Characterization of trade-off preferences between non-functional properties

Efficient design and evolution of complex software intensive systems rely on the ability to make informed decisions as early as possible in the life cycle. Such informed decisions should take both the intended functional and non-functional properties into account. Especially regarding the latter, it is both necessary to be able to predict properties and to prioritize them according to well-defined criteria. In this paper we focus on the latter problem, that is to say how to make trade-offs between non-functional properties of software intensive systems. We provide an approach based on the elicitation of utility functions from stake-holders and subsequent checks for consistency among these functions. The approach is exploitable through an easy-to-use GUI, which is also presented. Moreover, we describe the setup and the outcome of our two-fold validation based on exploratory elicitations with students and practitioners

Multi-view approaches for software and system modelling: a systematic literature review

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A hybrid approach for multi-view modeling

Multi-view modeling is a widely accepted technique to reduce the complexity in the development of modern software systems. It allows developers to focus on a narrowed portion of the specification dealing with a selected aspect of the problem. However, multi-view modeling support discloses a number of issues: on the one hand consistency management very often has to cope with semantics interconnections between the different concerns. On the other hand, providing a predefined set of views usually results as too restrictive because of expressiveness and customization needs. This paper proposes a hybrid solution for multi-view modeling based on an arbitrary number of custom views defined on top of an underlying modeling language. The aim is to benefit from the consistency by-construction granted by well-defined views while at the same time providing malleable perspectives through which the system under development can be specified

Platelet activating factor (1-O-alkyl-2-O-acetyl-sn-glycero-3-phosphocholine) Activity of analogs lacking oxygen at the 2-position

In mission-critical Internet of Things systems, applications require not only high availability, reliability, safety, and security but also regulatory compliance, scalability, and serviceability. In addition, they\u27re exposed to uncertainty and variability. Model-driven engineering is a candidate for meeting these challenges

Model-driven engineering for mobile robotic systems: a systematic mapping study

Mobile robots operate in various environments (e.g. aquatic, aerial, or terrestrial), they come in many diverse shapes and they are increasingly becoming parts of our lives. The successful engineering of mobile robotics systems demands the interdisciplinary collaboration of experts from different domains, such as mechanical and electrical engineering, artificial intelligence, and systems engineering. Research and industry have tried to tackle this heterogeneity by proposing a multitude of model-driven solutions to engineer the software of mobile robotics systems. However, there is no systematic study of the state of the art in model-driven engineering (MDE) for mobile robotics systems that could guide research or practitioners in finding model-driven solutions and tools to efficiently engineer mobile robotics systems. The paper is contributing to this direction by providing a map of software engineering research in MDE that investigates (1) which types of robots are supported by existing MDE approaches, (2) the types and characteristics of MRSs that are engineered using MDE approaches, (3) a description of how MDE approaches support the engineering of MRSs, (4) how existing MDE approaches are validated, and (5) how tools support existing MDE approaches. We also provide a replication package to assess, extend, and/or replicate the study. The results of this work and the highlighted challenges can guide researchers and practitioners from robotics and software engineering through the research landscape

Industry Best Practices in Robotics Software Engineering

Robotics software is pushing the limits of software engineering practice. The 3rd International Workshop on Robotics Software Engineering held a panel on "the best practices for robotic software engineering". This article shares the key takeaways that emerged from the discussion among the panelists and the workshop, ranging from architecting practices at the NASA/Caltech Jet Propulsion Laboratory, model-driven development at Bosch, development and testing of autonomous driving systems at Waymo, and testing of robotics software at XITASO. Researchers and practitioners can build on the contents of this paper to gain a fresh perspective on their activities and focus on the most pressing practices and challenges in developing robotics software today.Comment: 10 pages, 0 figure

Phylogenesis and Clinical Aspects of Pandemic 2009 Influenza A (H1N1) Virus Infection

During the spring of 2009, a new influenza A (H1N1) virus of swine origin emerged and spread worldwide causing a pandemic influenza. Here, 329 naso-pharyngeal swabs collected from patients with flu-like symptoms were analyzed by real-time PCR for the presence of H1N1 2009 pandemic virus. Twenty-five samples collected from immunocompetent and immunodepressed patients contained the H1N1 pandemic virus. Phylogenetic analysis of the hemagglutinin and neuraminidase genes showed no obvious differences in terms of similarity and/or homology between the sequences identified in immunocompetent individuals and those obtained from immunocompromised patients. Pre-existing clinical conditions may influence the outcome of H1N1 disease

Cytomegalovirus Glycoprotein B Genotype Distribution in Italian Transplant Patients.

Background: The cytomegalovirus (CMV) UL55 gene encodes for a glycoprotein implicated in virus pathogenesis. Based on UL55 polymorphism, CMV has been divided into 4 genotypes. Previous studies investigated the possible role of genotypes in the clinical outcome of infection in different categories of patients; however, few data are available, particularly in the transplant setting and Italian case records. Methods: Phylogenetic analysis through a maximum likelihood tree was used to evaluate the prevalence and distribution of CMV genotypes in whole blood specimens from 47 transplant patients and investigate the relation with demographic and clinical features. Results: Overall, 40.4% of patients were classified as single genotype (12.8% gB1, 23.4% gB2, 4.2% gB3); mixed genotypes were detected in 59.6%. Genotype 4 was detected only in mixed cases. In comparison to single genotypes, mixed genotypes were more frequently associated with a higher duration of DNA viremia and higher peak viral load. Conclusions: Mixed infections seem to be prevalent in Italian transplant patients; it is likely that mixed infections are more difficult to control by immunological response in comparison to single genotype infections. In this context, the genetic profile of infecting viruses and relation to clinical outcome should be investigated, also taking into account the CMV-specific cellular immune response