Skip to main content
SpringerLink
Log in

Foundation for Establishing NSE: Complexity Science

  • Chapter
  • First Online:
New Software Engineering Paradigm Based on Complexity Science

  • 782 Accesses

Abstract

This chapter introduces the foundation for establishing NSE – complexity science. Complexity science is the scientific study of nonlinear, dynamic, complex systems and the process of self-organization. Complexity science is the driving force for the development of sciences, engineering, and business in the twenty-first century. Complexity science explains how holism emerges in the world, and more. It is the intellectual successor to systems theory and chaos theory. Complexity science is a field derived from multiple disciplines – physics, chemistry, biology, and mathematics. Definitions of complexity are often tied to the concept of a complex system – something with many parts that interact to produce results that cannot be explained by simply specifying the role of each part. This concept contrasts with traditional machine or Newtonian constructs, which assume that all parts of a system can be known, that detailed planning produces predictable results, and that information flows along a predetermined path. Elements of complexity theory have been incorporated into a number of fields including genetics, immunology, cognitive science, economics, computer science, and linguistics. Currently, the most robust research in complexity science involves the study of inanimate systems such as computer networks and hydrodynamic systems as well as certain cellular networks (Ashok M. Patel, M.D., Thoralf M. Sundt III, M.D., and Prathibha Varkey, M.D., Complexity Science – Core Concepts and Applications for Medical Practice, http://www.minnesotamedicine.com/PastIssues/February2008/ClinicalFebruary2008/tabid/2462/Default.aspx); [Ber 76], [Sar06].

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Arthur WB (1999) Complexity and the economy. Science 284:107–109

    Article  Google Scholar 

  2. Von Bertalanffy L (1976) General system theory. George Braziller, New York

    Google Scholar 

  3. de Bono E (1968) New think: the use of lateral thinking in the generation of new ideas. Basic Books, New York

    Google Scholar 

  4. Dai R (1995) Metasynthetic social intelligence engineering: a review. Institute of Automation, Chinese Academy of Sciences, Beijing

    Google Scholar 

  5. Dent EB (2000) Complexity science: a paradigm shift. Emergence 1(4):5–19

    Article  Google Scholar 

  6. Faltings B (2000) Intelligent agents: software technology for the new millennium. Informatik/Informatique 1:2–5

    Google Scholar 

  7. Francis J (2004) Managing BPM, BPM and Nonlinear Thinking, June Issue

    Google Scholar 

  8. Holland JH (1992) Complex adaptive systems. American Academy of Arts & Sciences, Cambridge

    Google Scholar 

  9. James A. Highsmith III, Adaptive Software Development: A Collaborative Approach to Managing Complex Systems, DORSET HOUSE PUBLISHING CO., INC., 2000.

    Google Scholar 

  10. Jennings NR, Wooldridge M (2000) Agent-oriented software engineering. Department of Electronic Engineering, Queen Mary & Westfield College, University of London, London

    Google Scholar 

  11. Kimball L, Weinstein N, Silber T (2004) Maximizing facilitation skills using principles of complexity science. OD Network Conference, October 2004

    Google Scholar 

  12. Lamoreux M (2003) Complexity science and software development, an introduction to complexity science and its applications in agile software development, http://comdig.unam.mx/article.php?id_article=13746&find=complexity

    Google Scholar 

  13. Mandelbrot BB (1982) The fractal geometry of nature. W.H. Freeman, San Francisco. ISBN 0-7167-1186-9

    MATH  Google Scholar 

  14. Yasmin M, McKelvey B (2006) Using complexity science to effect a paradigm shift in information systems for the 21st century. J Inform Technol 21:211–215

    Article  Google Scholar 

  15. Von Neumann J (1966) Theory of self-reproducing automata. Edited and completed by A.W. Burks. University of Illinois Press, Urbana

    Google Scholar 

  16. Norreys PA (2008) PHYSICS: complexity in fusion plasmas. Science 319:1193

    Article  Google Scholar 

  17. Sardar Z, Abrams I (2006) Caos Para Todos/Introducing chaos. Icon Books, Cambridge

    Google Scholar 

  18. Sipper M (2002) Machine nature: the coming age of bio-inspired computing. McGraw-Hill, New York

    Google Scholar 

  19. Raymond Sneyers (1997) Climate chaotic instability: statistical determination and theoretical background. Environmetrics 8(5):517–532

    Article  Google Scholar 

  20. Toffoli T, Margolus N (1987) Cellular automata machines. The MIT Press, Cambridge

    Google Scholar 

  21. Wolfram S (1984) Universality and complexity in cellular automata. Physica D 10:1–35

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. 1545 Jackson St. #103, Oakland, CA, 94612, USA

    Jay Xiong

Authors
  1. Jay Xiong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jay Xiong .

Further Reading and Information Source

Further Reading and Information Source

  1. (a)

    Waldrop MM (1992) Complexity: the emerging science at the edge of order and chaos. Viking, London

  2. (b)

    Gleick J (1988) Chaos: making a new science. Cardinal, London

  3. (c)

    Castellani B, Hafferty FW (2009) Sociology and complexity science: a new field of inquiry. Springer, Heidelberg

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Xiong, J. (2011). Foundation for Establishing NSE: Complexity Science. In: New Software Engineering Paradigm Based on Complexity Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7326-9_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4419-7326-9_3

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-7325-2

  • Online ISBN: 978-1-4419-7326-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation