Organization Global Software Development Challenges of Software Product Quality

Leaders of global software development (GSD) processes in organizations have been confronting low software product quality. Managers of these processes have faced challenges that have been affecting customer satisfaction and that have resulted in negative social impacts on public safety, business financial performance, and global economic stability. The purpose of this qualitative exploratory multiple case study was to discover a common understanding shared by managers in Canadian GSD organizations of how to meet software product quality goals and enhance customer satisfaction. The conceptual framework for the study was based on Deming\u27s 14 principles of quality management. The purposeful sample included 30 knowledgeable participants who worked in Canada as GSD managers. Semistructured interviews conducted through telephone and audioconference tools, along with the review of related documents, were used to gather data. Eight themes emerged from the data analysis: developing a clear purpose and work principles, improving processes and employee skills, developing adequate personnel management strategies, promoting autonomy and personal worker development, formulating life cycle and development techniques, identifying challenges, formulating solutions, and focusing on product quality. The research findings have implications for positively influencing social change through the provision of methods and process knowledge to GSD organizational leaders. This information consists of best management and industry practices that can be applied to achieve software product quality and customer satisfaction, create management systems, maintain a competitive advantage, and prevent global software development project failures

Enterprise Resource Planning Implementation in One Government Agency

Ineffective enterprise resource planning (ERP) implementation strategies can have a negative impact on business competitive advantage. Business leaders who struggle to maintain global operations and audit readiness are at high risk of failure. Grounded in the general systems theory, the purpose of this qualitative single case study was to explore the strategies business leaders used to promote an awareness of the effects of performance on competitive advantage. The participants comprised of 22 business leaders on a military base in the state of Washington who effectively used ERP systems to increase global operations, audit readiness, and maximize competitive advantage. Data were collected from semistructured interviews, observer-as-participant observations, and company documents. Yin’s five step process was used to analyze the data. Four themes emerged: crucial ERP project planning, ERP system implementation strategies, senior business leader support, and ineffective strategies affecting ERP system performance. Based on the findings of this study, a key recommendation is business leaders should tailor their ERP system implementation strategies to include a cost-benefit analysis for hiring professional ERP systems trainers. The implications for positive social change include the potential to provide business leaders with an in-depth understanding of ERP system implementation strategies to effectively tailor their specific implementation strategies and support the economic stability of their employees

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

Infrastructure as Code Strategies and Benefits in Cloud Computing

Hybrid and multicloud infrastructure implementation without automation and versioning strategy can negatively impact organizations’ productivity. Organization leaders must ensure that infrastructures are implemented using the infrastructure as code (IaC) strategy because implementation solutions, including automated and DevOps procedures, provide assets for repeatable infrastructure implementation use cases. Grounded in the disruptive innovation theory, the purpose of this qualitative pragmatic inquiry study was to explore strategies solution architects use to implement IaC architecture using repeatable assets with DevOps procedures in cloud computing. The participants were seven solution architects in the information technology (IT) industry within the United States who have successfully implemented IaC in hybrid and multicloud within the past 3 years in cloud computing with DevOps procedures. Data were collected using semi-structured interviews, a focus group, and IT industry documents. The data analysis processes were analyzed using thematic analysis Eight themes emerged: IaC benefits, IaC cloud computing models, IaC cloud service providers, IaC configuration best practices, IaC DevOps practices, IaC implementation tools, IaC Kubernetes platforms, and IT infrastructure design practices. A specific recommendation is for organizational leaders to implement the IaC approach as it offers sustaining and disruptive innovation benefits, in addition, space agencies such as the National Aeronautics and Space Administration (NASA), European Space Agency (ESA), et al., could use this study in their mission infrastructures. The implications for positive social change include the potential to make the user application offerings affordable as it supports IT innovation in hybrid and multicloud globally

A novel framework for user-centered research data management

Recent Open Data policies have led to a large-scale demand for research data repositories. Research data repositories are expected to function as an important instrument for research data preservation as well as for research collaboration and dissemination, helping to realize the advantages that motivated those policies. Existing research data management (RDM) systems and infrastructure, of which research data repositories form an important component, are currently inadequate to support and further this vision. Research data are complex compound objects, and their use, and also the mode of interacting with them, differs considerably from those of manuscript documents (e.g. research publications). This research proposes a holistic framework for RDM system design that expressly takes into account the needs of system users as well as the peculiar requirements of research data, to develop well-functioning systems. It demonstrates the development process of a simple prototype of a user-centered, data-conscious RDM system, called DataFinder, from the earliest stages of requirements gathering to requirements analyses, design, development, and evaluation. Importance is given as much to the final deliverable (i.e. DataFinder) as to the process of attaining it, since a substantial part of the research preceded the former, and the findings garnered along the way will likely prove useful for purposes of which system design forms only one

Decision Support Systems

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference

Technology and Testing

From early answer sheets filled in with number 2 pencils, to tests administered by mainframe computers, to assessments wholly constructed by computers, it is clear that technology is changing the field of educational and psychological measurement. The numerous and rapid advances have immediate impact on test creators, assessment professionals, and those who implement and analyze assessments. This comprehensive new volume brings together leading experts on the issues posed by technological applications in testing, with chapters on game-based assessment, testing with simulations, video assessment, computerized test development, large-scale test delivery, model choice, validity, and error issues. Including an overview of existing literature and ground-breaking research, each chapter considers the technological, practical, and ethical considerations of this rapidly-changing area. Ideal for researchers and professionals in testing and assessment, Technology and Testing provides a critical and in-depth look at one of the most pressing topics in educational testing today