A Mechanism to Determine Method Location among Classes using Neural Network


The KIPS Transactions:PartB , Vol. 13, No. 5, pp. 547-552, Oct. 2006
10.3745/KIPSTB.2006.13.5.547,   PDF Download:

Abstract

There have been various cohesion measurements studied considering reference relation among attributes and methods in a class. Generally, these cohesion measurement are carried out in one class. If the range of reference relation considered are extended from one class to two classes, we could find out the reference relation between two classes. In this paper, we proposed a neural network to determine the method location. Neural network is effective to predict output value from input data not to be included in training and generalize after training input and output pattern repeatedly. Learning vector is generated with 30-dimensional input vector and one target binary values of method location in a constraint that there are two classes which have less than or equal to 5 attributes and methods. The result of the proposed neural network is about 95% in cross-validation and 88% in testing.


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Cite this article
[IEEE Style]
Y. A. Jung and Y. B. Park, "A Mechanism to Determine Method Location among Classes using Neural Network," The KIPS Transactions:PartB , vol. 13, no. 5, pp. 547-552, 2006. DOI: 10.3745/KIPSTB.2006.13.5.547.

[ACM Style]
Young A. Jung and Young B. Park. 2006. A Mechanism to Determine Method Location among Classes using Neural Network. The KIPS Transactions:PartB , 13, 5, (2006), 547-552. DOI: 10.3745/KIPSTB.2006.13.5.547.