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Since December 2019, the world has been facing the life-threatening disease, named Coronavirus disease-19 (COVID-19), recognized as a pandemic by the World Health Organization. The response of the Emergency Medicine network, integrating "out-of-hospital" and "hospital" activation, is crucial whenever the health system has to face a medical emergency, being caused by natural or human-derived disasters as well as by a rapidly spreading epidemic outbreak. We here report the Pavia Emergency Medicine network response to the COVID-19 outbreak. The "out-of-hospital" response was analysed in terms of calls, rescues and missions, whereas the "hospital" response was detailed as number of admitted patients and subsequent hospitalisation or discharge. The data in the first 5 weeks of the Covid-19 outbreak (February 21-March 26, 2020) were compared with a reference time window referring to the previous 5 weeks (January 17-February 20, 2020) and with the corresponding historical average data from the previous 5 years (February 21-March 26). Since February 21, 2020, a sudden and sustained increase in the calls to the AREU 112 system was noted (+ 440%). After 5 weeks, the number of calls and missions was still higher as compared to both the reference pre-Covid-19 period (+ 48% and + 10%, respectively) and the historical control (+ 53% and + 22%, respectively). Owing to the overflow from the neighbouring hospitals, which rapidly became overwhelmed and had to temporarily close patient access, the population served by the Pavia system more than doubled (from 547.251 to 1.135.977 inhabitants, + 108%). To minimize the possibility of intra-hospital spreading of the infection, a separate "Emergency Department-Infective Disease" was created, which evaluated 1241 patients with suspected infection (38% of total ED admissions). Out of these 1241 patients, 58.0% (n = 720) were admitted in general wards (n = 629) or intensive care unit (n = 91). To allow this massive number of admissions, the hospital reshaped many general ward Units, which became Covid-19 Units (up to 270 beds) and increased the intensive care unit beds from 32 to 60. In the setting of a long-standing continuing emergency like the present Covid-19 outbreak, the integration, interaction and team work of the "out-of-hospital" and "in-hospital" systems have a pivotal role. The present study reports how the rapid and coordinated reorganization of both might help in facing such a disaster. AREU-112 and the Emergency Department should be ready to finely tune their usual cooperation to respond to a sudden and overwhelming increase in the healthcare needs brought about by a pandemia like the current one. This lesson should shape and reinforce the future.

Objectives To detect possible severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA contamination of inanimate surfaces in areas at high risk of aerosol formation by patients with coronavirus disease 2019 (COVID-19). Methods Sampling was performed in the emergency unit and the sub-intensive care ward. SARS-CoV-2 RNA was extracted from swabbed surfaces and objects and subjected to real-time RT-PCR targeting RNA-dependent RNA polymerase and E genes. Virus isolation from positive samples was attempted in vitro on Vero E6 cells. Results Twenty-six samples were collected and only two were positive for low-level SARS-CoV-2 RNA, both collected on the external surface of continuous positive airway pressure helmets. All transport media were inoculated onto susceptible cells, but none induced a cytopathic effect on day 7 of culture. Conclusions Even though daily contact with inanimate surfaces and patient fomites in contaminated areas may be a medium of infection, our data obtained in real-life conditions suggest that it might be less extensive than hitherto recognized.

We describe clinical characteristics, treatments and outcomes of 44 Caucasian patients with coronavirus disease (COVID-19) at a single hospital in Pavia, Italy, from 21–28 February 2020, at the beginning of the outbreak in Europe. Seventeen patients developed severe disease, two died. After a median of 6 days, 14 patients were discharged from hospital. Predictors of lower odds of discharge were age > 65 years, antiviral treatment and for severe disease, lactate dehydrogenase > 300 mg/dL.

Objective: This study aimed to assess the role of Tocilizumab therapy (TCZ) in terms of ICU admission and mortality rate of critically ill patients with severe COVID-19 pneumonia. Design: Patients with COVID-19 pneumonia were prospectively enrolled in SMAtteo COvid19 REgistry (SMACORE). A retrospective analysis of patients treated with TCZ matched using propensity score to patients treated with Standard Of Care (SOC) was conducted. Setting: The study was conducted at IRCCS Policlinico San Matteo Hospital, Pavia, Italy, from March 14, 2020 to March 27, 2020. Participants: Patients with a confirmed diagnosis of COVID-19 hospitalized in our institution at the time of TCZ availability. Interventions: TCZ was administered to 21 patients. The first administration was 8 mg/kg (up to a maximum 800 mg per dose) of Tocilizumab intravenously, repeated after 12 h if no side effects were reported after the first dose. Main Outcomes and Measures: ICU admission and 7-day mortality rate. Secondary outcomes included clinical and laboratory data. Results: There were 112 patients evaluated (82 were male and 30 were female, with a median age of 63.55 years). Using propensity scores, the 21 patients who received TCZ were matched to 21 patients who received SOC (a combination of hydroxychloroquine, azithromycin and prophylactic dose of low weight heparin). No adverse event was detected following TCZ administration. This study found that treatment with TCZ did not significantly affect ICU admission (OR 0.11; 95% CI between 0.00 and 3.38; p = 0.22) or 7-day mortality rate (OR 0.78; 95% CI between 0.06 and 9.34; p = 0.84) when compared with SOC. Analysis of laboratory measures showed significant interactions between time and treatment regarding C-Reactive Protein (CRP), alanine aminotransferase (ALT), platelets and international normalized ratio (INR) levels. Variation in lymphocytes count was observed over time, irrespective of treatment. Conclusions: TCZ administration did not reduce ICU admission or mortality rate in a cohort of 21 patients. Additional data are needed to understand the effect(s) of TCZ in treating patients diagnosed with COVID-19.

