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Clustering scientific publications in an important problem in bibliometric research. We demonstrate how two software tools, CitNetExplorer and VOSviewer, can be used to cluster publications and to analyze the resulting clustering solutions. CitNetExplorer is used to cluster a large set of publications in the field of astronomy and astrophysics. The publications are clustered based on direct citation relations. CitNetExplorer and VOSviewer are used together to analyze the resulting clustering solutions. Both tools use visualizations to support the analysis of the clustering solutions, with CitNetExplorer focusing on the analysis at the level of individual publications and VOSviewer focusing on the analysis at an aggregate level. The demonstration provided in this paper shows how a clustering of publications can be created and analyzed using freely available software tools. Using the approach presented in this paper, bibliometricians are able to carry out sophisticated cluster analyses without the need to have a deep knowledge of clustering techniques and without requiring advanced computer skills.

As a result of the COVID-19 pandemic, many agile practitioners had to transition into a remote work environment. Despite remote work not being a new concept for agile software practitioners, the forced or recommended nature of remote work is new. This study investigates how the involuntary shift to remote work and how social restrictions imposed by the COVID-19 pandemic have affected agile software development (ASD), and how agile practitioners have been affected in terms of ways of working. An explanatory sequential mixed methods study was performed. Data were collected one year into the COVID-19 pandemic through a questionnaire with 96 respondents and in-depth semi-structured interviews with seven practitioners from seven different companies. Data were analyzed through Bayesian analysis and thematic analysis. The results show, in general, that the aspects of ASD that have been the most affected is communication and social interactions, while technical work aspects have not experienced the same changes. Moreover, feeling forced to work remotely has a significant impact on different aspects of ASD, e.g., productivity and communication, and industry practitioners’ employment of agile development and ways of working have primarily been affected by the lack of social interaction and the shift to digital communication. The results also suggest that there may be a group maturing debt when teams do go back into office, as digital communication and the lack of psychological safety stand in the way for practitioners’ ability to have sensitive discussions and progress as a team in a remote setting.

Development of models and dedicated numerical methods for dynamics in fractured rocks is an active research field, with research moving towards increasingly advanced process couplings and complex fracture networks. The inclusion of coupled processes in simulation models is challenged by the high aspect ratio of the fractures, the complex geometry of fracture networks, and the crucial impact of processes that completely change characteristics on the fracture-rock interface. This paper provides a general discussion of design principles for introducing fractures in simulators, and defines a framework for integrated modeling, discretization, and computer implementation. The framework is implemented in the open-source simulation software PorePy, which can serve as a flexible prototyping tool for multiphysics problems in fractured rocks. Based on a representation of the fractures and their intersections as lower-dimensional objects, we discuss data structures for mixed-dimensional grids, formulation of multiphysics problems, and discretizations that utilize existing software. We further present a Python implementation of these concepts in the PorePy open-source software tool, which is aimed at coupled simulation of flow and transport in three-dimensional fractured reservoirs as well as deformation of fractures and the reservoir in general. We present validation by benchmarks for flow, poroelasticity, and fracture deformation in porous media. The flexibility of the framework is then illustrated by simulations of non-linearly coupled flow and transport and of injection-driven deformation of fractures. All results can be reproduced by openly available simulation scripts.

We present MCMAS, a model checker for the verification of multi-agent systems. MCMAS supports efficient symbolic techniques for the verification of multi-agent systems against specifications representing temporal, epistemic and strategic properties. We present the underlying semantics of the specification language supported and the algorithms implemented in MCMAS, including its fairness and counterexample generation features. We provide a detailed description of the implementation. We illustrate its use by discussing a number of examples and evaluate its performance by comparing it against other model checkers for multi-agent systems on a common case study.

