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Continuous deployment has been practiced for many years by companies developing web‐ and cloud‐based applications. To succeed with continuous deployment, these companies have a strong collaboration culture between the operations and development teams. In addition, these companies use AI, analytics, and big data to assist with time‐consuming postdeployment activities such as continuous monitoring and fault identification. Thus, the term AIOps has evolved to highlight the importance and difficulty of maintaining highly available applications in a complex and dynamic environment. In contrast, software‐intensive embedded systems often provide customer product‐related services, such as maintenance, optimization, and support. These services are critical for these companies as they provide significant revenue and increase customer satisfaction. Therefore, the objective of our study is to gain an in‐depth understanding of the impact of continuous deployment on product‐related services provided by software‐intensive embedded systems companies. In addition, we aim to understand how AIOps can support continuous deployment in the context of software‐intensive embedded systems. To address this objective, we conducted a case study at a large and multinational telecommunications systems provider focusing on the radio access network (RAN) systems for 4G and 5G networks. The company provides RAN products and three complementing services: rollout, optimization, and customer support. The results from the case study show that the boundaries between product‐related services become blurry with continuous deployment. In addition, product‐related services, which were conducted in sequence by independent projects, converge with continuous deployment and become part of the same project. Further, AIOps platforms play an important role in reducing costs and increasing postdeployment activities' efficiency and speed. These results show that continuous deployment has a profound impact on the software‐intensive system's provider service organization. The service organization becomes the connection between the R&D organization and the customer. In order to cope with the increased speed of releases, deployment and postdeployment activities need to be largely automated. AIOps platforms are seen as a critical enabler in managing the increasing complexity without increasing human involvement. [ABSTRACT FROM AUTHOR]

With digitalization and with technologies such as software, data, and artificial intelligence, companies in the embedded systems domain are experiencing a rapid transformation of their conventional businesses. While the physical products and associated product sales provide the core revenue, these are increasingly being complemented with service offerings, new data‐driven services, and digital products that allow for continuous value creation and delivery to customers. However, although there is significant research on digitalization and digital transformation, few studies highlight the specific needs of embedded systems companies and what it takes to transform from a traditional towards a digital company within business domains characterized by high complexity, hardware dependencies, and safety‐critical system functionality. In this paper, we capture the difference between what constitutes a traditional and a digital company and we detail the typical evolution path embedded systems companies take when transitioning towards becoming digital companies. [ABSTRACT FROM AUTHOR]

Digitalization is transforming industry to an extent that we have only seen the beginnings of. Across domains, companies experience rapid changes to their existing practices due to new technologies and new entrants that current businesses. While digitalization brings endless opportunities, it comes with challenges that require companies to strategically engage with partners in their surrounding ecosystems. In this paper, we study how companies in the embedded systems domain experience the process of transitioning from product‐based companies to businesses where software, data, and artificial intelligence (AI) play an increasingly important role. To manage this, these companies need to evolve their existing ecosystems while at the same time create new ecosystems around new technologies. This involves maintaining existing technologies such as mechanics and electronics while at the same time expanding these with software, data, and AI. We provide a strategic decision framework that helps software‐intensive embedded systems companies to successfully navigate the digital transformation. We do this in two steps. First, we present three models that provide the technical content of the strategic decision framework. Second, we provide an overview of the strategic alternatives that incumbents and new entrants have available when existing technologies are commoditizing and new technologies are introduced. [ABSTRACT FROM AUTHOR]

A known problem in large software companies is to balance the prioritization of short-term and long-term business goals. As an example, architecture suboptimality (Architectural Technical Debt), incurred to deliver fast, might hinder future feature development. However, some technical debt generates more interest to be paid than other. We conducted a multi-phase, multiple-case embedded case study comprehending 9 sites at 6 large international software companies. We have investigated which architectural technical debt items generate more interest , how the interest occurs during software development and which costly extra-activities are triggered as a result. We presented a taxonomy of the most dangerous items identified during the qualitative investigation and a model of their effects that can be used for prioritization, for further investigation and as a quality model for extracting more precise and context-specific metrics. We found that some architectural technical debt items are contagious, causing the interest to be not only fixed, but potentially compound, which leads to the hidden growth of interest (possibly exponential). We found important factors to be monitored to refactor the debt before it becomes too costly. Instances of these phenomena need to be identified and stopped before the development reaches a crises. [ABSTRACT FROM AUTHOR]