Coronavirus disease 2019 (COVID‐19) diagnosis is based on molecular detection of SARS‐CoV‐2 in respiratory samples such as nasal swab (NS) However, the evidence that NS in patients with pneumonia was sometimes negative raises the attention to collect other clinical specimens SARS‐CoV‐2 was shown in 10 3% rectal swabs (RS), 7 7% plasma, 1% urine, and 0% feces from 143 NS‐positive patients Potential infection by fluids different from respiratory secretion is possible but unlikely [ABSTRACT FROM AUTHOR] Copyright of Pediatric Allergy & Immunology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )

Software is widely used, and society increasingly depends on its reliability. However, software has become so complex and it evolves so quickly that we fail to keep it under control. Therefore, we propose intents: fundamental laws that capture a software systems’ intended behavior (resilient, secure, safe, sustainable, etc.). The realization of this idea requires novel theories, algorithms, tools, and techniques to discover, express, verify, and evolve software intents. Thus, future software systems will be able to verify themselves that they meet their intents. Moreover, they will be able to respond to deviations from intents through selfcorrection. In this article we propose a research agenda, outlining which novel theories, algorithms and tools are required.

The interest of organisations in becoming more environmentally sustainable by adopting green ICT solution is constantly growing. More and more initiatives have been proposed on energy efficiency computing, ranging from hardware to software solutions [10]. Accordingly, energy efficiency has become an important issue for industry as energy consumption of ICT systems grows and related energy footprint into realise important financial savings while decreasing the environmental impact of their systems—in terms of, for example, greenhouse gas emissions, e-waste and heat generation [9].

Over the last decades, the use of information and communications technology (ICT) and software systems has exploded, making our lives and work much more efficient. However, besides the benefits that ICT brings us, it also contributes significantly to environmental issues [11, 13], not only because of the electricity consumed by computers, data centres, networks or other ICT utilities but also due to the rapidly growing computation needs of emerging software systems that contribute significantly to ever-increasing energy demands and greenhouse gas emissions [1, 21]. Decreasing ICT operation expenses becomes more and more crucial. How to make ICT greener (i.e. environmentally sustainable) and how to develop greener software have been gaining significant attention [16, 17, 24].

Background Neonatal units’ volume of activity, and other quantitative and qualitative variables, such as staffing, workload, work environment, care organization and geographical location, may influence the outcome of high risk newborns. Data about the distribution of these variables and their relationships among Italian neonatal units are lacking. Methods Between March 2010-April 2011, 63 neonatal intensive care units adhering to the Italian Neonatal Network participated in the SONAR Nurse study. Their main features and work environment were investigated by questionnaires compiled by the chief and by physicians and nurses of each unit. Twelve cross-sectional monthly-repeated surveys on different shifts were performed, collecting data on number of nurses on duty and number and acuity of hospitalized infants. Results Six hundred forty five physicians and 1601 nurses compiled the questionnaires. In the cross-sectional surveys 702 reports were collected, with 11082 infant and 3226 nurse data points. A high variability was found for units’ size (4–50 total beds), daily number of patients (median 14.5, range 3.4-48.7), number of nurses per shift (median 4.2, range 0.7-10.8) and number of team meetings per month. Northern regions performed better than Central and Southern regions for frequency of training meetings, qualitative assessment of performance, motivation within the unit and nursing work environment; mean physicians’ and nurses’ age increased moving from North to South. After stratification by terciles of the mean daily number of patients, the median number of nurses per shift increased at increasing volume of activity, while the opposite was found for the nurse-to-patient ratio adjusted by patients’ acuity. On average, in units belonging to the lower tercile there was 1 nurse every 2.5 patients, while in those belonging to the higher tercile the ratio was 1 nurse every 5 patients. Conclusions In Italy, there is a high variability in organizational characteristics and work environment among neonatal units and an uneven distribution of human resources in relation to volume of activity, suggesting that the larger the unit the greater the workload for each nurse. Urgent modifications in planning and organization of services are needed in order to pursue more efficient, homogeneous and integrated regionalized neonatal care systems.

Architectural Knowledge (AK) is defined as the integrated representation of the software architecture of a software-intensive system or family of systems along with architectural decisions and their rationale, external influence and the development environment. The SHARK workshop series focuses on current methods, languages, and tools that can be used to extract, represent, share, apply, and reuse AK, and the experimentation and/or exploitation thereof. This sixth edition of SHARK will discuss, among other topics, the approaches for AK personalization, where knowledge is not codified through templates or annotations, but it is exchanged through the discussion between the different stakeholders. © 2011 ACM.

Architectural knowledge has been recognized by the software architecture community as a self-contained research area in software architecture, and brought along some promising research directions. In this workshop we discuss the issues that lead to the application of architectural knowledge in research and industrial practice, ongoing research and new ideas to advance the field. In its previous editions this workshop examined the state of the art and practice, future challenges and trends, and architectural knowledge as perceived by different research communities, including requirements engineering, service-oriented computing and international standardization. This fourth edition will discuss, among others, the application, experimentation, specialization and use of architectural knowledge theory and approaches. © 2009 IEEE.

