Title :
Fuzzy-ExCOM Software Project Risk Assessment
Author :
Manalif, E. ; Capretz, Luiz Fernando ; Nassif, Ali Bou ; Ho, D.
Author_Institution :
Dept. of Electr. & Comput. Eng., Western Univ., London, ON, Canada
Abstract :
A software development project is considered to be risky 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 risks in new software projects. However, the original method has 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 software projects. The validation of this approach with industrial 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.
Keywords :
computational linguistics; fuzzy set theory; program verification; project management; risk management; software engineering; software management; Expert COCOMO methodology; effort estimation activities; extra high linguistic terms; fuzzy technique; fuzzy-ExCOM software project risk assessment; high linguistic terms; industrial data; information uncertainty; low linguistic terms; nominal linguistic terms; process complexity; risk identification; software development project; software development projects; very high linguistic terms; very low linguistic terms; Correlation; Estimation; Industries; Planning; Risk management; Sensitivity; Software; fuzzy technique; risk assessment; software project;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2012 11th International Conference on
Conference_Location :
Boca Raton, FL
Print_ISBN :
978-1-4673-4651-1
DOI :
10.1109/ICMLA.2012.193