Artificial intelligence is increasingly becoming important to businesses because many companies have realized the benefits of applying machine learning (ML) and deep learning (DL) in their operations. ML and DL have become attractive technologies for organizations looking to automate repetitive tasks to reduce manual work and free up resources for innovation. Unlike rule‐based automation, typically used for standardized and predictable processes, machine learning, especially deep learning, can handle more complex tasks and learn over time, leading to greater accuracy and efficiency improvements. One of such promising applications is to use AI to reduce manual engineering work. This paper discusses a particular case within McDermott where the research team developed a DL model to do a quality check of complex blueprints. We describe the development and the final product of this case—AI‐based software for the engineering, procurement, and construction (EPC) industry that helps to find the design mistakes buried inside very complex engineering drawings called piping and instrumentation diagrams (P&IDs). We also present a cost‐benefit analysis and potential scale‐up of the developed software. Our goal is to share the successful experience of AI‐based product development that can substantially reduce the engineering hours and, therefore, reduce the project's overall costs. The developed solution can also be potentially applied to other EPC companies doing a similar design for complex installations with high safety standards like oil and gas or petrochemical plants because the design errors it captures are common within this industry. It also could motivate practitioners and researchers to create similar products for the various fields within engineering industry. [ABSTRACT FROM AUTHOR]

Recently, business ecosystems have been recognized as one of the most interesting phenomenon in software engineering research. Companies experience a paradigm shift where product development and innovation is moving outside the boundaries of the firm and where networks of stakeholders join forces to co-create value. While there is prominent research focusing on the managerial perspective of business ecosystems, few studies provide strategic guidance for how to intentionally manage the different ecosystems that companies operate in. Therefore, and on the basis of multicase study research, we provide empirical evidence on the challenges that software-intensive companies experience in relation to the different types of business ecosystems they operate in. We conduct a 'state-of-the-art' literature review to identify strategies that are used to manage ecosystem engagements, and we develop a conceptual model in which we identify strategies for managing the innovation ecosystem, the differentiating ecosystem, and the commoditizing ecosystem. By categorising the different strategies in relation to the different types of ecosystems for which they are valid, the 'three-layer ecosystem strategy model' provides comprehensive support for strategy selection. We validate the use of the identified strategies in 6 software-intensive case companies, and we provide empirical insights on the 'relevance' and the 'desired use' of these strategies as experienced by the case companies. [ABSTRACT FROM AUTHOR]

Many consumer electronics firms are adopting an ecosystem-centric approach for supporting third-party applications. In an emerging market, a consumer electronics firm may need to create a new ecosystem or adopt a newly developed platform, both which has significant commercial and technical implications. In this paper we identify three types of ecosystems that are used today: vertically integrated hardware/software platforms, closed-source software platforms, and open-source software platforms. We introduce a first step towards a multi-criteria decision support method, which determines what type of ecosystem is most suitable for a specific product category from a software engineering perspective. We use this method to analyze a wide range of consumer electronics products. The analysis shows that the vertically integrated platform type is most suitable for product with a high degree of innovation, and open-source software platforms are more suitable when a large amount of variants are needed. The closed-source software platform type is less suitable for most types of consumer electronics devices. This first step towards a full-fledged decision support method can be used by platform owners to decide whether their platform can also be successfully transferred to another product type. [ABSTRACT FROM AUTHOR]

In strategic management, the term meta-organisation is discussed as a network of firms and individuals in which members coexist, collaborate and evolve through a set of relationships and together form a larger organism. We focus on the meta-organisation form of an ecosystem in the IT industry, which often is based around a technical architecture or platform. Studies often discuss one network and selected members in such a network, but few mention that firms can work in multiple ecosystems and need to apply divergent engagement models. We study how firms engage in multiple ecosystems through three qualitative case studies. The article contributes with the following: (1) firms often operate in multiple ecosystems for which they need to dynamically adapt their engagement strategy. (2) Firms are striving to balance between strategic divergences: power versus symbiosis and a collaborative approach versus a competitive approach. [ABSTRACT FROM AUTHOR]