Background: Although life-saving, intubation and mechanical ventilation can lead to complications including bronchopulmonary dysplasia (BPD). In order to reduce the incidence of BPD, non-invasive ventilation (NIV) is increasingly used. Objective: The aim of our study was to describe changes in ventilator strategies and outcomes between 2006 and 2010 in the Italian Neonatal Network (INN). Design: Multicentre cohort study. Settings: 31 tertiary level neonatal units participating in INN in 2006 and 2010. Patients: 2465 preterm infants 23-30 weeks gestational age (GA) without congenital anomalies. Main outcomes measures: Death, BPD and other variables defined according to Vermont Oxford Network. Logistic regressions, adjusting for confounders and clustering for hospitals, were used. Results: Similar numbers of infants were studied between 2006 and 2010 (1234 in 2006 and 1231 in 2010). The baseline risk of populations studied (GA, birth weight and Vermont Oxford Network Risk-Adjustment score) did not change. After adjusting for confounding variables, infants receiving invasive mechanical ventilation decreased (OR=0.72, 95% CI 0.58 to 0.89) while NIV increased (OR=1.75, 95% CI 1.39 to 2.21); intubation in delivery room decreased (OR=0.64, 95% CI 0.51 to 0.79). Considering outcomes, there was a significant reduction in mortality (OR=0.73, 95% CI 0.55 to 0.96) and in the combined outcome mortality or BPD (OR=0.76, 95% CI 0.62 to 0.94). Conclusions: Despite a stable baseline risk, from 2006 to 2010, we observed a lower level of invasiveness, a reduction of mechanical ventilation and an increase of NIV use, and this was accompanied by a decrease in risk-adjusted mortality and BPD.

Service Orientation is a paradigm for exposing business functions as reusable services and enabling business partners to discover those services on demand. Several service-oriented methodologies have been proposed in both academia and industry. Few methodologies, however, do provide concrete yet pragmatic support for developing software that is truly service-oriented, supporting service-specific aspects and challenges. As a consequence, the design of software services that are in-line with service aspects is left up to the prudence of the developers. To fill this gap, this paper proposes a methodology that incorporates essential ingredients of SOA during analysis and design. The methodology focuses service inventories while consciously addressing the perspectives of both service providers and service consumers. By supporting service-oriented reasoning, our methodology results in better reusable services, and the available inventories aid the development of service-oriented systems in a more cost-effective way. This is of the essence in cloud computing, which is a fast-spreading business model promising high ROI and cost savings.

The shift of the software architecture community towards architectural knowledge has brought along some promising research directions. In this workshop we discuss the issues that lead to the application of architectural knowledge in research and industrial practice as well as presenting ongoing research and new ideas to advance the field. We expect to examine the state of the art and practice and gauge future challenges and trends. This year's workshop has a strong emphasis on documenting, sharing, and reusing architectural rationale and design intent. © 2007 IEEE.

Enterprise Architecture (EA) is a mechanism to support IT investment decisions. What is lacking, is a practical tool like a checklist that can be used by enterprise architects to support IT investment decisions, and more specifically, the business case. The business case is a common practice to justify IT investment decisions. The objective of this research is to investigate how the use of a checklist can support enterprise architects to improve the quality of a business case. To answer this question, we conducted design science and developed and evaluated a checklist that can be used by enterprise architects in the assessment of a business case. The evaluation of the checklist was conducted by means of an experiment. The results of the experiment with 32 architects demonstrate that using a checklist as such does not lead to higher quality improvement suggestions in the assessment of a business case as compared to not using a checklist. In other words, a checklist alone does not make the difference. Discussion of the results of the experiment with focus groups reveals several preconditions for the use of a checklist. In any case, the use of the checklist reduces the risk of overlooking valuable insights to improve the quality of the business case.

We report on the use of our DecidArch game to teach software architecture design decision making in two consecutive years. We compare the support of three learning goals for the first version of the game with the second, revised version. Results show how the game has clearly improved. For the remaining issues. we suggest final improvements.

Context: Systematic Reviews (SRs) are means for collecting and synthesizing evidence from the identification and analysis of relevant studies from multiple sources. To this aim, they use a well-defined methodology meant to mitigate the risks of biases and ensure repeatability for later updates. SRs, however, involve significant effort. \ud Goal: The goal of this paper is to introduce a novel methodology that reduces the amount of manual tedious tasks involved in SRs while taking advantage of the value provided by human expertise. \ud Method: Starting from current methodologies for SRs, we replaced the steps of keywording and data extraction with an automatic methodology for generating a domain ontology and classifying the primary studies. This methodology has been applied in the Software Engineering sub-area of Software Architecture and evaluated by human annotators. \ud Results: The result is a novel Expert-Driven Automatic Methodology, EDAM, for assisting researchers in performing SRs. EDAM combines ontology-learning techniques and semantic technologies with the human-in-the-loop. The first (thanks to automation) fosters scalability, objectivity, reproducibility and granularity of the studies; the second allows tailoring to the specific focus of the study at hand and knowledge reuse from domain experts. We evaluated EDAM on the field of Software Architecture against six senior researchers. As a result, we found that the performance of the senior researchers in classifying papers was not statistically significantly different from EDAM. \ud Conclusions: Thanks to automation of the less-creative steps in SRs, our methodology allows researchers to skip the tedious tasks of keywording and manually classifying primary studies, thus freeing effort for the analysis and the discussion.

