Managing Large Systems examines a wide range of human, organizational, and managerial challenges associated with large systems. Special attention is given to the behavioral relationships among scientists and engineers, business and technical managers, sponsor organizations and their contractors, business and government offi cials, and line and functional managers.
Managing Large Systems examines a range of human, organizational, and managerial challenges associated with large systems. Special attention is given to the behavioral relationships among scientists and engineers, business and technical managers, sponsor organizations and their contractors, business and government officials, and line and functional managers.The descriptions of problems of technical organization and performance motivation are based primarily on an extended field study of the National Aeronautics and Space Administration. Managing Large Systems includes a description of the unique management system developed by NASA under the leadership of James Webb that many believe was responsible for their extraordinary technological achievements that culminated in the first moon landing. Parallels are drawn to other large-scale technology programs in aerospace and atomic energy.The authors find traditional managerial principles regarding controls, incentive systems, and planning to be inadequate in the context of large systems. They look to organizational clusters to manage future projects in advanced technological areas and in public sectors such as urban development, massive medical programs, and ecological improvements.
A human-centric guide to solving complex problems in engineering management, from sizing teams to handling technical debt. There’s a saying that people don’t leave companies, they leave managers. Management is a key part of any organization, yet the discipline is often self-taught and unstructured. Getting to the good solutions for complex management challenges can make the difference between fulfillment and frustration for teams—and, ultimately, between the success and failure of companies. Will Larson’s An Elegant Puzzle focuses on the particular challenges of engineering management—from sizing teams to handling technical debt to performing succession planning—and provides a path to the good solutions. Drawing from his experience at Digg, Uber, and Stripe, Larson has developed a thoughtful approach to engineering management for leaders of all levels at companies of all sizes. An Elegant Puzzle balances structured principles and human-centric thinking to help any leader create more effective and rewarding organizations for engineers to thrive in.
This timely book provides you with a solid understanding of battery management systems (BMS) in large Li-Ion battery packs, describing the important technical challenges in this field and exploring the most effective solutions. You find in-depth discussions on BMS topologies, functions, and complexities, helping you determine which permutation is right for your application. Packed with numerous graphics, tables, and images, the book explains the OC whysOCO and OC howsOCO of Li-Ion BMS design, installation, configuration and troubleshooting. This hands-on resource includes an unbiased description and comparison of all the off-the-shelf Li-Ion BMSs available today. Moreover, it explains how using the correct one for a given application can help to get a Li-Ion pack up and running in little time at low cost."
Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. - Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics - Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics - Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions
Many organizations critically depend on very large information systems. In the authors' experience these organizations often struggle to find the right strategy to sustainably develop their systems. Based on their own experience at a major bank, over more than a decade, the authors have developed a successful strategy to deal with these challenges, including: - A thorough analysis of the challenges associated with very large information systems - An assessment of possible strategies for the development of these systems, resulting in managed evolution as the preferred strategy - Describing key system aspects for the success of managed evolution, such as architecture management, integration architecture and infrastructure - Developing the necessary organizational, cultural, governance and controlling mechanisms for successful execution
Software reuse depicts a great vision for the software industry. It has been widely viewed as a promising way to improve both the productivity and quality of software development. However, despite of the successes we have achieved, there are still many issues that have limited the promotion of software reuse in the real world. Therefore, software reuse has remained an important hotspot of research. ICSR is the premier international conference in the field of software reuse. It has been an important venue for presenting advances and improvements within the software reuse domain, and a powerful driving force in promoting the interaction between researchers and practitioners. The theme of ICSR 10 was "High Confidence Software Reuse in Large Systems. " A high confidence system is one that behaves in a well-understood and predictable fashion. Today’s trends towards widespread use of commercial off-the-shelf (COTS) technology, increased integration, continuous evolution, and larger scale are yielding more complex software systems. So, the problem of how to build high confidence complex systems and how to reuse software with a high level of confidence has become a new attractive topic for research. Furthermore, high-level software asset reuse has been a goal for the last 20–30 years, and it can still be considered an unsolved question. Components-based development, MDA-MDE-MDD, extreme programming, and other techniques or methods are promising approaches to software reuse that still need more research. These proceedings report on the current state of the art in software reuse.
Management Information Systems provides comprehensive and integrative coverage of essential new technologies, information system applications, and their impact on business models and managerial decision-making in an exciting and interactive manner. The twelfth edition focuses on the major changes that have been made in information technology over the past two years, and includes new opening, closing, and Interactive Session cases.
Scientists and researchers concerned with the behavior of large ecosystems have focused in recent years on the concept of "resilience." Traditional perspectives held that ecological systems exist close to a steady state and resilience is the ability of the system to return rapidly to that state following perturbation. However beginning with the work of C. S. Holling in the early 1970s, researchers began to look at conditions far from the steady state where instabilities can cause a system to shift into an entirely different regime of behavior, and where resilience is measured by the magnitude of disturbance that can be absorbed before the system is restructured. Resilience and the Behavior of Large-Scale Systems examines theories of resilience and change, offering readers a thorough understanding of how the properties of ecological resilience and human adaptability interact in complex, regional-scale systems. The book addresses the theoretical concepts of resilience and stability in large-scale ecosystems as well as the empirical application of those concepts in a diverse set of cases. In addition, it discusses the practical implications of the new theoretical approaches and their role in the sustainability of human-modified ecosystems. The book begins with a review of key properties of complex adaptive systems that contribute to overall resilience, including multiple equlibria, complexity, self-organization at multiple scales, and order; it also presents a set of mathematical metaphors to describe and deepen the reader's understanding of the ideas being discussed. Following the introduction are case studies that explore the biophysical dimensions of resilience in both terrestrial and aquatic systems and evaluate the propositions presented in the introductory chapters. The book concludes with a synthesis section that revisits propositions in light of the case studies, while an appendix presents a detailed account of the relationship between return times for a disturbed system and its resilienc. In addition to the editors, contributors include Stephen R. Carpenter, Carl Folke, C. S. Holling, Bengt-Owe Jansson, Donald Ludwig, Ariel Lugo, Tim R. McClanahan, Garry D. Peterson, and Brian H. Walker.
Large Refactorings looks at methods of establish design improvements as an important and independent activity during development of software, and will help to ensure that software continues to adapt, improve and remain easy to read and modify without altering its observable behaviour. It provides real-world experience from real refactored projects and shows how to refactor software to ensure that it is efficient, fresh and adaptable.
