DEFINING THE IMPLEMENTATION ORDER OF SOFTWARE PROJECTS IN UNCERTAIN ENVIRONMENTS

Eber Assis Schmitz, Antonio Juarez Alencar, Marcelo C. Fernandes, Carlos Mendes de Azevedo

2008

Abstract

In the competitive world in which we live, where every business opportunity not taken is an opportunity handed to competitors, software developers have distanced themselves, in both language and values, from those who define the requirements that software has to satisfy and come up with the money that funds its development process. Such a distance helps to reduce or, in some cases, completely eliminate the competitive advantage that software development may provide to an organization; transforming this value creation activity into a business cost that is better kept low and under tight control. This article proposes a method for obtaining the optimal implementation order of software units in an information technology development project. This method, which uses a combination of heuristic procedures and Monte Carlo simulation, takes into consideration the fact that software development is generally carried out under cost and investment constraints in an uncertain environment, whose proper analysis indicate how to obtain the best possible return on investment. The article shows that decisions made under uncertainty may be substantially different from those made in a risk-free environment.

References

  1. Cleland-Huang, J. and Denne, M. (2005). Financially informed requirements prioritization. In Proceedings of the 27th international Conference on Software Engineering, pages 710 - 711, St. Louis, MO, USA. Association for Computing Machinery (ACM) and ACM Special Interest Group on Software Engineering (SIGSOFT), ACM.
  2. Denne, M. and Cleland-Huang, J. (2003). Software by Numbers: Low-Risk High-Return Development. Prentice Hall.
  3. Denne, M. and Cleland-Huang, J. (2004). The incremental funding method: Data driven software development. IEEE Software, 21(3):39-47.
  4. Germain, E. and Robillard, P. N. (2005). Engineering-based processes and agile methodologies for software development: a comparative case study. Journal of Systems and Software, 75(1-2):17-27.
  5. Hill, T. and Lewicki, P. (2005). Statistics: Methods and Applications. StatSoft, Inc.
  6. Holloway, C. A. (1979). Decision Making Under Uncertainty: Models and Choices. Prentice Hall.
  7. Hubbard, D. W. (2007). How to Measure Anything: Finding the Value of “Intangibles” in Business. John Wiley & Sons.
  8. Knuth, D. E. (1998). The Art of Computer Programming: Seminumerical Algorithms. Addison Wesley.
  9. Kotler, P. and Armstrong, G. (2007). Principles of Marketing. Prentice Hall, 12th edition.
  10. Kotz, S. and van Dorp, J. R. (2004). Beyond Beta: Other Continuous Families Of Distributions With Bounded Support And Applications. World Scientific Publishing Company.
  11. Little, T. (2004). Value creation and capture: A model of the software development process. IEEE SOFTWARE.
  12. Joint Task Force (2005). Computing curricula 2005: The overview report. Technical report, The Associantion for Computing Machinery (ACM), The Association for Information Systems (AIS) and The Computer Society (IEEE-CS). Information available in the Internet at www.acm.org/education/curricula.html. Site last visited on October 28th, 2007.
  13. Rashid, A., Moreira, A., and Araújo, J. (2003). Modularisation and composition of aspectual requirements.
  14. In Proceedings of the 2nd International Conference on Aspect-oriented Software Development, pages 11 - 20, Boston, Massachusetts, USA. Northeastern University, ACM.
  15. Robert, C. P. and Casella, G. (2005). Monte Carlo Statistical Methods. Spinger-Verlag, 2nd edition.
  16. Scott, D. (2006). I.T. Wars: Managing the BusinessTechnology Weave in the New Millennium. BookSurge Publishing.
  17. Thomas, J. S. and Duffy, D. E. (2004). The Statistical Analysis of Discrete Data. Springer-Verlag, 1st edition.
  18. Verhoef, C. (2005). Quantifying the value of ITinvestments. Science of Computer Programming, 56:315-342.
  19. Vose, D. (2000). Risk Analysis: A Quantitative Guide. John Wiley & Sons, 2nd edition.
Download


Paper Citation


in Harvard Style

Assis Schmitz E., Juarez Alencar A., C. Fernandes M. and Mendes de Azevedo C. (2008). DEFINING THE IMPLEMENTATION ORDER OF SOFTWARE PROJECTS IN UNCERTAIN ENVIRONMENTS . In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS, ISBN 978-989-8111-38-8, pages 23-29. DOI: 10.5220/0001670200230029


in Bibtex Style

@conference{iceis08,
author={Eber Assis Schmitz and Antonio Juarez Alencar and Marcelo C. Fernandes and Carlos Mendes de Azevedo},
title={DEFINING THE IMPLEMENTATION ORDER OF SOFTWARE PROJECTS IN UNCERTAIN ENVIRONMENTS},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS,},
year={2008},
pages={23-29},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001670200230029},
isbn={978-989-8111-38-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS,
TI - DEFINING THE IMPLEMENTATION ORDER OF SOFTWARE PROJECTS IN UNCERTAIN ENVIRONMENTS
SN - 978-989-8111-38-8
AU - Assis Schmitz E.
AU - Juarez Alencar A.
AU - C. Fernandes M.
AU - Mendes de Azevedo C.
PY - 2008
SP - 23
EP - 29
DO - 10.5220/0001670200230029