The intersection between software engineering research and the problems related to sustainability and green IT has been the subject of increasing attention. In spite of that, we observe that sustainability is still not clearly defined, or understood, in the field of software engineering. This lack of clarity leads to confusion about e.g. what is relevant to measure or the research implications over time or space. This paper provides an overview of how the research so far has defined sustainability, and how this definition has been used to guide which research areas. To this end, we carried out a systematic mapping study for selecting, classifying and analyzing relevant publications. In this study, we investigate which knowledge areas and which time scope of sustainability effects are mostly targeted in scientific research. Our analysis shows research trends and discusses gaps to be filled.

Software and IT usage are continuously growing to keep our society active and manage our individual lives. But as they grow, their energy demand is exploding. By 2030, data centers alone will already consume some 10% of the global electricity.1 Including the Internet, telecommunications, and embedded devices, the energy consumption will be one-third of the global demand. Understanding that end users only consume what we offer, it is the community of software developers who must become active in ecologic behaviors. Green IT is the call of today. Each single line of code that we develop today may still be running years from now on zillions of processors, eating energy and contributing to global climate change.

Although the benefits are well-known and undisputed, sharing architectural knowledge is not something architects automatically do. In an attempt to better understand what architects really do and what kind of support they need for sharing knowledge, we have conducted large-scale survey research. The results of our study indicate that architects can be characterized as rather lonesome decision makers who mainly consume, but neglect documenting and actively sharing architectural knowledge. Acknowledging this nature of architects suggests ways to develop more effective support for architectural knowledge sharing. © 2010 Elsevier Inc. All rights reserved.

Introduction In 1973, Petrea Jacobsen described the first patient showing dysmorphic features, developmental delay and congenital heart disease (atrial and ventricular septal defect) associated to a 11q deletion, inherited from the father. Since then, more than 200 patients have been reported, and the chromosomal critical region responsible for this contiguous gene disorder has been identified. Patients’ presentation We report on two unrelated newborns observed in Italy affected by Jacobsen syndrome (JBS, also known as 11q23 deletion). Both patients presented prenatal and postnatal bleeding, growth and developmental delay, craniofacial dysmorphisms, multiple congenital anomalies, and pancytopenia of variable degree. Array comparative genomic hybridization (aCGH) identified a terminal deletion at 11q24.1-q25 of 12.5 Mb and 11 Mb, in Patient 1 and 2, respectively. Fluorescent in situ hybridization (FISH) analysis of the parents documented a de novo origin of the deletion for Patient 1; parents of Patient 2 refused further genetic investigations. Conclusions Present newborns show the full phenotype of JBS including thrombocytopenia, according to their wide 11q deletion size. Bleeding was particularly severe in one of them, leading to a cerebral hemorrhage. Our report highlights the relevance of early diagnosis, genetic counselling and careful management and follow-up of JBS patients, which may avoid severe clinical consequences and lower the mortality risk. It may provide further insights and a better characterization of JBS, suggesting new elements of the genotype-phenotype correlations.

Software architecture can be defined as the overall structure of a software system. Specifically, it defines the components of the system and their relationships [3] [21]. Architecture usually provides several perspectives on the same system to answer the varying concerns of different system stakeholders. Defining the software architecture of an application or service is a key activity in the overall design and production process. In this chapter are notations and guidelines to define the architecture of a new wireless service.

The Robot Operating System (ROS) is the de-facto standard for robotic software. If on one hand ROS is helping roboticists, e.g., by providing a standardized communication platform, on the other hand ROS-based systems are getting larger and more complex and could benefit from good software architecture practices. This paper presents an observational study aimed at (i) unveiling the state-ofthe- practice for architecting ROS-based systems and (ii) providing guidance to roboticists about how to properly architect ROS-based systems. To achieve these goals, we (i) build a dataset of 335 GitHub repositories containing real open-source ROS-based systems, (ii) mine the repositories for extracting the state of the practice about how roboticists are architecting them, and (iii) synthesize a catalog of 49 evidence-based guidelines for architecting ROS-based systems. The guidelines have been validated by 77 roboticists working on real-world open-source ROS-based systems.

Current software engineering practices rely on highly heterogeneous and distributed teams working in a collaborative setting. Between 2013-2020, the publication output in the field of collaborative Model-Driven Software Engineering (MDSE) has significantly increased. However, the only systematic mapping study available is limited to studies published until 2015. In this paper, we provide an update on that study for the complementing 2016-2020 period, and report the latest results, challenges, and trends. Our analysis led to selecting 29 clusters of 54 new peer-reviewed publications on collaborative MDSE. Based on the novel developments in the field, we have extended and improved the original classification framework, making it applicable to recent and future research contributions on collaborative MDSE. The insights in this paper relate to the changing trends in the field and present new relevant information.

Context: The Robot Operating System (ROS) is the de-facto standard for robotics software. However, ROS-based systems are getting larger and more complex and could benefit from good software architecture practices. Goal: We aim at (i) unveiling the state-of-the-practice in terms of targeted quality attributes and architecture documentation in ROS-based systems, and (ii) providing empirically-grounded guidance to roboticists about how to properly architect ROS-based systems. Methods: We designed and conducted an observational study where we (i) built a dataset of 335 GitHub repositories containing real open-source ROS-based systems, and (ii) mined the repositories to extract and synthesize quantitative and qualitative findings about how roboticists are architecting ROS-based systems. Results: First, we extracted an empirically-grounded overview of the state of the practice for architecting and documenting ROS-based systems. Second, we synthesized a catalog of 47 architecting guidelines for ROS-based systems. Third, the extracted guidelines were validated by 119 roboticists working on real-world open-source ROS-based systems. Conclusion: Roboticists can use our architecting guidelines for applying good design principles to develop robots that meet quality requirements, and researchers can use our results as evidence-based indications about how real-world ROS systems are architected today, thus inspiring future research contributions.

