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Research and Analysis of Structural Hole and Matching Coefficient

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DOI: 10.4236/jsea.2010.311127    4,382 Downloads   8,043 Views   Citations

ABSTRACT

Measure is a map from the reality or experimental world to the mathematical world, through which people can more easily understand the properties of entities and the relationship between them. But the traditional software measurement methods have been unable to effectively measure this large-scale software. Therefore, trustworthy measurement gives an accurate measurement to these emerging features, providing valuable perspectives and different research dimensions to understand software systems. The paper introduces the complex network theory to software measurement methods and proposes a statistical measurement methodology. First we study the basic parameters of the complex network, and then introduce two new measurement parameters: structural holes, matching coefficient.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

P. Cai, H. Zhao, H. Liu, R. Pan, Z. Liu and H. Li, "Research and Analysis of Structural Hole and Matching Coefficient," Journal of Software Engineering and Applications, Vol. 3 No. 11, 2010, pp. 1080-1087. doi: 10.4236/jsea.2010.311127.

References

[1] M. Gaertler and R. J. Mondragon, “Accurately Modeling the Internet Topology,” Physics Review E, Vol. 66, No. 18, 2006, pp. 163-167.
[2] R. S. Burt, “Structural Holes: The Social Structure of Competition,” Harvard University Press, 1995, PP. 35-38.
[3] S. Abdelwahed, N. Kandasamy and A. Gokhale, “High Confidence Sofware for Cyber-Physical Systems,” Proceedings of the 2007 Workshop on Automating Service Quality, Atlanta, 2007, PP. 1-3.
[4] Y. T. Ma, J. X. Chen and J. H. Wu, “Research on the Phenomenon of Software Drift in Software Processes,” Proceedings of 8th International Workshop on Principles of Software Evolution, Lisbon, September 2005, pp. 195-198.
[5] M. Alshayeb and W. Li, “An Empirical Validation of Object-Oriented Metrics in Two Different Iterative Software Processes,” IEEE Transactions on Software Engineering, Vol. 29, No. 11, November 2003, pp. 1043- 1049.
[6] L. C. Briand, S. Morasca and V. R. Basili, “Property-Based Software Engineering Measurement,” IEEE Transactions on Software Engineering, Vol. 22, No. 1, January 1996, pp. 68-86.
[7] S. Furey, “Why We Should Use Function Points,” IEEE Software, Vol. 14, No. 2, 1997, pp. 28-30.
[8] M. Arnold and P. Pedross, “Software Size Measurement and Productivity Rating in a Large-Scale Software Development Department,” Proceedings of 20th International Conference on Software Engineering, Kyoto, 1998, pp. 503-506.
[9] M. Bauer, “Analysing Software Systems by Using Combinations of Metrics,” Proceedings of ECOOP’99 Workshops, Lisbon, 1999, pp. 170-171.
[10] S. R. Chidamber and C. F. Kemerer, “A Metrics Suite for Object-Oriented Design,” IEEE Transactions on Software Engineering, Vol. 20, No. 6, June 1994, pp. 476-493.
[11] F. B. e Abreu, “The MOOD Metrics Set,” Proceedings of ECOOP’95 Workshop on Metrics, Aarhus, 1995, pp. 150-152.
[12] N. E. Fenton and M. Neil, “Software Metrics: Successes, Failures and New Directions,” Journal of Systems and Software, Vol. 47, No. 2-3, July 1999, pp. 149-157.

  
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