This article presents the state of the art and practice in system and software variability. It describes the trends driving the increasing importance of variability management, proposes a research agenda, and provides an overview of the articles in this special issue. The Web extra at http://youtu.be/80DAUGahNAY is an audio recording of Davide Falessi speaking with Guest Editors Rafael Capilla and Rich Hilliard about the state of the art and practice in system and software variability. [ABSTRACT FROM PUBLISHER]

Artificial intelligence (AI) and the use of machine learning (ML) and deep learning (DL) technologies are becoming increasingly popular in companies. These technologies enable companies to leverage big quantities of data to improve system performance and accelerate business development. However, despite the appeal of ML/DL, there is a lack of systematic and structured methods and processes to help data scientists and other company roles and functions to develop, deploy and evolve models. In this paper, based on multi‐case study research in six companies, we explore practices and challenges practitioners experience in developing ML/DL models as part of large software‐intensive embedded systems. Based on our empirical findings, we derive a conceptual framework in which we identify three high‐level activities that companies perform in parallel with the development, deployment and evolution of models. Within this framework, we outline activities, iterations and triggers that optimize model design as well as roles and company functions. In this way, we provide practitioners with a blueprint for effectively integrating ML/DL model development into the business to achieve better results than other (algorithmic) approaches. In addition, we show how this framework helps companies solve the challenges we have identified and discuss checkpoints for terminating the business case. [ABSTRACT FROM AUTHOR]

Continuous experimentation (CE) refers to a set of practices used by software companies to rapidly assess the usage, value, and performance of deployed software using data collected from customers and systems in the field using an experimental methodology. However, despite its increasing popularity in developing web‐facing applications, CE has not been studied in the development process of business‐to‐business (B2B) mission‐critical systems. By observing the CE practices of different teams, with a case study methodology inside Ericsson, we were able to identify the different practices and techniques used in B2B mission‐critical systems and a description and classification of the four possible types of experiments. We present and analyze each of the four types of experiments with examples in the context of the mission‐critical long‐term evolution (4G) product. These examples show the general experimentation process followed by the teams and the use of the different CE practices and techniques. Based on these examples and the empirical data, we derived the HURRIER process to deliver high‐quality solutions that the customers value. Finally, we discuss the challenges, opportunities, and lessons learned from applying CE and the HURRIER process in B2B mission‐critical systems. [ABSTRACT FROM AUTHOR]

Increased system complexity has historically been treated as an inevitable consequence of architecture evolution over time. The three-layer product model offers an innovative framework for managing system growth that encourages greater efficiency, nimbler responsiveness, and more opportunities for innovation during all stages of the software development life cycle. [ABSTRACT FROM PUBLISHER]

Many successful software companies use social networking as a way to improve the services or products they provide. To gain an understanding of the role social networking plays in today's software development world, the guest editors of the January/February 2013 issue conducted semistructured interviews with leaders from four successful companies: Brian Doll, an engineer who manages GitHub's marketing; Doug Laundry, a principal group program manager at Microsoft; David Fullerton, vice president of engineering at Stack Exchange; and Robert Hughes, the president and chief operating officer of TopCoder. The first Web extra at http://try.github.com is a video of Joel Spolsky discussing the structure, software, technology, and culture of Stack Exchange. The second Web extra at http://blip.tv/play/gvUBgqLbRgI.html is a video of Matthew McCullough and Tim Berglund demonstrating how Git not only incorporates the best features of existing source control systems but also includes unique distributed capabilities that make version control commands available without connectivity, allowing you to choose when to interact with a network. The third Web extra at http://blip.tv/play/gvUBgqLbRgI.html is a video of Matthew McCullough and Tim Berglund demonstrating how to leverage Git's powerful yet underused advanced features. The last Web extra at http://youtu.be/SK6TBI1bNLI is a video of Thomas Baden, Chief Information Officer, State of Minnesota, Department of Human Services, describing the experience of working on the TopCoder Platform and with the members of the TopCoder Community. [ABSTRACT FROM PUBLISHER]

Dynamic software product lines address many of the challenges of building highly configurable software and use runtime variability mechanisms to support automatic decision making. [ABSTRACT FROM PUBLISHER]

The article focuses on key problems that occur in successful software product lines (SPL) over extended periods of time. These problems are coordination overhead, slow release cycles, and high system-level error density. Coordination overhead happens when there are decreasing amounts of time dedicated to add value to the SPL's products and shared assets. Slow release cycles means the release frequency slows to a point below the market speed. It is noted that discovery of errors during the integration stage causes high system-level error density.

Scenario profiles are used increasingly often for the assessment of quality attributes during the architectural design of software systems. However, the definition of scenario profiles is subjective and no data is available on the effects of individuals on scenario profiles. In this paper we present the design, analysis and results of a controlled experiment on the effect of individuals on scenario profiles, so that others can replicate the experiments on other projects and people. Both scenario profiles created by individuals and by groups are studied. The findings from the experiment showed that groups with prepared members proved to be the best method for creating scenario profiles. Unprepared groups did not perform better than individuals when creating scenario profiles. [ABSTRACT FROM AUTHOR]

Over the past decade, the advent of social networking has fundamentally altered the landscape of how software is used, designed, and developed. It has expanded how communities of software stakeholders communicate, collaborate, learn from, and coordinate with one another. The guest editors of this special issue describe both the field and the articles they selected for it. [ABSTRACT FROM PUBLISHER]

The article discusses service-orientation for mobile computing devices. Increasingly such devices are becoming integral to firms' information technology (IT) infrastructures. Extending a firm's common user interface across these devices poses challenges, including accommodation of varying technical capabilities among mobile devices and their rapid technological obsolescence. Three possible approaches are a client-server method with native client, client-server with a Java client, and the use of browser-based clients on mobile devices. Each has its benefits and drawbacks.

Today, companies operate in business ecosystems where they collaborate, compete, share, and learn from others with benefits such as to present more attractive offerings and sharing innovation costs. With ecosystems being the new way of operating, the ability to strategically reposition oneself to increase or shift power balance is becoming key for competitive advantage. However, companies run into a number of traps when trying to realize strategical changes in their ecosystems. In this paper, we identify 5 traps that companies fall into. First, the "descriptive versus prescriptive trap" is when companies assume that current boundaries between partners are immutable. Second, the "assumptions trap" is when powerful ecosystem partners assume that they understand what others regard as value‐adding without validating their assumptions. Third, the "keeping it too simple trap" is when companies overlooks the effort required to align interests. Fourth, the "doing it all at once trap" is when companies disrupt an ecosystem assuming that all partners can change direction at the same time. Finally, the "planning trap" is when companies are unable to move forward without a complete plan. We provide empirical evidence for each trap, and we propose an ecosystem engagement process for how to avoid falling into these. Key findings: Repositioning in the ecosystem is fraud with risks. We identify the key traps that companies fall into, as well as provide guidance on how to avoid them when transitioning from current to desired state by shifting power between ecosystem partners. [ABSTRACT FROM AUTHOR]

Background: Unintentional falls are common among the elderly and given the expected increase of the aging population, these falls contribute to a high number of admissions to the emergency department. Relatively low-energy trauma mechanisms can lead to serious injuries in the elderly, with contributing factors being comorbidities, medication use and degenerative abnormalities. Case presentation: A 94-year-old female suffered an unintentional fall at home. Upon arrival of the ambulance at her house she was hemodynamically stable and mobilized to the gurney with assistance. During primary survey at the emergency department, her blood pressure and oxygen saturation decreased, she was not able to move her legs anymore and lost consciousness. A full-body CTA was performed, which showed a fracture through the vertebral body of L2 with significant dislocation and a large active bleeding of the corpus, extending to the retroperitoneum and the epidural space. Despite resuscitation, her vital signs deteriorated and given the severe abnormalities on CTA, it was decided to discontinue further treatment, after which she deceased. The performed CTA and an x-ray from 2016 suggested diffuse idiopathic skeletal hyperostosis, which might have contributed to the severity and instability of the vertebral fracture. Mobilization after the fall might have increased the dislocation of the fracture. The use of oral anticoagulants worsened the subsequent bleeding and the extension to the epidural space caused the paralysis of the legs. Conclusions: It is important to be aware of the possible serious consequences of unintentional falls in the elderly population and to provide strict immobilization of the spinal column until proper imaging. [ABSTRACT FROM AUTHOR]