A wealth of e-Health mobile apps are available for many purposes, such as life style improvement, mental coaching, etc. The interventions, prompts, and encouragements of e-Health apps sometimes take context into account (e.g., previous interactions or geographical location of the user), but they still tend to be rigid, e.g., by using fixed rule sets or being not sufficiently tailored towards individuals. Personalization to the different users’ characteristics and run-time adaptation to their changing needs and context provide a great opportunity for getting users continuously engaged and active, eventually leading to better physical and mental conditions. This paper presents a reference architecture for enabling AI-based personalization and self-adaptation of mobile apps for e-Health. The reference architecture makes use of multiple MAPE loops operating at different levels of granularity and for different purposes.

The field green ICT focuses on the greening of ICT and using ICT to optimise the energy footprint of the ICT-supported processes. For organisations, applying green ICT in the broadest sense presents them with challenges. In this paper we explore what factors are influencing the adoption of green ICT. We follow three organisations that used a green ICT tool, the SURF Green ICT Maturity Model, to identify such factors. Tools like the maturity model help organisations identify the what and how. We found other factors, such as strategic alignment, culture and leadership, determine the why. As ICT is a general purpose technology, it potentially affects all processes in an organisation. To have a greening impact, the main challenge for green ICT is to take a systemic approach and involve all (relevant) parties. ICT departments often position themselves as support (followers, not leaders), this proves to be a big hurdle in the adoption of green ICT.

With the increasing dependence on software systems, their longevity is becoming a pressing need. Stability is envisioned as a primary property to achieve longevity. Stability has been defined and treated in many different ways in the literature. We conduct a systematic literature review to analyse the state-of-the-art related to stability as a software property. We formulate a taxonomy for characterising the notion, analyse the definitions found in the literature, and present research studies dealing with stability. Also, as architecture is one of the software artefacts with profound effects throughout the software lifecycle, we focus on software engineering practices for realising architectural stability. The analysis results show a wide variation in dimensions when dealing with stability. The state-of-the-art indicates the need for a shift towards a multi-dimensional concept that could cope with runtime dynamics and emerging software paradigms. More research efforts should be directed toward the identified gaps. The presented taxonomy and analysis of the literature aim to help the research community in consolidating the existing research efforts and deriving future developments.

In today's world, reducing energy consumption should be the goal for any organization and any system, including robotics software systems. However, state of the practice in robotics software development focuses primarily on achieving functionality and performance, with minimal recognition of energy-efficiency as a driving software quality. The goal of this paper is to identify, synthesize, and empirically evaluate architectural tactics for energy-efficiency applied by practitioners in real robotics projects. Four tactics were identified by mining software repository techniques applied to the ROS ecosystem. The tactics were evaluated via experimentation on a real, commodity robotics system. Results show that the application of green architectural tactics tends to largely improve the energy-efficiency of the robot (7.9% energy savings when all tactics are applied) and that the movement strategy and the physical environment where the robot operates strongly influence how energy is consumed by the robot.

Robots are becoming more and more commonplace in many industry settings. This successful adoption can be partly attributed to (1) their increasingly affordable cost and (2) the possibility of developing intelligent, software-driven robots. Unfortunately, robotics software consumes significant amounts of energy. Moreover, robots are often battery-driven, meaning that even a small energy improvement can help reduce its energy footprint and increase its autonomy and user experience. In this paper, we study the Robot Operating System (ROS) ecosystem, the de-facto standard for developing and prototyping robotics software. We analyze 527 energy-related data points (including commits, pull-requests, and issues on ROS-related repositories, ROS-related questions on StackOverflow, ROS Discourse, ROS Answers, and the official ROS Wiki). Our results include a quantification of the interest of roboticists on software energy efficiency, 10 recurrent causes, and 14 solutions of energy-related issues, and their implied trade-offs with respect to other quality attributes. Those contributions support roboticists and researchers towards having energy-efficient software in future robotics projects., Comment: 11 pages

Architectural technical debt in software-intensive systems is a metaphor used to describe the “big” design decisions (e.g., choices regarding structure, frameworks, technologies, languages, etc.) that, while being suitable or even optimal when made, significantly hinder progress in the future. While other types of debt, such as code-level technical debt, can be readily detected by static analyzers, and often be refactored with minimal or only incremental efforts, architectural debt is hard to be identified, of wide-ranging remediation cost, daunting, and often avoided. In this study, we aim at developing a better understanding of how software development organizations conceptualize architectural debt, and how they deal with it. In order to do so, in this investigation we apply a mixed empirical method, constituted by a grounded theory study followed by focus groups. With the grounded theory method we construct a theory on architectural technical debt by eliciting qualitative data from software architects and senior technical staff from a wide range of heterogeneous software development organizations. We applied the focus group method to evaluate the emerging theory and refine it according to the new data collected. The result of the study, i.e., a theory emerging from the gathered data, constitutes an encompassing conceptual model of architectural technical debt, identifying and relating concepts such as its symptoms, causes, consequences, management strategies, and communication problems. From the conducted focus groups, we assessed that the theory adheres to the four evaluation criteria of classic grounded theory, i.e., the theory fits its underlying data, is able to work, has relevance, and is modifiable as new data appears. By grounding the findings in empirical evidence, the theory provides researchers and practitioners with novel knowledge on the crucial factors of architectural technical debt experienced in industrial contexts.

Aviation connects our world by efficiently and rapidly moving people, opening new economic opportunities and transporting food and goods globally. But the notable growth of air travel in recent years has led to increasingly crowded airspace. According to the 2019 European Aviation Environment Report, aviation is responsible for about 3% of global CO2 emissions, which translates into a big ecological impact. It is imperative to steer the aviation industry towards optimizing resources, reducing costs, improving decision-making and increasing systems' resilience to unexpected events. In this work, we study the sustainability impact of software architecture principles at Amsterdam Schiphol Airport. To this aim, we create a framework that relates architecture principles with sustainability concerns, with the aim of seeking the right balance toward a positive impact on the sustainable development of the organization and its services. We combine techniques like OGSM and Decision Maps to extend the current architecture principles, and elicit Key Performance Indicators from current industrial practice. The resulting framework is the first step towards adopting sustainability in architecting and laying the foundation to monitor the effectiveness of the implemented architecture principles on the target sustainability goals of the organization.

The need for acknowledging and managing sustainability as an essential quality of software systems has been steadily increasing over the past few years, in part as a reaction to the implications of ``software eating the world''. Especially the widespread adoption of the Everything as a Service (*aaS) model of delivering software and (virtualized) hardware through cloud computing has put two sustainability dimensions upfront and center. On the one hand, services must be sustainable on a technical level by ensuring continuity of operations for both providers and consumers despite, or even better, while taking into account their evolution. On the other hand, the prosuming of services must also be financially sustainable for the involved stakeholders.

Background The ongoing pandemic of COVID-19 has underlined the importance of adopting effective infection prevention and control (IPC) measures in hospital and community settings. UV-based technologies represent promising IPC tools: their effective application for sanitation has been extensively evaluated in the past but scant, heterogeneous and not conclusive evidence is available on their effect on SARS-CoV-2 transmission. Methods With the aim of pooling the available evidence on the efficacy of UV technologies against coronaviruses, we conducted a systematic review following PRISMA guidelines, searching Medline, Embase and Cochrane Library, and the main clinical trials’ registries (WHO ICTRP, ClinicalTrials.gov, Cochrane and EU Clinical Trial Register). Quantitative data on studies’ interventionS were summarized in tables, pooled by different coronavirus species and strain, UV source, characteristics of UV light exposure and outcomes. Findings Eighteen papers met our inclusion criteria, published between 1972 and 2020. Six focused on SARS-CoV-2, four on SARS-CoV-1, one on MERS-CoV, three on seasonal coronaviruses, and four on animal coronaviruses. All were experimental studies. Overall, despite wide heterocenicity within included studies, complete inactivation of coronaviruses on surfaces or aerosolized, including SARS-CoV-2, was reported to take a maximum exposure time of 15 minutes and to need a maximum distance from the UV emitter up to 1 meter. Conclusion Advances in UV-based technologies in the field of sanitation and their proved high virucidal potential against SARS-CoV-2 support their use for IPC in hospital and community settings and their contribution towards ending the COVID-19 pandemic. National and international guidelines are to be updated and identify parameters and conditions of use to ensure both efficacy and safety of UV technology application for effective infection prevention and control in both healthcare and non-healthcare settings.

[Abstract] A number of software systems that attempt to help people achieve behavior change have been proposed in various domains such as health and wellness. However, sometimes, such systems have failed to provide a satisfactory or sustainable User Experience (UX), as it is observed when users may be reluctant to respond to the activation of the systems' changing demands. Moreover, a negative User Experience (UX) can be exposed by Behavior Change Support Systems (BCSS) if designers do not have clear understanding of the requirements that factually help changing the user behavior that accomplishes a sustainability goal. We first explored the Persuasive System Design (PSD) model that should be considered in UX assessment of BCSSs. Then, we propose a requirements discovery process that can be considered to redesign a software interactive system based on negative UX. This work has received partial support by the projects FEDER-UE CSI ED431G/01, ED43C 2018/29, accreditation 2016-2019 ED431G/08, KUSISQA supported by N° 014-2019-FONDECYT-BM-INC.INV, NOVA LINCS UID/CEC/04516/2019, MICINN IJC2018-037522-I, RTI2018-099646-B-I00 Xunta de Galicia; ED431G/01 Xunta de Galicia; ED43C 2018/29 Xunta de Galicia; ED431G/08 Gobierno de Chile; 014-2019-FONDECYTBM-INC.INV República Portuguesa. Fundação para a Ciência e a Tecnologia; UID/CEC/04516/2019

In the last years, software engineering researchers have defined sustainability as a quality requirement of software, but not enough effort has been devoted to develop new methods/techniques to support the analysis and assessment of software sustainability. In this study, we present the Sustainability Assessment Framework (SAF) that consists of two instruments: the software sustainability&ndash, quality model, and the architectural decision map. Then, we use participatory and technical action research in close collaboration with the software industry to validate the SAF regarding its applicability in specific cases. The unit of analysis of our study is a family of software products (Geographic Information System- and Mobile-based Workforce Management Systems) that aim to address sustainability goals (e.g., efficient collection of dead animals to mitigate social and environmental sustainability risks). The results show that the sustainability&ndash, quality model integrated with the architectural decision maps can be used to identify sustainability&ndash, quality requirements as design concerns because most of its quality attributes (QAs) have been either addressed in the software project or acknowledged as relevant (i.e., creating awareness on the relevance of the multidimensional sustainability nature of certain QAs). Moreover, the action&ndash, research method has been helpful to enrich the sustainability&ndash, quality model, by identifying missing QAs (e.g., regulation compliance, data privacy). Finally, the architectural decision maps have been found as useful to guide software architects/designers in their decision-making process.

