Recomendação de revisores de código no desenvolvimento distribuído de software

Code review is one of the main software defect mitigation techniques. Intrinsically collaborative, the process involves the analysis of source code modifications by technical peer in adherence to the guidelines of each repository. However, the efficiency of this approach is directly associated with choosing the appropriate technical peers to conduct the scrutiny. Especially in global software development, where members of the development team are geographically scattered with time and availability constraints and there are cultural and technical differences, choosing the reviewer becomes a complex task without the aid of computational tools. The aim of this paper is to present Gitrev, a tool that gathers reviewer recommendation methods for distributed software development that enhance collaboration in the review process. Taking into account the particularities of decentralised production processes, the proposed methods are based on historical interactions between developers, through the design of a collaborative network based on data from GitHub hosted open source repositories. The evaluation of the presented solution is a historic research based on the related literature and objective metrics of efficiency of the reviewers’ participation and instantiated on four major projects available on the platform. The results shows the recommended reviewers enhance interaction and collaboration among team members and adhere significantly to the objectives of the review process.A revisão de código é uma das principais técnicas de diminuição de defeitos de software. Intrinsecamente colaborativo, o processo envolve a análise das modificações no código fonte por um revisor, de acordo com as diretrizes de cada repositório. Contudo, a eficiência da técnica está diretamente associada à escolha dos pares técnicos adequados para realizar o escrutínio. Especialmente no Desenvolvimento Distribuído de Software (DDS), onde os membros da equipe de desenvolvimento estão espalhados geograficamente com restrições de horário e disponibilidade, além de diferenças culturais e técnicas, a escolha do revisor vira tarefa complexa sem auxílio de ferramentas computacionais. O objetivo do presente trabalho é apresentar o GitRev, uma plataforma que reúne diferentes métodos de recomendação de revisores para o desenvolvimento distribuído de software, potencializando a colaboração no processo de revisão. Levando em consideração as particularidades dos processos descentralizados de produção, são propostos métodos baseados nas interações históricas entre os desenvolvedores. Esta análise é realizada através da modelagem de uma rede social colaborativa tendo como base os dados oriundos dos repositórios open source hospedados no GitHub. Uma pesquisa histórica é conduzida para avaliar a solução apresentada, calcada na literatura relacionada e em métricas objetivas de eficiência da participação dos revisores e instanciado em quatro grandes projetos disponíveis na plataforma. Com os resultados obtidos, é possível observar que os revisores recomendados aumentam a interação e colaboração entre os envolvidos e aderem significativamente aos objetivos do processo de revisão

Combining haptics and inertial motion capture to enhance remote control of a dual-arm robot

High dexterity is required in tasks in which there is contact between objects, such as surface conditioning (wiping, polishing, scuffing, sanding, etc.), specially when the location of the objects involved is unknown or highly inaccurate because they are moving, like a car body in automotive industry lines. These applications require the human adaptability and the robot accuracy. However, sharing the same workspace is not possible in most cases due to safety issues. Hence, a multi-modal teleoperation system combining haptics and an inertial motion capture system is introduced in this work. The human operator gets the sense of touch thanks to haptic feedback, whereas using the motion capture device allows more naturalistic movements. Visual feedback assistance is also introduced to enhance immersion. A Baxter dual-arm robot is used to offer more flexibility and manoeuvrability, allowing to perform two independent operations simultaneously. Several tests have been carried out to assess the proposed system. As it is shown by the experimental results, the task duration is reduced and the overall performance improves thanks to the proposed teleoperation method

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

Learning to assist in triadic human-robot interaction

For robots that aim at providing physical assistance, a significant challenge is adapting to the different needs of people. A way to overcome this is to ask human experts to provide demonstrations of how to help a specific person; a setting known as Learning Assistance by Demonstration (LAD). In this thesis, we consider the application of robotic wheelchairs and investigate: how can demonstrations of assistance be used to improve the navigation performance of powered wheelchair users with hand-control disabilities? For this, we first contribute a custom teleoperation platform that enables demonstrations of assistance and uses haptic and virtual reality interfaces to facilitate the interpretation of raw sensor data. This platform is used to test claimed features of LAD, and we show that the technique can adapt to different hand-control impairments and also generates personalised assistive models. Furthermore, we explore the issue of model generalisation to physically different environments, which had not been investigated before. We show that this is a challenging problem and, to overcome it, propose solutions in terms of data collection and preprocessing, training and evaluation procedures, and learning algorithms. With these adaptations, we demonstrate that our model can provide useful assistance, even in previously unseen environments. To accelerate research in this field, we developed software that can simulate the full triadic interaction (assistant/robot/driver) concerning the application of LAD for robotic wheelchairs. This software permits the simulation of multiple disabilities and environments, and also allows people to take up the roles of the simulated driver and/or assistant. Finally, to keep our assumptions and developments in check, we conducted two experimental evaluations with humans, assessing how multimodal interfaces affect one's capability to infer the intention of a driver, and how different learning algorithms impact the generalisation and assistive performance of LAD.Open Acces

Haptic and Visual Feedback Assistance for Dual-Arm Robot Teleoperation in Surface Conditioning Tasks

Contact driven tasks, such as surface conditioning operations (wiping, polishing, sanding, etc.), are difficult to program in advance to be performed autonomously by a robotic system, specially when the objects involved are moving. In many applications, human-robot physical interaction can be used for the teaching, specially in learning from demonstrations frameworks, but this solution is not always available. Robot teleoperation is very useful when user and robot cannot share the same workspace due to hazardous environments, inaccessible locations, or because of ergonomic issues. In this sense, this article introduces a novel dual-arm teleoperation architecture with haptic and visual feedback to enhance the operator immersion in surface treatment tasks. Two task-based assistance systems are also proposed to control each robotic manipulator individually. To validate the remote assisted control, some usability tests have been carried out using Baxter, a dual-arm collaborative robot. After analysing several benchmark metrics, the results show that the proposed assistance method helps to reduce the task duration and improves the overall performance of the teleoperation

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.13Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt