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Article
Fuzzy-ExCOM Software Project Risk Assessment
Electrical and Computer Engineering Publications
  • Luiz Fernando Capretz, University of Western Ontario
  • Ekananta Manalif, London Hydro
  • Ali Bou Nassif, University of Western Ontario
  • Danny Ho, NFA Estimation Inc.
Document Type
Article
Publication Date
12-1-2012
URL with Digital Object Identifier
10.1109/ICMLA.2012.193
Abstract
A software development project can be considered to be risky project due to the uncertainty of the information (customer requirements), the complexity of the process, and the intangible nature of the product. Under these conditions, risk management in software development projects is mandatory, but often it is difficult and expensive to implement. Expert COCOMO is an efficient approach to software project risk management, which leverages existing knowledge and expertise from previous effort estimation activities to assess the risk in a new software project. However, the original method has a limitation because it cannot effectively deal with imprecise and uncertain inputs in the form of linguistic terms such as: Very Low (VL), Low (L), Nominal (N), High (H), Very High (VH) and Extra High (XH). This paper introduces the fuzzy-ExCOM methodology that combines the advantages of a fuzzy technique with Expert COCOMO methodology for risk assessment in a software project. A validation of this approach with project data shows that fuzzy-ExCOM provides better risk assessment results with a higher level of sensitivity with respect to risk identification compared to the original Expert COCOMO methodology.
Citation Information
@inproceedings{DBLP:conf/icmla/ManalifCNH12, author = {Ekananta Manalif and Luiz Fernando Capretz and Ali Bou Nassif and Danny Ho}, title = {Fuzzy-ExCOM Software Project Risk Assessment}, booktitle = {ICMLA (2)}, year = {2012}, pages = {320-325}, ee = {http://dx.doi.org/10.1109/ICMLA.2012.193}, crossref = {DBLP:conf/icmla/2012-2}, bibsource = {DBLP, http://dblp.uni-trier.de} } @proceedings{DBLP:conf/icmla/2012-2, title = {11th International Conference on Machine Learning and Applications, ICMLA, Boca Raton, FL, USA, December 12-15, 2012. Volume 2}, booktitle = {ICMLA (2)}, publisher = {IEEE}, year = {2012}, isbn = {978-1-4673-4651-1}, ee = {http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6403616}, bibsource = {DBLP, http://dblp.uni-trier.de} }