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Economics-driven Software Architecture presents a guide for engineers and architects who need to understand the economic impact of architecture design decisions: the long term and strategic viability, cost-effectiveness, and sustainability of applications and systems. Economics-driven software development can increase quality, productivity, and profitability, but comprehensive knowledge is needed to understand the architectural challenges involved in dealing with the development of large, architecturally challenging systems in an economic way. This book covers how to apply economic considerations during the software architecting activities of a project. Architecture-centric approaches to development and systematic evolution, where managing complexity, cost reduction, risk mitigation, evolvability, strategic planning and long-term value creation are among the major drivers for adopting such approaches. It assists the objective assessment of the lifetime costs and benefits of evolving systems, and the identification of legacy situations, where architecture or a component is indispensable but can no longer be evolved to meet changing needs at economic cost. Such consideration will form the scientific foundation for reasoning about the economics of nonfunctional requirements in the context of architectures and architecting.
Economics-driven Software Architecture presents a guide for engineers and architects who need to understand the economic impact of architecture design decisions: the long term and strategic viability, cost-effectiveness, and sustainability of applications and systems. Economics-driven software development can increase quality, productivity, and profitability, but comprehensive knowledge is needed to understand the architectural challenges involved in dealing with the development of large, architecturally challenging systems in an economic way. This book covers how to apply economic considerations during the software architecting activities of a project. Architecture-centric approaches to development and systematic evolution, where managing complexity, cost reduction, risk mitigation, evolvability, strategic planning and long-term value creation are among the major drivers for adopting such approaches. It assists the objective assessment of the lifetime costs and benefits of evolving systems, and the identification of legacy situations, where architecture or a component is indispensable but can no longer be evolved to meet changing needs at economic cost. Such consideration will form the scientific foundation for reasoning about the economics of nonfunctional requirements in the context of architectures and architecting. Familiarizes readers with essential considerations in economic-informed and value-driven software design and analysis Introduces techniques for making value-based software architecting decisions Provides readers a better understanding of the methods of economics-driven architecting
Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques Presents case studies involving enterprise, business, and government service deployment of big data applications Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data
System Quality and Software Architecture collects state-of-the-art knowledge on how to intertwine software quality requirements with software architecture and how quality attributes are exhibited by the architecture of the system. Contributions from leading researchers and industry evangelists detail the techniques required to achieve quality management in software architecting, and the best way to apply these techniques effectively in various application domains (especially in cloud, mobile and ultra-large-scale/internet-scale architecture) Taken together, these approaches show how to assess the value of total quality management in a software development process, with an emphasis on architecture. The book explains how to improve system quality with focus on attributes such as usability, maintainability, flexibility, reliability, reusability, agility, interoperability, performance, and more. It discusses the importance of clear requirements, describes patterns and tradeoffs that can influence quality, and metrics for quality assessment and overall system analysis. The last section of the book leverages practical experience and evidence to look ahead at the challenges faced by organizations in capturing and realizing quality requirements, and explores the basis of future work in this area. Explains how design decisions and method selection influence overall system quality, and lessons learned from theories and frameworks on architectural quality Shows how to align enterprise, system, and software architecture for total quality Includes case studies, experiments, empirical validation, and systematic comparisons with other approaches already in practice.
Results-Based Software Management: Achieve Better Outcomes with Finite Resources Effective software development is no longer merely an IT concern: today, it is crucial to the entire enterprise. However, most businesspeople are not ready to make informed decisions about software initiatives. The Economics of Iterative Software Development: Steering Toward Better Business Results will prepare them. Drawing on decades of software development and business experience, the authors demonstrate how to utilize practical, economics-based techniques to plan and manage software projects for maximum return on technology investments. The authors begin by dispelling widespread myths about software costs, explaining why traditional, “engineering-based” software management introduces unacceptable inefficiencies in today’s development environments. Next, they show business and technical managers how to combine the principles of economics and iterative development to achieve optimal results with limited resources. Using their techniques, readers will learn how to build systems that enable maximum business innovation and process improvement—and implement software processes that allow them to do so consistently. Highlights include How to repeatedly quantify the value a project is delivering and quickly adjust course as needed How to reduce software project size, complexity, and other “project killers” How to identify and eliminate software development processes that don’t work How to improve development processes, reduce rework, mitigate risk, and identify inefficiencies How to create more proficient teams by improving individual skills, team interactions, and organizational capability Where to use integrated, automated tools to improve effectiveness What to measure, and when: specific metrics for project inception, elaboration, construction, and transition The Economics of Iterative Software Development: Steering Toward Better Business Results will help both business and technical managers make better decisions throughout the software development process—and it will help team and project leaders keep any project or initiative on track, so they can deliver more value faster.
