“Jugaad”—The Creativeness for Selection of Software Development Methodology Advisory System—Fuzzy Expert System

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 379)


Globalization and technical revolution are raising several challenges to the software development sector. Over the past 50 years, software has evolved as a specialized problem-solving and information analysis tool to an industry, but now it is facing multiple challenges. The objective of this study is to landscape current knowledge, in terms of productivity and find out its impact on the software development. To resolve such problems, “Software Development Practitioner” needs to find out a flexible way (Jugaad) for development. “Jugaad” is the Indian common man’s philosophy to achieve the dream goal within the available resources. The researcher has made earnest attempts to study the steps to be undertaken to make the flexible module. The goal of this paper is to rectify the present hurdles and hassles in development approaches by representing “Selection of Software Development Methodologies Advisory System” on the basis of reference of fuzzy expert system.


Productivity of software development Factor affecting productivity JUGAAD Fuzzy expert system Uncertainty Selection of software development advisory system 


  1. 1.
    Kardile, V.V.: Enhance accuracy in software development’s planning & estimation process by adopt “uncertainty analysis and assessment” in the system modeling process a review (2012). ISBN:978-1-4244-8677-9Google Scholar
  2. 2.
    Kardile, V.V.: Need to understand uncertainty in system development modelling process. IEEE (2011). ISBN:978-0-7695-4437-3Google Scholar
  3. 3.
    Ambler, S.W.: Defining Success, by. Dr. Dobb’s Journal. Source :2014 IT project success survey (2014). www.ambaysoft.com/surveys/success2014.html
  4. 4.
    Boehm, B.W.: Improving software productivity. IEEE Comput. 20(8), 43–58 (1987)CrossRefGoogle Scholar
  5. 5.
    Kardile, V.V.: Understanding need of “uncertainty analysis” in the system design process. Int. J. Soft. Eng. Appl. (IJSEA), vol. 2, 3 July 2011. ISSN: 0975-9018Google Scholar
  6. 6.
    Kardile, V.V.: Understanding the need of flexible software development approach using economic model IEEE: CFP1195-PRT (2011). ISBN:978-1-4244-8677-9Google Scholar
  7. 7.
    Radjou, N., Prabhu, J., Ahuja, S.: Jugaad Innovation. Jossey-Bass, A Wiley Imprint (2012)Google Scholar
  8. 8.
    Chen, J.: An analytical theory of project investment: a comparison with real option theory. Int. J. Manag. Financ. (2006)Google Scholar
  9. 9.
    Ngai, E.W.T., Wat, F.K.T.: Design and development of a fuzzy expert system for hotel selection (2003)Google Scholar
  10. 10.
    Klauer, B., Brown, J.D.: Conceptualising imperfect knowledge in public decision making: ignorance, uncertainty, error and ‘risk situations’. Env. Res. Eng. Manag. 27(1), 124e128 (2004)Google Scholar
  11. 11.
    Kumru, M.: Assessing the visual quality of sanitary ware by using fuzzy logic. Appl. Soft Comput. 13(8), 3646–3656 (2013)Google Scholar
  12. 12.
    Ayman Al Ahmar, M.: Rule based expert system for selecting software development methodology. J. Theor. Appl. Inf. Technol. © 2005–2010, jatit&llsGoogle Scholar
  13. 13.
    Goodarxi, M.H., Rafe, V.: Educational advisor system implemented by web based fuzzy expert system. Asian J. Inf. Technol. 11(2), 77–82 (2012). J. Soft. Eng. Appl. (Medwell Journals 2012) 5, 500–507. doi: 10.4236/jsea.2012.57058. Published July 2012. http://www.SciRP.org/journal/jsea
  14. 14.
    Fard, M.T.T., Jafari, H.R., Shojaie, S.E.: Analysis expert system factors in IT project selection using Fuzzy AHP. Interdisc. J. Contemp. Res. Bus. copy right © 2012. Institute of Interdisciplinary Business Research 512, 4(8) Dec 2012. jcrb.webs.com
  15. 15.
    Fenton, N.E., Neil, M.: Software metrics: successes, failures and new directions. J. Syst. Soft. 47, 149–157 (1999)Google Scholar
  16. 16.
    Refsgaard, J.C., van der Sluijsb, J.P., Højberga, A.L., Vanrolleghemc, P.A.: Uncertainty in the environmental modelling process, a framework and guidance. Environmental Modeling & Software 22 (2007)Google Scholar
  17. 17.
  18. 18.
    Walker, W.E., Harremoës, P., Rotmans, J., Van der Sluijs, J.P., Van Asselt, M.B.A., Janssen, P., Krayer von Krauss, M.P.: Defining uncertainty a conceptual basis for uncertainty management in model-based decision support. Integrated Assessment 4(1), 5e17 (2003)Google Scholar
  19. 19.
    Thompson, K.: Agile journal productivity report. www.agilejournal.com (2011)
  20. 20.
    Kardile, V.V.: Understanding of software effort estimation at the early software development of the lifecycle—a literature view. Int. J. Eng. Res. Appl. 2(1), 848–852 (2012)Google Scholar
  21. 21.
    Aneselmo, D., Ledgard, H.: Measuring productivity in the software industry. Communications of the ACM, vol. 46, (Nov 2003)Google Scholar
  22. 22.
    Scacchi, W.: Understanding software Productivity (1994). Google search last access 12/12/2012Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Computer Science DepartmentTuljaram Chaturchand CollegeBaramati (Pune)India
  2. 2.Department of Computer ScienceNDAKhadakwasala, PuneIndia

Personalised recommendations