Large software companies need to support continuous and fast delivery of customer value both in the short and long term. However, this can be hindered if both the evolution and maintenance of existing systems are hampered by Technical Debt. Although a lot of theoretical work on Technical Debt has been produced recently, its practical management lacks empirical studies. In this paper, we investigate the state of practice in several companies to understand what the cost of managing TD is, what tools are used to track TD, and how a tracking process is introduced in practice. We combined two phases: a survey involving 226 respondents from 15 organizations and an in-depth multiple case study in three organizations including 13 interviews and 79 Technical Debt issues. We selected the organizations where Technical Debt was better tracked in order to distill best practices. We found that the development time dedicated to managing Technical Debt is substantial (an average of 25% of the overall development), but mostly not systematic: only a few participants (26%) use a tool, and only 7.2% methodically track Technical Debt. We found that the most used and effective tools are currently backlogs and static analyzers. By studying the approaches in the companies participating in the case study, we report how companies start tracking Technical Debt and what the initial benefits and challenges are. Finally, we propose a Strategic Adoption Model for the introduction of tracking Technical Debt in software organizations. [ABSTRACT FROM AUTHOR]

Runtime variability offers a good choice for many systems that experience dynamic changes in their quality and context. [ABSTRACT FROM PUBLISHER]

Software ecosystems are considered the natural evolution of software product lines. A software ecosystem provides a (software) product within a particular business and organizational context that supports the exchange of activities and services within a domain. However, the increasing degree of autonomy demanded by software ecosystems is elevating the system response to end users, while the existing software ecosystem architectures are not well prepared to deal with the dynamicity of context changes and autonomous behavior needs. In order to provide a transition toward an increased level of autonomy, in this article, we introduce the notion of autonomous dynamic ecosystems as representative of those software ecosystems able to support dynamic, smart, and autonomous features demanded by modern software systems. In this work, we further investigate and provide evidence of four industrial examples that have fully embodied the principles of autonomous dynamic ecosystems, and we characterize the main features and technology requirements of this kind of new ecosystems. [ABSTRACT FROM AUTHOR]

Background& Aim: Sarcopenia is defined as a loss of muscle mass and function, which can be caused by normal ageing or factors such as physical inactivity. Severe health consequences caused by sarcopenia highlight the need for early identification. Computed Tomography (CT) imaging, often mentioned as the gold standard due to its accuracy, is costly and not routinely performed in daily clinical care. Ultrasound of the rectus femoris, however, is low in costs and easily accessible. The aim is to present the current and most recent literature regarding the diagnostic value of ultrasound measurements of the rectus femoris for the diagnosis of sarcopenia in adults.Methods: The databases PubMed and Web of Science were used to search for studies comparing ultrasound of the rectus femoris with a reference test to diagnose sarcopenia in adults. The quality of the final eligible studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies, version 2, tool (QUADAS-2).Results: Six studies were included in this systematic review. The muscle thickness and cross-sectional area of the rectus femoris were assessed and compared with the reference tests CT, Dual-Energy X-ray Absorptiometry (DXA), and Bioelectrical Impedance Analysis (BIA). Half of the studies had a low risk of bias on all QUADAS-2 domains. Three studies reported statistical significant outcomes and diagnostic values ranging from 60 to 81% sensitivity and 51 to 94% specificity.Conclusions: Ultrasound of the rectus femoris muscle to diagnose sarcopenia has been shown to be a promising method in multiple clinical populations. However, there were some limitations such as a high methodological heterogeneity. Future research should develop standardized protocols and determine clear cut-off values to allow for a better implementation of ultrasound in clinical practice. [ABSTRACT FROM AUTHOR]

Introduction: Sarcopenia is a muscle disease that involves loss of muscle strength and physical function and is associated with adverse health effects. Even though sarcopenia has attracted increasing attention in the literature, many research findings have not yet been translated into clinical practice. In this article, we aim to validate a deep learning neural network for automated segmentation of L3 CT slices and aim to explore the potential for clinical utilization of such a tool for clinical practice.Materials and Methods: A deep learning neural network was trained on a multi-centre collection of 3413 abdominal cancer surgery subjects to automatically segment muscle, subcutaneous and visceral adipose tissue at the L3 lumbar vertebral level. 536 Polytrauma subjects were used as an independent test set to show generalizability. The Dice Similarity Coefficient was calculated to validate the geometric similarity. Quantitative agreement was quantified using Bland-Altman's Limits of Agreement interval and Lin's Concordance Correlation Coefficient. To determine the potential clinical usability, randomly selected segmentation images were presented to a panel of experienced clinicians to rate on a Likert scale.Results: Deep learning results gave excellent agreement versus a human expert operator for all of the body composition indices, with Concordance Correlation Coefficient for skeletal muscle index of 0.92, Skeletal muscle radiation attenuation 0.94, Visceral Adipose Tissue index 0.99 and Subcutaneous Adipose Tissue Index 0.99. Triple-blinded visual assessment of segmentation by clinicians correlated only to the Dice coefficient, but had no association to quantitative body composition metrics which were accurate irrespective of clinicians' visual rating.Conclusion: A deep learning method for automatic segmentation of truncal muscle, visceral and subcutaneous adipose tissue on individual L3 CT slices has been independently validated against expert human-generated results for an enlarged polytrauma registry dataset. Time efficiency, consistency and high accuracy relative to human experts suggest that quantitative body composition analysis with deep learning should is a promising tool for clinical application in a hospital setting. [ABSTRACT FROM AUTHOR]

Background: The prevalence of inflicted femur fractures in young children varies (1.5-35.2%), but these data are based on small retrospective studies with high heterogeneity. Age and mobility of the child seem to be indicators of inflicted trauma.Objective: This study describes other factors associated with inflicted and neglectful trauma that can be used to distinguish inflicted and neglectful from accidental femur fractures.Materials and Methods: This retrospective study included children (0-6 years) who presented with an isolated femur fracture at 1 of the 11 level I trauma centers in the Netherlands between January 2010 and January 2016. Outcomes were classified based on the conclusions of the Child Abuse and Neglect teams or the court. Cases in which conclusions were unavailable and there was no clear accidental cause were reviewed by an expert panel.Results: The study included 328 children; 295 (89.9%) cases were classified as accidental trauma. Inflicted trauma was found in 14 (4.3%), while 19 (5.8%) were cases of neglect. Indicators of inflicted trauma were age 0-5 months (29%, positive likelihood ratio [LR +] 8.35), 6-12 months (18%, LR + 5.98) and 18-23 months (14%, LR + 3.74). Indicators of neglect were age 6-11 months (18%, LR + 4.41) and age 18-23 months (8%, LR + 1.65). There was no difference in fracture morphology among groups.Conclusion: It is unlikely that an isolated femur fracture in ambulatory children age > 24 months is caused by inflicted trauma/neglect. Caution is advised in children younger than 24 months because that age is the main factor associated with inflicted trauma/neglect and inflicted femur fractures. [ABSTRACT FROM AUTHOR]

The adoption of Agile Software Development in large companies is a recent phenomenon of great interest both for researchers and practitioners. Although intra-team interaction is well supported by established agile practices, the critical interaction between the agile team and other parts of the organization is still unexplored in literature. Such interactions slow down the development, hindering the achievement of business goals based on speed: short time to market, quick replication of products of a product-line, and reaction time for product evolution. We have employed a two-year long multiple-case case-study, collecting data through interviews and a survey in three large companies developing embedded software. Through a combination of qualitative and quantitative analysis, we have found strong evidence that interaction challenges between the development team and other groups in the organization hinder speed and are widespread in the organizations. This paper also identifies current practices in use at the studied companies and provides detailed guidelines for novel solutions in the investigated domain. Such practices are called boundary-spanning activities in information system research and coordination theory. We present a comparison between large embedded software companies employing agile and developing a line of products based on reused assets and agile companies developing pure software. We highlight specific contextual factors and areas where novel spanning activities are needed for mitigating the interaction challenges hindering speed. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In large-scale software development, there is typically a conflict between being responsive to individual customers, while at the same time achieving scale in terms of delivering a high number of features to a large customer base. Most often, organizations focus on scale and individual customer requests are viewed as problematic since they add complexity to product variation and version control. Here, we explore the use of customer-specific teams as a means to address this conflict. First, we verify the use of customer-specific teams as successful for improving customer responsiveness, customer satisfaction and feature quality through a case study at Ericsson. Second, we identify three approaches for how to organize feature development, and recommendations on how software development companies can efficiently use these to improve their practices. Third, we observe new business opportunities that arise when using customer-specific teams. [ABSTRACT FROM PUBLISHER]

