community would benefit from an increased focus on the tools it produces and the support it provides to potential and actual users to compare, evaluate, and use them.
Inspired by “tool challenge and competition” workshops in other fields (e.g., [1–4]) and the success of the first offering of the workshop last year at MODELS’17 , MDETools’18 intends to provide a forum for (1) determining the state-of-the-art in MDE tools and comparative evaluations of existing tools by identifying comparison criteria, use cases, and evaluation procedures, (2) discussing the strengths, weaknesses of tools, together with opportunities for improvements, reuse, and ‘cross-fertilization’, (3) identifying relevant industrial trends, opportunities and challenges and how they can be leveraged or dealt with, (4) collecting best practices for the development, distribution, and maintenance of MDE tools and any supporting material.
To cope with complexity, modern software-intensive systems are often split in different concerns to serve the needs of diverse stakeholders. These concerns are often associated with specialized description languages and technologies, which are based on concern-specific problems and solution concepts. Developers thus face the challenging task of integrating the different languages and associated technologies used to produce software artifacts in the different concern spaces. The proposed GEMOC 2018 will be a full-day workshop bringing together researchers and practitioners in the modeling language community to discuss the challenges associated with integrating multiple, heterogeneous modeling languages. The workshop interests include techniques, frameworks, and environments to facilitate the creation, integration, and automated processing of heterogeneous modeling languages. Languages of interest range from requirements, to design and runtime languages, and include both general-purpose and domain-specific languages. Challenges related to engineering composable languages, well-formed semantic composition of languages and reasoning about systems described using heterogeneous languages are of particular interest. Following the five previous editions, the objective is to continue expanding a community focused on problems arising from the globalization of modeling languages; i.e., the use of multiple DSLs to support coordinated development of diverse aspects of a system.
With the advent of standardized hardware/software platforms for robots and the dynamics with which software ecosystems and app stores develop in application markets, the following research topics arise in the overlap of software engineering and robotics: (1) Model-driven software Development for robotic systems, (2) software and app reuse for robotics, (3) end-user app development, (4) the compliance to legal and safety constraints, and (5) total cost of ownership. Model-driven engineering helps to design, develop, and integrated complex systems by automating the development process concentrating on different levels of abstraction. With the advances in the robotic research communities and the increasing complexity of application scenarios for future robotic systems, model-driven techniques must be established to improve the quality (e.g., re-usability, reliability, maintainability) of the developed systems. Therefore, there is a need for a new paradigm of software and systems engineering for robots. This suggests establishing a new joint community of researchers from robotics and software engineering.
The number of Internet-of-Things (IoT) endpoints has been continuously increasing in the recent years and is planned to explode by 2020. In this context, it is critical to facilitate the creation and operation of IoT systems. In particular, because these systems can act on the physical world, aspects related to trustworthiness (e.g., security and privacy concerns, resilience) are challenging and of paramount importance. The goal of this workshop is to look at issues related to developing appropriate model-driven approaches to design, develop, monitor, and operate IoT systems. We aim at triggering discussions between researchers from the model-driven software development and IoT communities, as well as to promote discussions between theoreticians and practitioners.
System engineers spend a significant part of their time debugging the systems they develop, i.e., finding and fixing the cause of failures initially observed using verification and validation techniques such as testing, model checking, and simulation. While verification and validation techniques are finding their way into model-driven engineering processes and tools, locating the source of a failure (a defect) in a modelled system is still mostly a manual task. Although program debugging techniques are well-established and used in academia and industry, only a few debugging techniques and tools for models have been proposed, which are most often implemented in an ad-hoc way. Implementing such tools is complicated due to the wide variety of models and modelling languages used throughout system development. This workshop aims to bring together researchers, to contribute to the emerging field of debugging in model-driven engineering by further developing the research agenda established in the previous edition of the workshop, and by presenting new ideas, techniques, and tools.
Models are purposeful abstractions of systems and their environments. They can be used to understand, simulate, and validate complex systems at different abstraction levels. Thus, the use of models is of increasing importance for industrial applications. Model-Driven Engineering (MDE) is a development methodology that is based on models, metamodels, and model transformations. The shift from code-centric software development to model-centric software development in MDE opens up promising opportunities for the verification and validation (V&V) of software. On the other hand, the growing complexity of models and model transformations requires efficient V&V techniques in the context of MDE.
