VirtualEMF: a Model Virtualization Tool

International audienceSpecification of complex systems involves several heterogeneous and interrelated models. Model composition is a crucial (and complex) modeling activity that allows combining different system perspectives into a single cross-domain view. Current composition solutions fail to fully address the problem, presenting important limitations concerning efficiency, interoperability, and/or synchronization. To cope with these issues, in this demo we introduce VirtualEMF: a model composition tool based on the concept of a virtual model, i.e., a model that do not hold concrete data, but that redirects all its model manipulation operations to the set of base models from which it was generated

Example-based Validation of Domain-Specific Visual Languages

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SLE 2015: Proceedings of the 2015 ACM SIGPLAN International Conference on Software Language Engineering, http://dx.doi.org/10.1145/10.1145/2814251.2814256The definition of Domain-Specific Languages (DSLs) is a recurrent activity in Model-Driven Engineering. However, their construction is many times an ad-hoc process, partly due to the lack of tools enabling a proper engineering of DSLs and promoting domain experts to play an active role. The focus of this paper is on the validation of meta- models for visual DSLs. For this purpose, we propose a language and tool support for describing properties that in- stances of meta-models should (or should not) meet. Then, our system uses a model finder to produce example models, enriched with a graphical concrete syntax, that confirm or refute the assumptions of the meta-model developer. Our language complements metaBest, a framework for the validation and verification of meta-models that includes two other languages for unit testing and specification-based test- ing of meta-models. A salient feature of our approach is that it fosters interaction with domain experts by the use, process- ing and creation of informal drawings constructed in editors liked yED or Dia. We assess the usefulness of the approach in the validation of a DSL for house blueprints, with the par- ticipation of 26 4th year computer science students.Work supported by the Spanish MINECO (TIN2011-24139 and TIN2014-52129-R), the R&D programme of the Madrid Region (S2013/ICE-3006), and the EU commission (FP7-ICT-2013-10, #611125)

Eugenia:towards disciplined and automated development of GMF-based graphical model editors

EMF and GMF are powerful frameworks for implementing tool support for modelling languages in Eclipse. However, with power comes complexity, implementing a graphical editor for a modelling language using EMF and GMF requires developers to handcraft and maintain several detailed interconnected models through a loosely guided, labour-intensive, and error-prone process. We demonstrate how the application of metamodel annotation and model transformation techniques can help to manage the complexity of GMF and EMF and deliver significant productivity, quality, and maintainability benefits. We present Eugenia, an open-source tool that implements the proposed approach, illustrate its functionality with an example, evaluate it through an empirical study, and report on the community’s response to the tool

Type inference in flexible model-driven engineering using classification algorithms

Flexible or bottom-up model-driven engineering (MDE) is an emerging approach to domain and systems modelling. Domain experts, who have detailed domain knowledge, typically lack the technical expertise to transfer this knowledge using traditional MDE tools. Flexible MDE approaches tackle this challenge by promoting the use of simple drawing tools to increase the involvement of domain experts in the language definition process. In such approaches, no metamodel is created upfront, but instead the process starts with the definition of example models that will be used to infer the metamodel. Pre-defined metamodels created by MDE experts may miss important concepts of the domain and thus restrict their expressiveness. However, the lack of a metamodel, that encodes the semantics of conforming models has some drawbacks, among others that of having models with elements that are unintentionally left untyped. In this paper, we propose the use of classification algorithms to help with the inference of such untyped elements. We evaluate the proposed approach in a number of random generated example models from various domains. The correct type prediction varies from 23 to 100% depending on the domain, the proportion of elements that were left untyped and the prediction algorithm used

Progression of chronic pain and associated health-related quality of life and healthcare resource use over 5 years after total knee replacement: evidence from a cohort study

Objective As part of the STAR Programme, a comprehensive study exploring long-term pain after surgery, we investigated how pain and function, health-related quality of life (HRQL), and healthcare resource use evolved over 5 years after total knee replacement (TKR) for those with and without chronic pain 1 year after their primary surgery. Methods We used data from the Clinical Outcomes in Arthroplasty Study prospective cohort study, which followed patients undergoing TKR from two English hospitals for 5 years. Chronic pain was defined using the Oxford Knee Score Pain Subscale (OKS-PS) where participants reporting a score of 14 or lower were classified as having chronic pain 1-year postsurgery. Pain and function were measured with the OKS, HRQL using the EuroQoL-5 Dimension, resource use from yearly questionnaires, and costs estimated from a healthcare system perspective. We analysed the changes in OKS-PS, HRQL and resource use over a 5-year follow-up period. Multiple imputation accounted for missing data. Results Chronic pain was reported in 70/552 operated knees (12.7%) 1 year after surgery. The chronic pain group had worse pain, function and HRQL presurgery and postsurgery than the non-chronic pain group. Those without chronic pain markedly improved right after surgery, then plateaued. Those with chronic pain improved slowly but steadily. Participants with chronic pain reported greater healthcare resource use and costs than those without, especially 1 year after surgery, and mostly from hospital readmissions. 64.7% of those in chronic pain recovered during the following 4 years, while 30.9% fluctuated in and out of chronic pain. Conclusion Although TKR is often highly beneficial, some patients experienced chronic pain postsurgery. Although many fluctuated in their pain levels and most recovered over time, identifying people most likely to have chronic pain and supporting their recovery would benefit patients and healthcare systems

Requirements for modelling tools for teaching

Modelling is an important activity in software development and it is essential that students learn the relevant skills. Modelling relies on dedicated tools and these can be complex to install, configure, and use—distracting students from learning key modelling concepts and creating accidental complexity for teachers. To address these challenges, we believe that modelling tools specifically aimed at use in teaching are required. Based on discussions at a working session organised at MODELS 2023 and the results from an internationally shared questionnaire, we report on requirements for such modelling tools for teaching. We also present examples of existing modelling tools for teaching and how they address some of the requirements identified

OSSMETER: Automated measurement and analysis of open source software

International audienceDeciding whether an open source software (OSS) meets the requiredstandards for adoption in terms of quality, maturity, activity of development anduser support is not a straightforward process. It involves analysing various sourcesof information, including the project’s source code repositories, communicationchannels, and bug tracking systems. OSSMETER extends state-of-the-art techniquesin the field of automated analysis and measurement of open-source software(OSS), and develops a platform that supports decision makers in the processof discovering, comparing, assessing and monitoring the health, quality, impactand activity of opensource software. To achieve this, OSSMETER computestrustworthy quality indicators by performing advanced analysis and integrationof information from diverse sources including the project metadata, source coderepositories, communication channels and bug tracking systems of OSS projects

TRIM33 switches off Ifnb1 gene transcription during the late phase of macrophage activation

Despite its importance during viral or bacterial infections, transcriptional regulation of the interferon-β gene (Ifnb1) in activated macrophages is only partially understood. Here we report that TRIM33 deficiency results in high, sustained expression of Ifnb1 at late stages of toll-like receptor-mediated activation in macrophages but not in fibroblasts. In macrophages, TRIM33 is recruited by PU.1 to a conserved region, the Ifnb1 Control Element (ICE), located 15 kb upstream of the Ifnb1 transcription start site. ICE constitutively interacts with Ifnb1 through a TRIM33-independent chromatin loop. At late phases of lipopolysaccharide activation of macrophages, TRIM33 is bound to ICE, regulates Ifnb1 enhanceosome loading, controls Ifnb1 chromatin structure and represses Ifnb1 gene transcription by preventing recruitment of CBP/p300. These results characterize a previously unknown mechanism of macrophage-specific regulation of Ifnb1 transcription whereby TRIM33 is critical for Ifnb1 gene transcription shutdown