Understanding what drives environmentally protective or destructive behavior is important to the design and implementation of effective public policies to encourage people’s engagement in proenvironmental behavior (PEB). Research shows that a connection to nature is associated with greater engagement in PEB. However, the variety of instruments and methods used in these studies poses a major barrier to integrating research findings. We conducted a meta-analysis of the relationship between connection to nature and PEB. We identified studies through a systematic review of the literature and used Comprehensive Meta-Analysis software to analyze the results from 37 samples (n = 13,237) and to test for moderators. A random-effects model demonstrated a positive and significant association between connection to nature and PEB (r = 0.42, 95% CI 0.36, 0.47, p < 0.001). People who are more connected to nature reported greater engagement in PEB. Standard tests indicated little effect of publication bias in the sample. There was significant heterogeneity among the samples. Univariate categorical analyses showed that the scales used to measure connection to nature and PEB were significant moderators and explained the majority of the between-study variance. The geographic location of a study, age of participants, and the percentage of females in a study were not significant moderators. We found that a deeper connection to nature may partially explain why some people behave more proenvironmentally than others and that the relationship is ubiquitous. Facilitating a stronger connection to nature may result in greater engagement in PEB and conservation, although more longitudinal studies with randomized experiments are required to demonstrate causation. El entendimiento de los conductores del comportamiento de protección o destrucción ambiental es importante para el diseño e implementación de políticas públicas que fomenten la participación de las personas dentro del comportamiento a favor del ambiente (PEB, en inglés). Las investigaciones muestran que la conexión con la naturaleza está asociada con una mayor participación en el PEB. Sin embargo, la variedad de instrumentos y métodos que utilizados en estos estudios presentan una barrera importante para la integración de los resultados de las investigaciones. Realizamos un metaanálisis de la relación entre la conexión con la naturaleza y el PEB. Identificamos estudios por medio de una revisión sistemática de la literatura y utilizamos software de Metaanálisis Completo para analizar los resultados de 37 muestras (n = 13,237) y para examinar a los moderadores. Un modelo de efectos azarosos demostró una asociación positiva y significativa entre la conexión con la naturaleza y el PEB (r = 0.42, 95% CI 0.36, 0.47, p < 0.001). Las personas que están más conectadas con la naturaleza reportaron una mayor participación en el PEB. Las pruebas estándares indicaron un efecto menor del sesgo de publicación en la muestra. Hubo una heterogeneidad significativa entre las muestras. Los análisis univariados categóricos mostraron que las escalas usadas para medir la conexión con la naturaleza y el PEB fueron moderadores significativos y explicaron la mayoría de la varianza entre estudios. La ubicación geográfica de un estudio, la edad de los participantes, y el porcentaje de mujeres en un estudio no fueron moderadores significativos. Encontramos que una conexión más profunda con la naturaleza puede explicar parcialmente por qué algunas personas se comportan más a favor del ambiente que otras y que dicha relación es ubicua. La facilitación de una conexión más fuerte con la naturaleza puede resultar en una mayor participación en el PEB y en la conservación, aunque se requieren estudios más longitudinales con experimentos aleatorios para demostrar la causalidad 理解保护环境和破坏环境行为背后的驱动力,对于设计和实施有效的公共政策以鼓励人们参与环保行动 至关重要 。 已有研究表明,与自然的联系和环保行动参与度之间存在相关性 。 然而,这些研究使用了各种各样 的工具和方法,导致这些研究結果难以整合 。 因此,我们对人与自然的联系和环保行为之间的关系进行了荟萃 分析 。 我们通过系统文献综述筛选出相关研究,并用综合荟萃分析软件分析了 37 个样本 (n = 13,237) 的研究结 果以检验干涉变量 。 随机效应模型显示, 亲近自然与环保行为之间有显著的正相关关系 (r = 0.42, 95% CI 0.36, 0.47, p < 0.001) 。 更亲近自然的人自我报告的环保行为参与度也更高 。 标准检测分析表明,样本中的研究发表 偏差的影响很小,而各样本间存在显著的异质性 。 单变量分类分析结果显示,用于测定人与自然的联系和环保 行为的尺度是重要的干涉变量,解释了大部分的研究间差异 。 而研究地点 、 参与者年龄和性別都不是显著的干 涉变量 。 我们还发现,与自然更深层次的联系可能部分解释了为什么有些人更环保,而且其间的相关性普遍存 在 。 促进人与自然更紧密的联系或能推动人们更多地参与环保和保护行动,尽管仍需要更多包含随机实验的纵 向研究来证明因果关系 。

Software intensive systems play a crucial role in most, if not all, aspects of modern society. As such, both their sustainability and their role in supporting sustainable processes must be realized by design . To this aim, the architecture of software intensive systems should be designed to support sustainability goals; and measured to understand how effectively they do so. In this paper, we present the sustainability assessment framework (SAF) Toolkit—a set of instruments we developed to support software architects and design decision makers in modeling sustainability as a software quality property. The SAF Toolkit is the result of our experience gained in more than a decade of case studies in collaboration with industrial partners. We illustrate the toolkit with examples that come from some of such studies. We extract our lessons learned, our current research, and future plans to extend the SAF Toolkit for further architecture modeling and measurement.