Background Since sustainability became a challenge in software engineering, researchers mainly from requirements engineering and software architecture communities have contributed to defining the basis of the notion of sustainability-aware software. Problem Despite these valuable efforts, the assessment and design based on the notion of sustainability as a software quality is still poorly understood. There is no consensus on which sustainability requirements should be considered. Aim and Method To fill this gap, a survey was designed with a double objective: i) determine to which extent quality requirements contribute to the sustainability of software-intensive systems; and ii) identify direct dependencies among the sustainability dimensions. The survey involved different target audiences (e.g. software architects, ICT practitioners with expertise in Sustainability). We evaluated the perceived importance/relevance of each sustainability dimension, and the perceived usefulness of exploiting a sustainability model in different software engineering activities. Results Most respondents considered modifiability as relevant for addressing both technical and environmental sustainability. Functional correctness, availability, modifiability, interoperability and recoverability favor positively the endurability of software systems. This study has also identified security, satisfaction, and freedom from risk as very good contributors to social sustainability. Satisfaction was also considered by the respondents as a good contributor to economic sustainability.

Architectural technical debt in a software-intensive system is driven by design decisions about its structure, frameworks, technologies, languages, etc. Unlike code-level technical debt, which can be readily detected by static analysers, and can often be refactored with minimal efforts, architectural debt is hard to detect, and its remediation is wide-ranging, daunting, and often avoided. The objective of this study is to develop a better understanding of how software development organisations conceptualize their architectural debt, and how they deal with it, if at all. We used a grounded theory method, eliciting qualitative data from software architects and senior technical staff from a wide range of software development organizations. The result of the study, i.e., the theory emerging from the collected data, constitutes an encompassing conceptual theory of architectural debt, identifying and relating concepts such as symptoms, causes, consequences, and management strategies. By grounding the findings in empirical data, the theory provides researchers and practitioners with evidence of which crucial factors of architectural technical debt are experienced in industrial contexts.

Background] A software sustainability model is commonly defined in terms of social, economic, technical and environmental dimensions. A key challenge is its characterization regarding sustainability requirements and their dependencies since it depends on, and varies with, the type of software system, and changes in operational contexts. [Aims] With the purpose of facilitating the definition of a context-dependent software sustainability model, we introduce nichesourcing as a type of distributed problem-solving paradigm, named crowdsourcing. [Method] First a set of nichesourcing requirements were identified, and an existing nichesourcing methodology, originally used in the cultural heritage domain was analyzed with respect to its applicability in Software Engineering. [Results] As a result, we propose an adapted methodology for nichesourcing the knowledge on sustainability requirements and their dependencies. Strengths and challenges for crowdsourced software engineering are also identified.

Clustering of users underlies many of the personalisation algorithms that are in use nowadays. Such clustering is mostly performed in an offline fashion. For a health and wellbeing setting, offline clustering might however not be suitable, as limited data is often available and patient states can also quickly evolve over time. Existing online clustering algorithms are not suitable for the health domain due to the type of data that involves multiple time series evolving over time. In this paper we propose a new online clustering algorithm called CluStream-GT that is suitable for health applications. By using both artificial and real datasets, we show that the approach is far more efficient compared to regular clustering, with an average speedup of 93%, while only losing 12% in the accuracy of the clustering with artificial data and 3% with real data.CCS CONCEPTS• Computing methodologies$\rightarrow$ Cluster analysis.

Background. Software sustainability is defined in terms of multiple and interdependent dimensions (economic, social, technical and environmental). Preliminary initiatives have investigated the contribution of certain quality attributes to sustainability dimensions. Problem. Despite these valuable efforts, the characterization of software sustainability is still a key challenge. This entails how sustainability can be embraced in the design of software systems by identifying the relevant software quality attributes (QAs) and their dependencies. Both attributes and dependencies vary heavily with amongst others the type of software system and its operational context. Aim and Method. We followed a multiple case study research method with the main objective of investigating the applicability of the sustainability model in different contexts. We aim also to enrich our model, by means of identifying missing quality attributes or new contributions to the sustainability dimensions. We selected two software projects as cases of our study, where each one was independently conducted in specific situations. Results. The results of the study show that the relevant quality requirements identified in both projects (cases) are covered by most of the QAs related to the social (82%) and technical (83%) dimensions. Moreover, some QAs that were not addressed in the corresponding projects, their relevance like context completeness, and flexibility were acknowledged. These results suggest that the software sustainability model could support the identification of relevant QAs. The case study also contributed to identify QAs that had not been considered in the economic, technical and social dimensions of the sustainability-quality model.

