Correction published on 10 August 2020,
see
Entropy 2020, 22(8), 878.
Measuring Software Modularity Based on Software Networks
1
School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China
2
School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China
3
Department of Computer Science, Western Michigan University, Kalamazoo, MI 49008, USA
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(4), 344; https://doi.org/10.3390/e21040344
Received: 14 February 2019 / Revised: 14 March 2019 / Accepted: 24 March 2019 / Published: 28 March 2019
(This article belongs to the Section Complexity)
Modularity has been regarded as one of the most important properties of a successful software design. It has significant impact on many external quality attributes such as reusability, maintainability, and understandability. Thus, proposing metrics to measure the software modularity can be very useful. Although several metrics have been proposed to characterize some modularity-related attributes, they fail to characterize software modularity as a whole. A complex network uses network models to abstract the internal structure of complex systems, providing a general way to analyze complex systems as a whole. In this paper, we introduce the complex network theory into software engineering and employ modularity, a metric widely used in the field of community detection in complex network research, to measure software modularity as a whole. First, a specific piece of software is represented by a software network, feature coupling network (FCN), where methods and attributes are nodes, couplings between methods and attributes are edges, and the weight on the edges denotes the coupling strength. Then, modularity is applied to the FCN to measure software modularity. We apply the Weyuker’s criteria which is widely used in the field of software metrics, to validate the modularity as a software metric theoretically, and also perform an empirical evaluation using open-source Java software systems to show its effectiveness as a software metric to measure software modularity.
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MDPI and ACS Style
Xiang, Y.; Pan, W.; Jiang, H.; Zhu, Y.; Li, H. Measuring Software Modularity Based on Software Networks. Entropy 2019, 21, 344. https://doi.org/10.3390/e21040344
AMA Style
Xiang Y, Pan W, Jiang H, Zhu Y, Li H. Measuring Software Modularity Based on Software Networks. Entropy. 2019; 21(4):344. https://doi.org/10.3390/e21040344
Chicago/Turabian StyleXiang, Yiming; Pan, Weifeng; Jiang, Haibo; Zhu, Yunfang; Li, Hao. 2019. "Measuring Software Modularity Based on Software Networks" Entropy 21, no. 4: 344. https://doi.org/10.3390/e21040344
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