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AUTHOR(S): 

Jehad Al Dallal

 

TITLE

Empirical Investigation of the Impact of Accounting for Transitive Relationships on Lack-of-Cohesion Measurement

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ABSTRACT

The quality of a class in object oriented system has a great impact on the overall quality of the software. Class cohesion, which refers to the degree of relatedness of the class members, is an important quality aspect. A few of class cohesion metrics, which are proposed in the literature, empirically address the impact of accounting for transitive relations between class attributes and methods caused by method invocations. This paper provides an empirical evaluation for the impact of considering transitive relationships on class cohesion quantified by one of the most popular class cohesion metrics, referenced as Lack of Cohesion (LCOM). The metric is applied with and without considering transitive relations on classes of two open source Java applications and the results are statistically analyzed. The results provide an evidence that the ability of LCOM in precisely indicating class quality enhances when accounting for both direct and transitive relations in the LCOM measurement.

KEYWORDS

object-oriented class, software quality, class cohesion metric, class cohesion, direct and transitive relations

REFERENCES

[1] J. Al Dallal and L. Briand, A Precise method-method interaction-based cohesion metric for object-oriented classes, ACM Transactions on Software Engineering and Methodology (TOSEM), 2012, Vol. 21, No. 2, pp. 8:1- 8:34.

[2] J. Al Dallal, Mathematical validation of objectoriented class cohesion metrics, International Journal of Computers, 2010, Vol. 4, No. 2, pp. 45-52.

[3] L. C. Briand, J. Daly, and J. Wuest, A unified framework for cohesion measurement in object-oriented systems, Empirical Software Engineering - An International Journal, Vol. 3, No. 1, 1998, pp. 65-117.

[4] J. M. Bieman and B. Kang, Cohesion and reuse in an object-oriented system, Proceedings of the 1995 Symposium on Software reusability, Seattle, Washington, United States, pp. 259-262, 1995.

[5] L. Badri and M. Badri, A Proposal of a new class cohesion criterion: an empirical study, Journal of Object Technology, Vol. 3, No. 4, 2004..

[6] L. Fernández, and R. Peña, A sensitive metric of class cohesion, International Journal of Information Theories and Applications, Vol. 13, No. 1, 2006, pp. 82- 91.

[7] C. Bonja and E. Kidanmariam, Metrics for class cohesion and similarity between methods, Proceedings of the 44th Annual ACM Southeast Regional Conference, Melbourne, Florida, 2006, pp. 91-95.

[8] J. Bansiya, L. Etzkorn, C. Davis, and W. Li, A class cohesion metric for object-oriented designs, Journal of Object-Oriented Program, Vol. 11, No. 8, pp. 47-52. 1999.

[9] S. Counsell , S. Swift , and J. Crampton, The interpretation and utility of three cohesion metrics for object-oriented design, ACM Transactions on Software Engineering and Methodology (TOSEM), Vol. 15, No. 2, 2006, pp.123-149.

[10] J. Al Dallal, A design-based cohesion metric for object-oriented classes, International Journal of Computer Science and Engineering, 2007, Vol. 1, No. 3, pp. 195-200.

[11] J. Al Dallal, Software similarity-based functional cohesion metric, IET Software, 2009, Vol. 3, No. 1, pp. 46- 57.

[12] J. Al Dallal, Theoretical validation of object-oriented lack-of-cohesion metrics, proceedings of the 8th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (SEPADS 2009), Cambridge, UK, February 2009.

[13] J. Al Dallal and L. Briand, An object-oriented highlevel design-based class cohesion metric, Information and Software Technology, 2010, Vol. 52, No. 12, pp. 1346- 1361.

[14] J. Al Dallal, Fault prediction and the discriminative powers of connectivity-based object-oriented class cohesion metrics, Information and Software Technology, 2012, Vol. 54, No. 4, pp. 396-416.

[15] S.R. Chidamber and C.F. Kemerer, Towards a Metrics Suite for Object-Oriented Design, Object-Oriented Programming Systems, Languages and Applications (OOPSLA), Special Issue of SIGPLAN Notices, Vol. 26, No. 10, 1991, pp. 197-211.

[16] S.R. Chidamber and C.F. Kemerer, A Metrics suite for object Oriented Design, IEEE Transactions on Software Engineering, Vol. 20, No. 6, 1994, pp. 476-493.

[17] W. Li and S.M. Henry, Maintenance metrics for the object oriented paradigm. In Proceedings of 1st International Software Metrics Symposium, Baltimore, MD, 1993, pp. 52-60.

[18] M. Hitz and B. Montazeri, Measuring coupling and cohesion in object oriented systems, Proceedings of the International Symposium on Applied Corporate Computing, 1995, pp. 25-27.

[19] B. Henderson-Sellers, Software Metrics, Prentice Hall, Hemel Hempstaed, U.K., 1996.

[20] J. Al Dallal, Efficient program slicing algorithms for measuring functional cohesion and parallelism, International Journal of Information Technology, Vol. 4, No. 2, 2007, pp. 93-100.

[21] J. Al Dallal, Improving the applicability of objectoriented class cohesion metrics, Information and Software Technology, 2011, Vol. 53, No. 9, pp. 914-928.

[22] Illusion, http://sourceforge.net/projects/aoi/, July 2010.

[23] JabRef, http://sourceforge.net/projects/jabref/, July 2010.

[24] D. Hosmer and S. Lemeshow, Applied Logistic Regression, Wiley Interscience, 2000, 2nd edition.

[25] L. C. Briand, J. Wüst, and H. Lounis, Replicated Case Studies for Investigating Quality Factors in ObjectOriented Designs, Empirical Software Engineering, 6(1), 2001, pp. 11-58.

[26] T. Gyimothy, R. Ferenc, and I. Siket, Empirical validation of object-oriented metrics on open source software for fault prediction, IEEE Transactions on Software Engineering, 3(10), 2005, pp. 897-910.

[27] A. Marcus, D. Poshyvanyk, and R. Ferenc, Using the conceptual cohesion of classes for fault prediction in object-oriented systems, IEEE Transactions on Software Engineering, 34(2), 2008, pp. 287-300.

[28] J. A. Hanley and B. J. McNeil, The meaning and use of the area under a receiver operating characteristic (ROC) curve, Radiology, 143(1), 1982, pp. 29-36.

[29] J. Al Dallal, Accounting for data encapsulation in the measurement of object-oriented class cohesion, Journal of Software: Evolution And Process, Vol. 27, No. 5, 2015, pp. 373-400.

[30] J. Al Dallal, The effects of incorporating special methods into cohesion measurement on class instantiation reuse-proneness prediction, IET Software, 2014, Vol. 8, No. 6, pp. 285-295.

[31] J. Al Dallal and S. Morasca, Predicting objectoriented class reuse-proneness using internal quality attributes, Empirical Software Engineering, Vol. 19, No. 4, 2014, pp. 775-821.

[32] 26.J. Al Dallal, The impact of inheritance on the internal quality attributes of java classes, Kuwait Journal of Science and Engineering, 2012, Vol. 39, No. 2A, pp. 131- 154.

Cite this paper

Jehad Al Dallal. (2016) Empirical Investigation of the Impact of Accounting for Transitive Relationships on Lack-of-Cohesion Measurement. International Journal of Computers, 1, 237-241

 

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