Breaking with many established assumptions about how innovation ought to work, open source software projects offer eye-opening examples of novel innovation practices for students and practitioners in many fields. In this article we briefly review existing research on the open source phenomenon and discuss the utility of open source software research findings for many other fields. We categorize the research into three areas: motivations of open source software contributors; governance, organization, and the process of innovation in open source software projects; and competitive dynamics enforced by open source software. We introduce the articles in this special issue of Management Science on open source software, and show how each contributes insights to one or more of these areas.

With the increasing computing and networking capabilities, IoT devices and edge gateways have become part of a larger IoT–edge–cloud computing continuum, where processing and storage tasks are distributed across the whole network hierarchy, not concentrated only in the cloud. At the same time, this also introduced continuous delivery practices to the development of software components for network-connected gateways and sensing/actuating nodes. These devices are placed on end users’ premises and are characterized by continuously changing cyber-physical contexts, forcing software developers to maintain multiple application versions and frequently redeploy them on a distributed fleet of devices with respect to their current contexts. Doing this correctly and efficiently goes beyond manual capabilities and requires an intelligent and reliable automated solution. This paper describes a model-based approach to automatically assigning multiple software deployment plans to hundreds of edge gateways and connected IoT devices implemented in collaboration with a smart healthcare application provider. From a platform-specific model of an existing edge computing platform, we extract a platform-independent model that describes a list of target devices and a pool of available deployment plans. Next, we use constraint solving to automatically assign deployment plans to devices at once with respect to their specific contexts. The result is transformed back into the platform-specific model and includes a suitable deployment plan for each device, which is then consumed by our engine to deploy software components not only on edge gateways but also on their downstream IoT devices with constrained resources and connectivity. We validate the approach with a fleet deployment prototype integrated into a DevOps toolchain used by the partner application provider. Initial experiments demonstrate the viability of the approach and its usefulness in supporting DevOps for edge and IoT software development.

For the last ten years, software product line (SPL) tool developers have been facing the implementation of different variability requirements and the support of SPL engineering activities demanded by emergent domains. Despite systematic literature reviews identifying the main characteristics of existing tools and the SPL activities they support, these reviews do not always help to understand if such tools provide what complex variability projects demand. This paper presents an empirical research in which we evaluate the degree of maturity of existing SPL tools focusing on their support of variability modeling characteristics and SPL engineering activities required by current application domains. We first identify the characteristics and activities that are essential for the development of SPLs by analyzing a selected sample of case studies chosen from application domains with high variability. Second, we conduct an exploratory study to analyze whether the existing tools support those characteristics and activities. We conclude that, with the current tool support, it is possible to develop a basic SPL approach. But we have also found out that these tools present several limitations when dealing with complex variability requirements demanded by emergent application domains, such as non-Boolean features or large configuration spaces. Additionally, we identify the necessity for an integrated approach with appropriate tool support to completely cover all the activities and phases of SPL engineering. To mitigate this problem, we propose different road map using the existing tools to partially or entirely support SPL engineering activities, from variability modeling to product derivation.

Blended modeling aims to improve the user experience of modeling activities by prioritizing the seamless interaction with models through multiple notations over the consistency of the models. Inconsistency tolerance, thus, becomes an important aspect in such settings. To understand the potential of current commercial and open-source modeling tools to support blended modeling, we have designed and carried out a systematic study. We identify challenges and opportunities in the tooling aspect of blended modeling. Specifically, we investigate the user-facing and implementation-related characteristics of existing modeling tools that already support multiple types of notations and map their support for other blended aspects, such as inconsistency tolerance, and elevated user experience. For the sake of completeness, we have conducted a multivocal study, encompassing an academic review, and grey literature review. We have reviewed nearly 5000 academic papers and nearly 1500 entries of grey literature. We have identified 133 candidate tools, and eventually selected 26 of them to represent the current spectrum of modeling tools.