Hatching Compositions of Low-code Templates

Funding Information: Acknowledgements. Partially supported by grant Lisboa-01-0247-Feder-045917. Publisher Copyright: © 2022 ACM.Low-code frameworks strive to simplify and speed-up application development. Native support for the reuse and composition of parameterised coarse-grain components (templates) is essential to achieve these goals. OSTRICH-a rich template language for the OutSystems platform-was designed to simplify the use and creation of such templates. However, without a built-in composition mechanism, OSTRICH templates are hard to create and maintain. This paper presents a template composition mechanism and its typing and instantiation algorithms for model-driven low-code development environments. We evolve OSTRICH to support nested templates and allow the instantiation (hatching) of templates in the definition of other templates. Thus, we observe a significant increase code reuse potential, leading to a safer evolution of applications. The present definition seamlessly extends the existing Out-Systems metamodel with template constructs expressed by model annotations that maintain backward compatibility with the existing language toolchain. We present the metamodel, its annotations, and the corresponding validation and instantiation algorithms. In particular, we introduce a type-based validation procedure that ensures that using a template inside a template produces valid models. The work is validated using the OSTRICH benchmark. Our prototype is an extension of the OutSystems IDE allowing the annotation of models and their use to produce new models. We also analyse which existing OutSystems sample screens templates can be improved by using and sharing nested templates.publishe

Robust Contract Evolution in a TypeSafe MicroServices Architecture

Microservices architectures allow for short deployment cycles and immediate effects but offer no safety mechanisms when service contracts need to be changed. Maintaining the soundness of microservice architectures is an error-prone task that is only accessible to the most disciplined development teams. We present a microservice management system that statically verifies service interfaces and supports the seamless evolution of compatible interfaces. We define a compatibility relation that captures real evolution patterns and embodies known good practices on the evolution of interfaces. Namely, we allow for the addition, removal, and renaming of data fields of a producer module without breaking or needing to upgrade consumer services. The evolution of interfaces is supported by runtime generated proxy components that dynamically adapt data exchanged between services to match with the statically checked service code.The model was instantiated in a core language whose semantics is defined by a labeled transition system and a type system that prevents breaking changes from being deployed. Standard soundness results for the core language entail the existence of adapters, hence the absence of adaptation errors and the correctness of the management model. This adaptive approach allows for gradual deployment of modules, without halting the whole system and avoiding losing or misinterpreting data exchanged between system nodes. Experimental data shows that an average of 69% of deployments that would require adaptation and recompilation are safe under our approach

Typing the evolution of variational software

[Excerpt] Maintaining multiple versions of a software system is a laborious and challenging task, which is many times a strong requirement of the software development process. Such hurdle is justified by needs of backward compatibility with libraries or existence of legacy equipment with particular constraints. It is also an intrinsic requirement of software product lines that target multiple target platforms, service, or licensing levels [7]. A crucial example of a high variability context is an operating system where hundreds of variants need to be maintained to cope with all the different target architectures [1]. We find another important example in mobile applications, where server and client code need to be updated in sync to change structure of the interface or the semantics of webservices. However, it is always the case that older versions of server code must be maintained to support client devices that are not immediately updated. The soundness of a unique and common code corpus demands a high degree of design and programming discipline [8], code versioning, branching and merging tools [12], and sophisticated management methods [11, 9]. For instance, in looselycoupled service-oriented architectures, where the compatibility guaranties between modules are almost non-existent, special attention is needed to maintain the soundness between multiple versions of service end-points (cf. Twitter API [13]). [...]This work is supported by NOVA LINCS UID/CEC/04516/2013, COST CA15123 - EUTYPES and FC&T Project CLAY - PTDC/EEI-CTP/4293/2014

Conforto térmico em trabalhadores de aviários

Background: the poultry work environment has been a cause of concern in relation to the occurrence of biological risks, being still this environment the target of few studies by Occupational Health and Safety professionals. Objectives: evaluate of thermal comfort through the analysis of the Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) indexes. Methodology: sampling was non-probabilistic as to type and for convenience as to technique. The sample consisted of 8 aviaries from 2 companies and 6 workers who worked in them. Questionnaires were applied to workers and the environmental and individual parameters related to thermal comfort were evaluated, inside and outside the aviaries. Results: it was verified the existence of thermal discomfort in the evaluated aviaries. This discomfort is a consequence of workers' occupational exposure to different temperatures, particularly during the winter season. Conclusion: constructive measures were suggested in terms of ventilation, the existence of a thermal recovery area and a rest area for personnel after occupational exposure to cold or heat. As for individual measures, it was advised to wear appropriate clothing depending on the location of the tasks to be carried out, inside or outside, in the aviaries.Marco contextual: El entorno de trabajo avícola ha sido un motivo de preocupación en relación a la ocurrencia de riesgos biológicos, y este entorno sigue siendo objeto de pocos estudios por parte de profesionales de Seguridad y Salud Ocupacional. Objetivos: evaluar el confort térmico mediante el análisis de los índices de Predicted Mean Vote(VMP) y Predicted Percentage of Dissatisfied (PPI). Metodología: la muestra fue no probabilística con respecto al tipo y por conveniencia en cuanto a la técnica. La muestra se constituyó por 8 aviarios de 2 empresas y 6 trabajadores que en ellos laboraban. Se aplicaron cuestionarios a los trabajadores y se evaluaron los parámetros ambientales e individuales relacionados con el confort térmico, dentro y fuera de los aviarios. Resultados: se constató la existencia de malestar térmico en los aviarios evaluados. Esta incomodidad es consecuencia de la exposición ocupacional de los trabajadores a diferentes temperaturas, particularmente en el invierno. Conclusión:Se han sugerido, la existencia de un área de recuperación térmica y una zona de reposo para las personas después de la exposición ocupacional al frío o al calor. Se recomendó tener ropa adecuada según el lugar de las tareas a realizar dentro o fuera de los aviarios.Enquadramento: podendo existir vulnerabilidade dos trabalhadores avícolas face às temperaturas do interior dos aviários em comparação com as do exterior é importante analisar a sua exposição ocupacional em termos de conforto térmico. Objetivos: avaliar o conforto térmico em trabalhadores do setor avícola no ambiente interior e exterior dos aviários e analisar a sua possível relação com a fase de desenvolvimento do frango. Metodologia: o estudo efetuado foi observacional, transversal, com uma amostra por conveniência de 6 trabalhadores de 8 aviários. A recolha de dados foi realizada através de um questionário dirigido a todos os trabalhadores seguida da medição dos valores de Predicted Mean Vote (PMV) e Predicted Percentage of Dissatisfied (PPD). Resultados: em aviários de frangos com 8 dias de idade verificou-se uma total concordância entre os valores de PMV e PPD, nos de 35 dias uma concordância significativa e nos de 85 dias uma considerável concordância. Conclusão: existe desconforto térmico nos trabalhadores avaliados, especialmente nos que trabalham em aviários para frangos com 8 e 35 dias de idade. O desconforto térmico foi pior nos aviários de frangos com 8 dias, revelando assim a relação entre o índice de conforto térmico e a fase de desenvolvimento do frango

The IPIN 2019 Indoor Localisation Competition—Description and Results

IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks

Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001

Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001.Peer reviewe