The workshop on Model Driven Engineering, Verification and Validation (MoDeVVa) offers a forum for researchers and practitioners who are working on V&V and MDE. The main goals of the workshop are to identify, investigate, and discuss mutual impacts of MDE and V&V.
For the 2018 edition of the MoDeVVa workshop we would like to propose an emphasis on usability, user friendliness and approaches, tools and techniques that enable the applicability of V&V in MDE as well as the use of MDE in V&V activities. We would additionally like to invite submissions where machine learning is used as an enabler to ease the usage and applicability in practice of modeling and verification techniques.
Software engineering research must always be solidly rooted in industrial needs. Such needs must be given a medium to be clearly communicated between industry and research. Otherwise, research becomes untethered while the industry’s needs are not met. The objective of the PAINS workshop is to bring together people from industry and the research community to discuss concrete pains, issues and challenges faced in the industrial practice of MDE.
Previous approaches to eliciting MDE requirements often brought forth academic perspectives. With a unique focus on the needs of industrial practitioners, the PAINS workshop aims to close the gap between industrial requirements in model-driven engineering and academic solutions. To achieve this, we propose a workshop format of short presentations of industrial pains, followed by problem-specific or domain-specific breakout sessions better accessible to industrial practitioners.
Software artefacts constantly increase in complexity, variety and novelty. Environment and business constraints, user requirements and new insights put additional pressure on their adaptability, availability, reliability and quality: they continuously need to be up to date. But evolution issues are critical, complex and costly to manage. They concern requirements, architecture, design, source code, documentation, integration or deployment. They also typically affect various kinds of models (data, behavioural, domain, source code or goal models). Addressing and managing these varieties of changes is essential. Models and meta-models, the cornerstone of complex software systems’ abstractions, represent a powerful mean for facing software evolution challenges by ensuring a more abstract and expressive modeling of software evolution. They can help and guide software evolution and can enforce and reduce critical risks and important involved resources. The workshop puts the focus on Models and Evolution by considering two main sides: (1) Managing software evolution needs by relying on the high-level abstraction power of models and meta-models. (2) Managing model and metamodel evolution needs and the co-evolution of all related software artefacts by putting attention to their increasing evolution issues as they become primary artefacts.
MULTI 2018 is the fifth workshop in the MULTI workshop series focusing on multi-level modeling. Although multi-level modelling approaches have been successfully used in industrial projects and standards definitions there is still no clear consensus on precisely what multi-level modelling is and how it can be best supported. For example, there are different views on whether it is sound to combine instance facets and type facets into so-called clabjects, whether strict metamodeling is too restrictive and what tool architectures provide the best framework for supporting modeling with multiple-classification levels. The goal of this workshop is to build on the success of the previous MULTI workshops at MODELS 2014, 2015, 2016, and 2017, and provide a forum for researchers and practitioners to discuss advances in this field.
Modeling is an intrinsically human endeavour. Therefore, many of the questions related to modeling can only be answered by empirical studies of human factors and activities. Yet, empirical research with human subjects is not in the mainstream of major scienti c events in the eld of modeling. The HuFaMo-workshop was created in 2015 to promote this form of research by creating a venue where these topics can be discussed and disseminated. For that purpose, HuFaMo invites both reports of completed research and proposals of study designs. We encourage the sharing of experience and invite new researchers into the eld of human factors in modeling. Thanks to the different editions of the workshop, a community of researchers and practitioners began to form to broaden the foothold of human factors research in the MDE community. With the 2018 edition, we intend to strengthen this community. While maintaining the principle of sharing experience through reports and proposals, we will focus on starting up a replicated experiment in order to promote a collaborative e ort of the participants.
Model-based approaches promote the use of models and related artefacts (such as metamodels and model transformations) as central elements to tackle the complexity of building systems. Both in academia and in industry there is a growing need to efficiently i) store; ii) analyse; and ii) search & navigate, and iii) curate large collections of models. Such collections include for example large sets of software models such as the Lindholmen UML dataset, or of heterogeneous models in large MDE ecosystems and systems-of-systems, including e.g. software, hardware, and business models.
The workshop Analytics and Mining of Model Repositories (AMMoRe) aims to gather modelling researchers and practitioners to discuss the emerging problems and propose solutions. The scope ranges from industrial reports and empirical analyses in the problem domain to novel cross-disciplinary approaches for large-scale analytics and management, e.g. exploiting techniques from data analytics, repository mining and machine learning.