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Research and Measurement of Software Complexity Based on Wuli, Shili, Renli (WSR) and Information Entropy

by Rong Jiang 1,2
School of Information, Yunnan University of Finance and Economics, Kunming 650221, China
School of Software, Yunnan University, Kunming, 650091, China 
Academic Editor: J. A. Tenreiro Machado
Entropy 2015, 17(4), 2094-2116;
Received: 30 December 2014 / Revised: 31 March 2015 / Accepted: 1 April 2015 / Published: 8 April 2015
Complexity is an important factor throughout the software life cycle. It is increasingly difficult to guarantee software quality, cost and development progress with the increase in complexity. Excessive complexity is one of the main reasons for the failure of software projects, so effective recognition, measurement and control of complexity becomes the key of project management. At first, this paper analyzes the current research situation of software complexity systematically and points out existing problems in current research. Then, it proposes a WSR framework of software complexity, which divides the complexity of software into three levels of Wuli (WL), Shili (SL) and Renli (RL), so that the staff in different roles may have a better understanding of complexity. Man is the main source of complexity, but the current research focuses on WL complexity, and the research of RL complexity is extremely scarce, so this paper emphasizes the research of RL complexity of software projects. This paper not only analyzes the composing factors of RL complexity, but also provides the definition of RL complexity. Moreover, it puts forward a quantitative measurement method of the complexity of personnel organization hierarchy and the complexity of personnel communication information based on information entropy first and analyzes and validates the scientificity and rationality of this measurement method through a large number of cases. View Full-Text
Keywords: software complexity; software project; WSR; information entropy software complexity; software project; WSR; information entropy
MDPI and ACS Style

Jiang, R. Research and Measurement of Software Complexity Based on Wuli, Shili, Renli (WSR) and Information Entropy. Entropy 2015, 17, 2094-2116.

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