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http://dx.doi.org/10.3745/KIPSTB.2006.13B.5.547

A Mechanism to Determine Method Location among Classes using Neural Network  

Jung, Young-A. (단국대학교 대학원 전자계산학과)
Park, Young-B. (단국대학교 전자컴퓨터학부)
Publication Information
The KIPS Transactions:PartB / v.13B, no.5, 2006 , pp. 547-552 More about this Journal
Abstract
There have been various cohesion measurements studied considering reference relation among attributes and methods in a class. Generally, these cohesion measurement are camed 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. Tn 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.
Keywords
Decision of Method Location; Cohesion; Refactoring; Neural Network; RPROP(Resilient Back Propagation);
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Times Cited By KSCI : 1  (Citation Analysis)
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