Recommender systems in model-driven engineering: A systematic mapping review

Recommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms. They are also increasingly being applied to facilitate software engineering activities. Following this trend, we are witnessing a growing research interest on recommendation approaches that assist with modelling tasks and model-based development processes. In this paper, we report on a systematic mapping review (based on the analysis of 66 papers) that classifies the existing research work on recommender systems for model-driven engineering (MDE). This study aims to serve as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods, and the open challenges and opportunities in this field of researchThis work has been funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 813884 (Lowcomote [134]), by the Spanish Ministry of Science (projects MASSIVE, RTI2018-095255-B-I00, and FIT, PID2019-108965GB-I00) and by the R&D programme of Madrid (Project FORTE, P2018/TCS-431

Automating the synthesis of recommender systems for modelling languages

We are witnessing an increasing interest in building recommender systems (RSs) for all sorts of Software Engineering activities. Modelling is no exception to this trend, as modelling environments are being enriched with RSs that help building models by providing recommendations based on previous solutions to similar problems in the same domain. However, building a RS from scratch requires considerable effort and specialized knowledge. To alleviate this problem, we propose an automated approach to the generation of RSs for modelling languages. Our approach is model-based, and we provide a domain-specific language called Droid to configure every aspect of the RS (like the type and features of the recommended items, the recommendation method, and the evaluation metrics). The RS so configured can be deployed as a service, and we offer out-of-the-box integration of this service with the EMF tree editor. To assess the usefulness of our proposal, we present a case study on the integration of a generated RS with a modelling chatbot, and report on an offline experiment measuring the precision and completeness of the recommendationsThis project has received funding from the EU Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813884, the Spanish Ministry of Science (RTI2018-095255-B-I00) and the R&D programme of Madrid (P2018/TCS-4314

Building recommenders for modelling languages with Droid

© ACM 2022. 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 ASE '22: Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, http://dx.doi.org/10.1145/3551349.3559521Recommender systems (RSs) are increasingly being used to help in all sorts of software engineering tasks, including modelling. However, building a RS for a modelling notation is costly. This is especially detrimental for development paradigms that rely on domain-specific languages (DSLs), like model-driven engineering and lowcode approaches. To alleviate this problem, we propose a DSL called Droid that facilitates the configuration and creation of RSs for particular modelling notations. Its tooling provides automation for all phases in the development of a RS: data preprocessing, system configuration for the modelling language, evaluation and selection of the best recommendation algorithm, and deployment of the RS into a modelling tool. A video of the tool is available at https://www.youtube.com/watch?v=VHiObfKUhS0.Project funded by the EU Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie granta greement No 813884,the Spanish Ministry of Science(PID2021-122270OB-I00) and the R&D programme of Madrid (P2018/TCS-4314)

Latin American Consensus for Pediatric Cardiopulmonary Resuscitation 2017

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.Objectives: To develop a Latin American Consensus about Pediatric Cardiopulmonary Resuscitation. To clarify, reinforce, and adapt some specific recommendations for pediatric patients and to stimulate the implementation of these recommendations in clinical practice. Design: Expert consensus recommendations with Delphi methodology. Setting: Latin American countries. Subjects: Experts in pediatric cardiopulmonary resuscitation from 19 Latin American countries. Interventions: Delphi methodology for expert consensus. Measurements and Main Results: The goal was to reach consensus with all the participating experts for every recommendation. An agreement of at least 80% of the participating experts had to exist in order to deliver a recommendation. Two Delphi voting rounds were sent out electronically. The experts were asked to score between 1 and 9 their level of agreement for each recommendation. The score was then classified into three groups: strong agreement (score 7–9), moderate agreement (score 4–6), and disagreement (score 1–3). Nineteen experts from 19 countries participated in both voting rounds and in the whole process of drafting the recommendations. Sixteen recommendations about organization of cardiopulmonary resuscitation, prevention, basic resuscitation, advanced resuscitation, and postresuscitation measures were approved. Ten of them had a consensus of 100%. Four of them were agreed by all the participants except one (94.7% consensus). One recommendation was agreed by all except two experts (89.4%), and finally, one was agreed by all except three experts (84.2%). All the recommendations reached a level of agreement. Conclusions: This consensus adapts 16 international recommendations to Latin America in order to improve the practice of cardiopulmonary resuscitation in children. Studies should be conducted to analyze the effectiveness of the implementation of these recommendations.Revisión por pare