We present the results of two case studies we conducted at Baan in the Netherlands. At the time of conducting the case studies, Baan was part of Invensys plc. (Baan is now owned by SSA Global Technologies.) In these case studies we investigated how companies identify design erosion and address this in their software, a practice we call ‘design preservation’. In this study, we selected two sub-systems in Baan products that had recently been subjected to extensive maintenance activities because they were eroded. In this paper, we analyze the problems these systems had, how Baan identified that these systems were problematic, and the remedies that were used to address the problems. In addition to confirming some of our earlier conclusions, we have been able to extract some common causes for design erosion problems as well as a number of recommended design preservation practices, which, at least for Baan, have proven to be very effective in strengthening design preservation. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Purpose: Between 0.1—3% of injured children who present at a hospital emergency department ultimately die as a result of their injuries. These events are typically reported as unnatural causes of death and may result from either accidental or non-accidental trauma (NAT). Examples of the latter include trauma that is inflicted directly or resulting from neglect. Although consultation with a forensic physician is mandatory for all deceased children, the prevalence of fatal inflicted trauma or neglect among children is currently unclear. Methods: This is a retrospective study that included children (0–18 years) who presented and died at one of the 11 Level I trauma centers in the Netherlands between January 1, 2014, and January 1, 2019. Outcomes were classified based on the conclusions of the Child Abuse and Neglect team or those of forensic pathologists and/or the court in cases referred for legally mandated autopsies. Cases in which conclusions were unavailable and there was no clear accidental cause of death were reviewed by an expert panel. Results: The study included 175 cases of childhood death. Seventeen (9.7%) of these children died due to inflicted trauma (9.7%), 18 (10.3%) due to neglect, and 140 (80%) due to accidents. Preschool children (< 5 years old) were significantly more likely to present with injuries due to inflicted trauma and neglect compared to older children (44% versus 6%, p < 0.001, odds ratio [OR] 5.80, 95% confidence interval [CI] 2.66–12.65). Drowning accounted for 14 of the 18 (78%) pediatric deaths due to neglect, representing 8% of the total cases. Postmortem radiological studies and autopsies were performed on 37 (21%) of all cases of childhood death. Conclusion: One of every five pediatric deaths in our nationwide Level I trauma center study was attributed to NAT; 44% of these deaths were the result of trauma experienced by preschool-aged children. A remarkable number of fatal drownings were due to neglect. Postmortem radiological studies and autopsies were performed in only one-fifth of all deceased children. The limited use of postmortem investigations may have resulted in missed cases of NAT, which will result in an overall underestimation of fatal NAT experienced by children. [ABSTRACT FROM AUTHOR]

Based on 25 interviews with participants from four case study companies that develop large‐scale software embedded systems, this paper presents the Test Activity Stakeholders (TAS) model. The TAS model shows how the continuous integration and delivery pipeline can be designed to include test activities that support four stakeholder interests: "Check changes," "Secure stability," "Measure progress," and "Verify compliance." The model is developed to show how each of the stakeholder interests are best supported by unit/component tests or system tests, by automated testing or manual testing and by tests executed in simulated environments or on real hardware. The TAS model may serve as a starting point for companies when evaluating and designing their continuous integration and delivery pipeline. The validation of the TAS model included twelve individuals from three case study companies. The validation showed that the TAS model is actionable and useful in practice, enabling the identification of stakeholders and showing where improvement efforts should be focused in order to support all stakeholder interests in the continuous integration and delivery pipeline. The Test Activity Stakeholders (TAS) model shows how the continuous integration and delivery pipeline can be designed to include test activities that support four stakeholder interests: "Check changes," "Secure stability," "Measure progress," and "Verify compliance." The validation of the TAS model showed that the model is actionable and useful in practice, showing where improvement efforts should be focused in order to support all stakeholder interests in the continuous integration and delivery pipeline. [ABSTRACT FROM AUTHOR]

An introduction is presents in which the editor discusses various reports within the issue on topics including use of Bayesian networks for assisting continuous improvement of Scrum projects, portfolio management and adoption level of scaled agile development.

