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Journal of Information Science and Engineering, Vol. 30 No. 4, pp. 1279-1301 (September 2014)


An Information-Entropy-based Risk Measurement Method of Software Development Project*


RONG JIANG1,2
1School of Information
Yunnan University of Finance and Economics
Kunming, 650221 P.R. China
2School of Software
Yunnan University
Kunming, 650091 P.R. China
E-mail: okgoodbetterbest@163.com

Risk is the major reason for the failure of software development projects. The risk measurement can provide the decision-making data for the risk management and control. The traditional risk measurement method usually assesses in terms of the occurrence probability and the loss of the risk factors, which usually are assessed by experts subjectively. Therefore, they are greatly influenced by artificial factors. In this way, it is difficult to realize the objective and effective measurement. This paper proposes one risk measurement method of software development project based on information entropy, which makes up for the shortcomings of the former studies. This method makes use of information entropy to measure the amount of information so as to measure the software development project risk. In this paper, a new risk checklist is given. First of all, it obtains the risk information through the checklist. Then it obtains the information amount of risk factors by aid of information entropy. This paper concludes that the larger the information amount of the risk factors is, the larger the removed uncertainty is, the smaller the information entropy is and the smaller the risk is. In short, there is a positive correlation between risk and entropy. This paper demonstrates the scientificity and rationality of the method theoretically. Compared with other risk measurement methods, this method manifests certain advantage. The case analysis prove the rationality and feasibility of this method.

Keywords: risk measurement, software development project, information entropy, risk checklist, measurement method

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Received October 12, 2013; revised December 23, 2013; accepted February 15, 21014.
Communicated by Jiann-Liang Chen.
* This work was supported by National Natural Science Foundation of China (Grant No. 61263022, 61303234 and 71362016), China Postdoctoral Science Foundation (Grant No. 2012M521722), National Social Science Foundation of China (Grant No. 12XTQ012), Humanities and Social Sciences Youthful Foundation of the Ministry of Education of China (Grant No. 11YJCZH073), Introduction of Talents Project of Science Research Foundation of Yunnan University of Finance and Economics (Grant No. YC2012D07).