New Software Engineering Paradigm Based on Complexity Science: An Introduction to NSE - Softcover

Xiong, Jay

Softcover

ISBN 10: 1489981594 ISBN 13: 9781489981592

Publisher: Springer, 2014

Synopsis

This book describes a complete revolution in software engineering based on complexity science through the establishment of NSE – Nonlinear Software Engineering paradigm which complies with the essential principles of complexity science, including the Nonlinearity principle, the Holism principle, the Complexity Arises From Simple Rules principle, the Initial Condition Sensitivity principle, the Sensitivity to Change principle, the Dynamics principle, the Openness principle, the Self-organization principle, and the Self-adaptation principle. The aims of this book are to offer revolutionary solutions to solve the critical problems existing with the old-established software engineering paradigm based on linear thinking and simplistic science complied with the superposition principle, and make it possible tohelp software development organizations double their productivity, halve their cost, and remove 99% to 99.99% of the defects in their software products, and efficiently handle software complexity, conformity, visibility, and changeability. It covers almost all areas in software engineering.

The tools NSE_CLICK- an automatic acceptance testing platform for outsourcing (or internally developed) C/C++ products, and NSE_CLICK_J - an automatic acceptance testing platform for outsourcing (or internally developed) Java products are particularly designed for non-technical readers to view/review how the acceptance testing of a software product developed with NSE can be performed automatically, and how the product developed with NSE is truly maintainable at the customer site.

About this title

From the Back Cover

Title: New Software Engineering Paradigm Based on Complexity Science: An Introduction to NSE Author: Jay Xiong Software has become the driving force for the development of all kinds of businesses, engineering, sciences and the global economy. But software itself is not well engineered, resulting in a total economic cost that is disturbingly high. Jay Xiong, a leading entrepreneur in the field of software engineering, realized many of the problems in software engineering stem from an incorrect paradigm. Software is a nonlinear complex system, but the existing software engineering paradigm is based on linear thinking, reductionism, and a superposition principle that the whole of a system is the sum of its parts. Xiong believes that the solution to software problems lies with complexity science, which is the science of studying complex systems with many interactive components. In New Software Engineering Paradigm Based on Complexity Science: An Introduction to NSE, Xiong details how complexity science can be a powerful means to solve all critical issues existing in today’s software engineering through a two-step process. Step one discusses shifting the engineering paradigm to one based on nonlinear process and complexity science. For that, he posits the Nonlinear Software Engineering (NSE) paradigm. And step two applies complexity science to efficiently handle the problems of an individual complex system. This text introduces many new concepts, ideas, algorithms, models, methods, techniques and tools. It is aimed at anyone who has any relation to computer science and software engineering.

The tools NSE_CLICK- an automatic acceptance testing platform for outsourcing (or internally developed) C/C++ products, and NSE_CLICK_J - an automatic acceptance testing platform for outsourcing (or internally developed) Java products are particularly designed for non-technical readers to view/review how the acceptance testing of a softwareproduct developed with NSE can be performed automatically, and how the product developed with NSE is truly maintainable at the customer site.

Edition details

• Publisher: Springer
• Publication date: 2014
• ISBN 10: 1489981594
• ISBN 13: 9781489981592
• Binding: Paperback
• Language: English
• Number of pages: 781