Abstract
In the software engineering, the class diagrams in the Unified Modeling Language show the collaboration relationship among classes to describe the structure of a system; nevertheless, how do the classes tend to collaborate with each other? This paper chooses the prevalent Java Development Kits to study the connectivity tendency of actual Java class collaboration networks based on the assortativity method. The collaboration between actual Java classes is analyzed and illustrated by statistics and charts. The empirical analysis finds that the out- and in-degrees of these networks display the anticorrelation and the weak disassortativity. The collaboration relationship between classes can be classified as strong and weak collaborations according to their assortativity coefficients, which is a highly statistically significant distinction.
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References
Pastor-Satorras R, Vázquez A, et al. Dynamical and correlation properties of the Internet. Phys Rev Lett. 2001;87(25):258701-1–4.
Barrat A, Barthélemy M, et al. Modeling the evolution of weighted networks. Phys Rev E. 2004;70(6):066149-1. 12.
Newman MEJ. Assortative mixing in networks. Phys Rev Lett. 2002;89(20):208701-1–4.
Myers CR. Software systems as complex networks: structure, function, and evolvability of software collaboration graphs. Phys Rev E. 2003;68(4):046116-1–15.
Subelj L, Zitnik S, et al. Node mixing and group structure of complex software networks. Adv Complex Syst. 2014;15(1):53–79.
Bhattacharya P, Iliofotou M. Graph-based analysis and prediction for software evolution. In: Proceedings of the 34th international conference on software engineering. Piscataway: IEEE Press; 2012. p. 419–29.
Pan WF, Li B, et al. Multi-granularity evolution analysis of software using complex network theory. J Syst Sci Complex. 2011;24(6):1068–82.
Zanetti MS, Sarigöl E, et al. A quantitative study of social organisation in open source software communities; 2013. arXiv:1208.4289.
Fuge M, Tee K, et al. Network analysis of collaborative design networks: a case study of OpenIDEOf. J Comput Inf Sci Eng. 2014;14(2):021009-1–8.
Bliss CA, Kloumann IM, et al. Twitter reciprocal reply networks exhibit assortativity with respect to happiness. J Comput Sci. 2012;3(5):388–97.
Barabási AL, Albert R, et al. Mean-field theory for scale-free networks. Physica A. 1999;272(1–2):173–87.
Acknowledgments
This work is supported by the National Natural Science Foundation of China (Grant No. 51205220) and the Scientific Research Foundation of Shanghai University of Engineering Science (Grant No. E1-0501-14-0106).
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Yan, D., Wang, K., Yang, M. (2015). Disassortativity of Class Collaboration Networks. In: Wong, W. (eds) Proceedings of the 4th International Conference on Computer Engineering and Networks. Lecture Notes in Electrical Engineering, vol 355. Springer, Cham. https://doi.org/10.1007/978-3-319-11104-9_129
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DOI: https://doi.org/10.1007/978-3-319-11104-9_129
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11103-2
Online ISBN: 978-3-319-11104-9
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