Managing Trade-Offs in Adaptable Software Architectures explores the latest research on adapting large complex systems to changing requirements. To be able to adapt a system, engineers must evaluate different quality attributes, including trade-offs to balance functional and quality requirements to maintain a well-functioning system throughout the lifetime of the system. This comprehensive resource brings together research focusing on how to manage trade-offs and architect adaptive systems in different business contexts. It presents state-of-the-art techniques, methodologies, tools, best practices, and guidelines for developing adaptive systems, and offers guidance for future software engineering research and practice. Each contributed chapter considers the practical application of the topic through case studies, experiments, empirical validation, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to, how to architect a system for adaptability, software architecture for self-adaptive systems, understanding and balancing the trade-offs involved, architectural patterns for self-adaptive systems, how quality attributes are exhibited by the architecture of the system, how to connect the quality of a software architecture to system architecture or other system considerations, and more. Explains software architectural processes and metrics supporting highly adaptive and complex engineering Covers validation, verification, security, and quality assurance in system design Discusses domain-specific software engineering issues for cloud-based, mobile, context-sensitive, cyber-physical, ultra-large-scale/internet-scale systems, mash-up, and autonomic systems Includes practical case studies of complex, adaptive, and context-critical systems
Jeffersonian Economic Architecture in the Digital Age By: Robert S. Ellinger Ph.D Jeffersonian Economic Architecture in the Digital Age is a book focused on how to synergically adapt to the catastrophic change in culture that humanity is currently undergoing. This is due to seismic change in technology at the dawn of the Digital Age. The author Robert S. Ellinger Ph.D. has created an architectural model using concepts from a variety of academic disciplines including spatial economics, history, systems engineering, information technology, enterprise architecture, and political science. He uses this model to demonstrate how humanity adapted to technology change in the past. He then transforms this model for the future Digital Age. And he does this while keeping Jefferson’s and other founding father’s concept of equal opportunity for all as envisioned in the US Declaration of Independence and Preamble of the US Constitution.
This book focuses on software sustainability, regarded in terms of how software is or can be developed while taking into consideration environmental, social, and economic dimensions. The sixteen chapters cover various related issues ranging from technical aspects like energy-efficient programming techniques, formal proposals related to energy efficiency measurement, patterns to build energy-efficient software, the role of developers on energy efficient software systems and tools for detecting and refactoring code smells/energy bugs; to human aspects like its impact on software sustainability or the adaptation of ACM/IEEE guidelines for student and professional education and; and an economics-driven architectural evaluation for sustainability. Also aspects as the elements of governance and management that organizations should consider when implementing, assessing and improving Green IT or the relationship between software sustainability and the Corporate Social Responsibility of software companies are included. The chapters are complemented by usage scenarios and experience reports on several domains as cloud applications, agile development or e-Health, among others. As a whole, the chapters provide a complete overview of the various issues related to sustainable software development. The target readership for this book includes CxOs, (e.g. Chief Information Officers, Chief Executive Officers, Chief Technology Officers, etc.) software developers, software managers, auditors, business owners, and quality professionals. It is also intended for students of software engineering and information systems, and software researchers who want to know the state of the art regarding software sustainability.
Whether ERP software, office applications, open-source products or online games: In terms of its economic characteristics, software differs fundamentally from industrial goods or services. Based on the economic principles and rules of the software industry, the book reveals strategies and business models to software vendors that comprise cooperation, distribution, pricing and production and industrialization strategies, as well as software as a service and platform concepts. Further aspects including the outsourcing behavior of software vendors and users; providing business software as open source software; selecting software; and the value chains in the software industry are also addressed. Based on a number of expert meetings, it contains numerous case studies and new empirical findings. Target audience of the book are professionals and executives from the software, consulting and IT branches as well as students and scholars of business administration, computer science, business and industrial engineering.
Poor quality continues to bedevil large-scale development projects, but few software leaders and practitioners know how to measure quality, select quality best practices, or cost-justify their usage. In The Economics of Software Quality, leading software quality experts Capers Jones and Jitendra Subramanyam show how to systematically measure the economic impact of quality and how to use this information to deliver far more business value. Using empirical data from hundreds of software organizations, Jones and Subramanyam show how integrated inspection, static analysis, and testing can achieve defect removal rates exceeding 95 percent. They offer innovative guidance for predicting and measuring defects and quality; choosing defect prevention, pre-test defect removal, and testing methods; and optimizing post-release defect reporting and repair. This book will help you Prove that improved software quality translates into strongly positive ROI and greatly reduced TCO Drive better results from current investments in debugging and prevention Use quality techniques to stay on schedule and on budget Avoid "hazardous" metrics that lead to poor decisions Important note: The audio and video content included with this enhanced eBook can be viewed only using iBooks on an iPad, iPhone, or iPod touch.