Microservice architecture (MSA) is defined as an architectural style where the software system is developed as a suite of small services, each running in its own process and communicating with lightweight mechanisms. The benefits of MSA are many, ranging from an increase in development productivity, to better business-IT alignment, agility, scalability, and technology flexibility. The high degree of microservices distribution and decoupling is, however, imposing a number of relevant challenges from an architectural perspective. In this context, measuring, controlling, and keeping a satisfactory level of quality of the system architecture is of paramount importance. In this paper we propose an approach for the specification, aggregation, and evaluation of software quality attributes for the architecture of microservice-based systems. The proposed approach allows developers to (i) produce architecture models of the system, either manually or automatically via recovering techniques, (ii) contribute to an ecosystem of well-specified and automatically-computable software quality attributes for MSAs, and (iii) continuously measure and evaluate the architecture of their systems by (re-)using the software quality attributes defined in the ecosystem. The approach is implemented by using Model-Driven Engineering techniques. The current implementation of the approach has been validated by assessing the maintainability of a third-party, publicly available benchmark system.

Cyber-foraging is a technique to enable mobile devices to extend their computing power and storage by offloading computation or data to more powerful servers located in the cloud or in single-hop proximity. In previous work, we developed a set of reusable architectural tactics for cyber-foraging systems. We define architectural tactics as design decisions that influence the achievement of a system quality. In this article we present the results of three case studies to validate the application of the tactics to promote their intended functional and non-functional requirements. The first two case studies focus on the identification of architectural tactics in existing cyber-foraging systems. The third case study focuses on the development of a new cyber-foraging system using the architectural tactics. The results of the case studies are an initial demonstration of the validity of the tactics, and the potential for taking a tactics-driven approach to fulfill functional and non-functional requirements for cyber-foraging systems. (C) 2019 Elsevier B.V. All rights reserved.

Prefetching network requests has been advocated as a highly effective way of reducing network latency experienced by the user since it allows network responses to be generated immediately from a local cache. In this paper we discuss how user navigation patterns can be used for developing navigation-aware techniques for personalized prefetching of network requests of Android apps. The proposed idea opens for a new family of prefetching opportunities since it focusses at a higher level of abstraction with respect to state-of-the-art approaches for network requests prefetching. The proposed idea allows the development of approaches which adapt their prefetching behaviour according to the unique navigation patterns each user exhibits while interacting with a mobile app.

Context. Android is the largest mobile platform today, with thousands of apps published and updated in the Google Play store everyday. Maintenance is an important factor in Android apps lifecycle, as it allows developers to constantly improve their apps and better tailor them to their user base. Goal. In this paper we investigate the evolution of various maintainability issues along the lifetime of Android apps. Method. We designed and conducted an empirical study on 434 GitHub repositories containing open, real (i.e., published in the Google Play store), and actively maintained Android apps. We statically analyzed 9,945 weekly snapshots of all apps for identifying their maintainability issues over time. We also identified maintainability hotspots along the lifetime of Android apps according to how their density of maintainability issues evolves over time. More than 2,000 GitHub commits belonging to identified hotspots have been manually categorized to understand the context in which maintainability hotspots occur. Results. Our results shed light on (i) how often various types of maintainability issues occur over the lifetime of Android apps, (ii) the evolution trends of the density of maintainability issues in Android apps, and (iii) an in-depth characterization of development activities related to maintainability hotspots. Together, these results can help Android developers in (i) better planning code refactoring sessions, (ii) better planning their code review sessions (e.g., steering the assignment of code reviews), and (iii) taking special care of their code quality when performing tasks belonging to activities highly correlated with maintainability issues. We also support researchers by objectively characterizing the state of the practice about maintainability of Android apps. Conclusions. Independently from the type of development activity, maintainability issues grow until they stabilize, but are never fully resolved.

Nowadays, many software applications are executed in mobile devices. This poses new challenges on optimizing the limited capacity set by battery life without compromising energy efficiency and performance. In this paper, we propose a framework for mobile applications to enable and evaluate self-Adaptability for the purpose of improving energy efficiency without sacrificing performance. Our framework consists of two main parts: The mobile apps simulator and the scheduler.

Behavior Change Software systems (BCSSs) have shown promising outcomes in terms of promoting healthy behaviors. However, a negative User Experience (UX) can be induced by BCSS if designers do not have clear understanding of the requirements that factually help in changing the user behavior that achieves a sustainability goal. In order to get insights into how to discover such sustainability requirements, we propose a discovery approach, whose emphasis is placed on negative UX assessed through attitudes and behaviors expressed by users due to the lack of fulfillment of actual user needs. The approach is tested on existing software systems designed for preventing or reducing Repetitive Strain Injury as a particular category of BCSS. Twelve requirements that contribute to social sustainability were discovered.

Most of the innovation in automotive is nowadays coming from electronics and software. The pressure of reducing time to market and increasing flexibility while keeping quality are leading motivations for these companies to embrace system-wide Continuous Integration and Delivery (CI&D), which in the scope of complex automotive value-chains, implies inter-organizational CI&D. In this paper, we investigate the challenges and impediments posed by inter-organizational CI&D in the automotive domain, i.e. continuous software development that involves agile interaction between an OEM (the car manufacturer) and its software suppliers. In particular, we focus on legal contracts that regulate the agreements between these companies and transparency intended as the degree/level of information that is shared between the various companies in the value-chain. The main findings of this study show that (i) inter-organizational transparency is considered positive but not a necessary condition for inter-organizational CI&D, (ii) transparency has positive effects on information sharing among different companies, and (iii) legal contracts are an impediment for inter-organizational CI&D. The results of the study provide useful insights for practitioners that work in similar settings. In addition, the identified challenges and impediments define a research agenda for researchers.