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Reseach Article

Risk Management in Software Development using Artificial Neural Networks

by Amrita Gandhi, Ajit Naik, Kapil Thakkar, Manisha Gahirwal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Number 19
Year of Publication: 2014
Authors: Amrita Gandhi, Ajit Naik, Kapil Thakkar, Manisha Gahirwal
10.5120/16468-6155

Amrita Gandhi, Ajit Naik, Kapil Thakkar, Manisha Gahirwal . Risk Management in Software Development using Artificial Neural Networks. International Journal of Computer Applications. 93, 19 ( May 2014), 22-28. DOI=10.5120/16468-6155

@article{ 10.5120/16468-6155,
author = { Amrita Gandhi, Ajit Naik, Kapil Thakkar, Manisha Gahirwal },
title = { Risk Management in Software Development using Artificial Neural Networks },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 93 },
number = { 19 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 22-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume93/number19/16468-6155/ },
doi = { 10.5120/16468-6155 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:16:10.323047+05:30
%A Amrita Gandhi
%A Ajit Naik
%A Kapil Thakkar
%A Manisha Gahirwal
%T Risk Management in Software Development using Artificial Neural Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 93
%N 19
%P 22-28
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

IT industry is one of the biggest industries around the world with several software projects being developed which vary in size, cost, complexity, etc. During development, many risks of different types arise such as lack of staff experience, new technologies, budgets, etc. These risks play a huge role in success or failure of a project. Most of the available risk management solutions are too costly and time consuming. There is a need for an efficient risk management technique. To assist the project manager in risk management, we have developed an application which will identify the risks involved during software development and predict the success or failure of the project using Artificial Neural Networks. The prediction will be done using historical data taking the important and common risk factors into account. After risk identification, the probability of success or failure will be determined and suggestions for risk mitigation will be provided for the project. This application will help the project managers in carrying out risk management activities efficiently.

References
  1. Bent Flyvbjerg and Alexander Budzier 2011 Why your IT project may be riskier than you think. , Harvard Business Review.
  2. Hubbard, Douglas (2009). The Failure of Risk Management: Why It's Broken and How to Fix It. John Wiley & Sons. p. 46.
  3. Neural Networks and Learning Machines by Simon Haykin (2009)
  4. Barki, H. ; Rivard, S. ; and Talbot, J. Toward an assessment of software development risk. Journal of Management Infonnation Systems.
  5. Boehm, B. 1991. Software risk management: principles and practices
  6. Moynihan. T. 1997 How experienced project managers assess risk. IEEE Software.
  7. Marvin J. Carr, Suresh L. Konda, Ira Monarch, F. Carol Ulrich, Clay F. Walker (1993). Taxonomy-Based Risk Identification
Index Terms

Computer Science
Information Sciences

Keywords

Risk Identification Neural Networks Backpropagation