Managing Large Systems

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.

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

The trusted handbook—now in a new edition This newly revised handbook presents a multifaceted view of systems engineering from process and systems management perspectives. It begins with a comprehensive introduction to the subject and provides a brief overview of the thirty-four chapters that follow. This introductory chapter is intended to serve as a "field guide" that indicates why, when, and how to use the material that follows in the handbook. Topical coverage includes: systems engineering life cycles and management; risk management; discovering system requirements; configuration management; cost management; total quality management; reliability, maintainability, and availability; concurrent engineering; standards in systems engineering; system architectures; systems design; systems integration; systematic measurements; human supervisory control; managing organizational and individual decision-making; systems reengineering; project planning; human systems integration; information technology and knowledge management; and more. The handbook is written and edited for systems engineers in industry and government, and to serve as a university reference handbook in systems engineering and management courses. By focusing on systems engineering processes and systems management, the editors have produced a long-lasting handbook that will make a difference in the design of systems of all types that are large in scale and/or scope.

The book describes how to manage and successfully deliver large, complex, and expensive systems that can be composed of millions of line of software code, being developed by numerous groups throughout the globe, that interface with many hardware items being developed by geographically dispersed companies, where the system also includes people, policies, constraints, regulations, and a myriad of other factors. It focuses on how to seamlessly integrate systems, satisfy the customer’s requirements, and deliver within the budget and on time. The guide is essentially a “shopping list” of all the activities that could be conducted with tailoring guidelines to meet the needs of each project.

This book constitutes the refereed proceedings of the 10th International Conference on Software Reuse, ICSR 2008, held in Beijing, China, in May 2008. The 40 revised full papers presented together with 5 workshop summaries and 5 tutorials were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on architecture and reuse approaches, high confidence and reuse, component selection and reuse repository, product line, domain models and analysis, service oriented environment, components and services, reuse approaches and frameworks, as well as reuse approaches and methods.

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