Microwave-based sensing for tissue analysis is recently gaining interest due to advantages such as non-ionizing radiation and non-invasiveness. We have developed a set of transmission sensors for microwave-based real-time sensing to quantify muscle mass and quality. In connection, we verified the sensors by 3D simulations, tested them in a laboratory on a homogeneous three-layer tissue model, and collected pilot clinical data in 20 patients and 25 healthy volunteers. This report focuses on initial sensor designs for the Muscle Analyzer System (MAS), their simulation, laboratory trials and clinical trials followed by developing three new sensors and their performance comparison. In the clinical studies, correlation studies were done to compare MAS performance with other clinical standards, specifically the skeletal muscle index, for muscle mass quantification. The results showed limited signal penetration depth for the Split Ring Resonator (SRR) sensor. New sensors were designed incorporating Substrate Integrated Waveguides (SIW) and a bandstop filter to overcome this problem. The sensors were validated through 3D simulations in which they showed increased penetration depth through tissue when compared to the SRR. The second-generation sensors offer higher penetration depth which will improve clinical data collection and validation. The bandstop filter is fabricated and studied in a group of volunteers, showing more reliable data that warrants further continuation of this development. [ABSTRACT FROM AUTHOR]

Manual segmentation of muscle and adipose compartments from computed tomography (CT) axial images is a potential bottleneck in early rapid detection and quantification of sarcopenia. A prototype deep learning neural network was trained on a multi-center collection of 3413 abdominal cancer surgery subjects to automatically segment truncal muscle, subcutaneous adipose tissue and visceral adipose tissue at the L3 lumbar vertebral level. Segmentations were externally tested on 233 polytrauma subjects. Although after severe trauma abdominal CT scans are quickly and robustly delivered, with often motion or scatter artefacts, incomplete vertebral bodies or arms that influence image quality, the concordance was generally very good for the body composition indices of Skeletal Muscle Radiation Attenuation (SMRA) (Concordance Correlation Coefficient (CCC) = 0.92), Visceral Adipose Tissue index (VATI) (CCC = 0.99) and Subcutaneous Adipose Tissue Index (SATI) (CCC = 0.99). In conclusion, this article showed an automated and accurate segmentation system to segment the cross-sectional muscle and adipose area L3 lumbar spine level on abdominal CT. Future perspectives will include fine-tuning the algorithm and minimizing the outliers. [ABSTRACT FROM AUTHOR]

Sarcopenia is related to adverse outcomes in various populations. However, little is known about the prevalence of sarcopenia in polytrauma patients. Identifying the number of patients at risk of adverse outcome will increase awareness to prevent further loss of muscle mass. We utilized data from a regional prospective trauma registry of all polytrauma patients presented between 2015 and 2019 at a single level-I trauma center. Subjects were screened for availability of computed tomography (CT)-abdomen and height in order to calculate skeletal mass index, which was used to estimate sarcopenia. Additional parameters regarding clinical outcome were assessed. Univariate analysis was performed to identify parameters related adverse outcome and, if identified, entered in a multivariate regression analysis. Prevalence of sarcopenia was 33.5% in the total population but was even higher in older age groups (range 60–79 years), reaching 82 % in patients over 80 years old. Sarcopenia was related to 30-day or in-hospital mortality (p = 0.032), as well as age (p < 0.0001), injury severity score (p = 0.026), and Charlson comorbidity index (p = 0.001). Log rank analysis identified sarcopenia as an independent predictor of 30-day mortality (p = 0.032). In conclusion, we observed a high prevalence of sarcopenia among polytrauma patients, further increasing in older patients. In addition, sarcopenia was identified as a predictor for 30-day mortality, underlining the clinical significance of identification of low muscle mass on a CT scan that is already routinely obtained in most trauma patients. [ABSTRACT FROM AUTHOR]

Companies need to know how much value their ideas deliver to customers. One of the most powerful ways to accurately measure this is by conducting online controlled experiments (OCEs). To run experiments, however, companies need to develop strong experimentation practices as well as align their organization and culture to experimentation. The main objective of this paper is to demonstrate how to run OCEs at large scale using the experience of companies that succeeded in scaling. Based on case study research at Microsoft, Booking.com, Skyscanner, and Intuit, we present our main contribution—The Experiment Growth Model. This four‐stage model addresses the seven critical aspects of experimentation and can help companies to transform their organizations into learning laboratories where new ideas can be tested with scientific accuracy. Ultimately, this should lead to better products and services. [ABSTRACT FROM AUTHOR]