Identifying Thresholds for Similarity-Based Class Cohesion (SCC) Metrics

Author

Fajar Pradana, Bayu Priyambadha, Denny Sagita Rusdianto

Abstract

Abstract. The object-oriented design (OOD) concept can be used to implement a quality measurement program is based on the possibility of inter-relationship between attributes and methods in the class diagram and interaction between objects on a communication diagram. The process of calculating the value of cohesion on the design of object-oriented software using Similarity-Based Class Cohesion metrics can be done by identifying the relationship between the three types of possible interaction between those methods, method-attribute, and interaction attribute-attribute. But the existence of such measurements theory is rarely used in the software development industry. This is due to there is no threshold value that is used as the limit of good or bad design. This study aims to determine the threshold of cohesion metric based on the class diagram. The result showed that the threshold of SCC metric is 0.45. 0.45 is the value that has the highest level of agreement with the design expert

Full Text:

PDF

References


Dallal, J.A. dan Briand L.C. (2010) “An Object Oriented High-Level Design-Based Class Cohesion Metric”. Journal Information and Software Technology.

J. Al Dallal, “A design-based cohesion metric for object-oriented classes,” Int. J. Comput. Sci. …, vol. 1, no. 3, pp. 195–200, 2007.

J. Al Dallal, “Measuring the discriminative power of object-oriented class cohesion metrics,” IEEE Trans. Softw. Eng., vol. 37, no. 6, pp. 788–804, 2011.

Yunis Roni dan Halim Arwin. (2014) “Studi Empiris Hubungan Metrik Kohesi Dengan Kecenderungan Kesalahan Pada Aplikasi Berorientasi Objek”. STMIK Mikroskil

K. A. M. Ferreira, M. A. S. Bigonha, R. S. Bigonha, L. F. O. Mendes, and H. C. Almeida, “Identifying thresholds for object-oriented software metrics,” J. Syst. Softw., vol. 85, no. 2, pp. 244–257, 2012.

J. Sim and C. C. Wright, “The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size Requirements,” Phys. Ther., vol. 85, no. 3, pp. 257–68, Mar. 2005.

I. Chowdhury and M. Zulkernine, “Using complexity, coupling, and cohesion metrics as early indicators of vulnerabilities,” J. Syst. Archit., vol. 57, no. 3, pp. 294–313, 2011.




DOI: http://dx.doi.org/10.25126/jitecs.20161213